[{"citation":{"bibtex":"@inproceedings{Özcan_Kirchberg_Koldewey_Dumitrescu_2022, place={Athens}, title={Performance Management Approach for Digital Platforms in B2B Markets}, booktitle={The Role of Innovation: Past, Present, Future}, author={Özcan, Leon and Kirchberg, Lisa Irene and Koldewey, Christian and Dumitrescu, Roman}, editor={Bitran, Iain and Bitetti, Leandro and  Conn, Steffen and Fishburn, Jessica and Huizingh, Eelko  and Torkkeli, Marko and Yang, Jialei}, year={2022} }","chicago":"Özcan, Leon, Lisa Irene Kirchberg, Christian Koldewey, and Roman Dumitrescu. “Performance Management Approach for Digital Platforms in B2B Markets.” In <i>The Role of Innovation: Past, Present, Future</i>, edited by Iain Bitran, Leandro Bitetti, Steffen  Conn, Jessica Fishburn, Eelko  Huizingh, Marko Torkkeli, and Jialei Yang. Athens, 2022.","short":"L. Özcan, L.I. Kirchberg, C. Koldewey, R. Dumitrescu, in: I. Bitran, L. Bitetti, S.  Conn, J. Fishburn, E. Huizingh, M. Torkkeli, J. Yang (Eds.), The Role of Innovation: Past, Present, Future, Athens, 2022.","ama":"Özcan L, Kirchberg LI, Koldewey C, Dumitrescu R. Performance Management Approach for Digital Platforms in B2B Markets. In: Bitran I, Bitetti L,  Conn S, et al., eds. <i>The Role of Innovation: Past, Present, Future</i>. ; 2022.","ieee":"L. Özcan, L. I. Kirchberg, C. Koldewey, and R. Dumitrescu, “Performance Management Approach for Digital Platforms in B2B Markets,” in <i>The Role of Innovation: Past, Present, Future</i>, Athens, 2022.","apa":"Özcan, L., Kirchberg, L. I., Koldewey, C., &#38; Dumitrescu, R. (2022). Performance Management Approach for Digital Platforms in B2B Markets. In I. Bitran, L. Bitetti, S.  Conn, J. Fishburn, E. Huizingh, M. Torkkeli, &#38; J. Yang (Eds.), <i>The Role of Innovation: Past, Present, Future</i>.","mla":"Özcan, Leon, et al. “Performance Management Approach for Digital Platforms in B2B Markets.” <i>The Role of Innovation: Past, Present, Future</i>, edited by Iain Bitran et al., 2022."},"file_date_updated":"2022-11-04T07:30:29Z","place":"Athens","conference":{"start_date":"2022-11-28","name":"ISPIM Connects Athens","location":"Athens","end_date":"2022-11-30"},"status":"public","has_accepted_license":"1","_id":"33997","editor":[{"last_name":"Bitran","first_name":"Iain","full_name":"Bitran, Iain"},{"full_name":"Bitetti, Leandro","last_name":"Bitetti","first_name":"Leandro"},{"last_name":" Conn","first_name":"Steffen","full_name":" Conn, Steffen"},{"first_name":"Jessica","last_name":"Fishburn","full_name":"Fishburn, Jessica"},{"last_name":"Huizingh","first_name":"Eelko ","full_name":"Huizingh, Eelko "},{"full_name":"Torkkeli, Marko","first_name":"Marko","last_name":"Torkkeli"},{"full_name":"Yang, Jialei","first_name":"Jialei","last_name":"Yang"}],"ddc":["600"],"user_id":"1112","publication":"The Role of Innovation: Past, Present, Future","abstract":[{"lang":"eng","text":"Digital platforms have already led to disruptions in multiple B2C markets and are becoming increasingly dominant in B2B markets. As a result, more and more companies are trying to participate in the platform economy. However, the successful development and operation of a digital platform is associated with significant challenges, which leads to 85% of all platforms failing. A core challenge is the dynamic nature of the platform economy, with varying strategic objectives at different stages in the platform lifecycle. Platform operators must continuously monitor platform progress and adjust their strategy.\r\nUtilizing action research in the real-world platform project AI Marketplace, we developed a lifecycle-oriented performance management approach for digital platforms in B2B markets. It enables platform operators to reflect on their position in the platform lifecycle, derive relevant strategic objectives, and monitor them with suitable key performance indicators. Hence, allowing them to secure the long-term success of their platform business."}],"date_created":"2022-11-04T07:31:57Z","file":[{"date_created":"2022-11-04T07:30:29Z","creator":"loezcan","content_type":"application/pdf","success":1,"file_id":"33998","date_updated":"2022-11-04T07:30:29Z","relation":"main_file","access_level":"closed","file_size":694337,"file_name":"[ÖKK+22] Performance Management Approach for Digital Platforms in B2B Markets.pdf"}],"department":[{"_id":"563"}],"type":"conference","keyword":["Digital Platform","Two-Sided Market","Multi-Sided Market","Platform Lifecycle","Platform Monitoring","Performance Management"],"publication_identifier":{"unknown":["978-952-65069-1-3"]},"author":[{"id":"45137","full_name":"Özcan, Leon","last_name":"Özcan","first_name":"Leon"},{"id":"63192","first_name":"Lisa Irene","last_name":"Kirchberg","full_name":"Kirchberg, Lisa Irene"},{"first_name":"Christian","last_name":"Koldewey","full_name":"Koldewey, Christian"},{"full_name":"Dumitrescu, Roman","first_name":"Roman","last_name":"Dumitrescu"}],"year":"2022","title":"Performance Management Approach for Digital Platforms in B2B Markets","date_updated":"2024-09-30T07:59:27Z","language":[{"iso":"eng"}]},{"keyword":["neural networks","physics-guided","data-driven","multi-objective optimization","system identification","machine learning","dynamical systems"],"type":"conference","department":[{"_id":"153"},{"_id":"880"}],"date_created":"2022-05-05T06:22:55Z","abstract":[{"text":"While trade-offs between modeling effort and model accuracy remain a major concern with system identification, resorting to data-driven methods often leads to a complete disregard for physical plausibility. To address this issue, we propose a physics-guided hybrid approach for modeling non-autonomous systems under control. Starting from a traditional physics-based model, this is extended by a recurrent neural network and trained using a sophisticated multi-objective strategy yielding physically plausible models. While purely data-driven methods fail to produce satisfying results, experiments conducted on real data reveal substantial accuracy improvements by our approach compared to a physics-based model. ","lang":"eng"}],"publication":"14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)","issue":"12","doi":"https://doi.org/10.1016/j.ifacol.2022.07.282","language":[{"iso":"eng"}],"date_updated":"2024-11-13T08:43:16Z","intvolume":"        55","title":"Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems","year":"2022","author":[{"full_name":"Schön, Oliver","first_name":"Oliver","last_name":"Schön"},{"first_name":"Ricarda-Samantha","last_name":"Götte","full_name":"Götte, Ricarda-Samantha","id":"43992"},{"last_name":"Timmermann","first_name":"Julia","full_name":"Timmermann, Julia","id":"15402"}],"quality_controlled":"1","citation":{"apa":"Schön, O., Götte, R.-S., &#38; Timmermann, J. (2022). Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>, <i>55</i>(12), 19–24. <a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>","ieee":"O. Schön, R.-S. Götte, and J. Timmermann, “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems,” in <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>, Casablanca, Morocco, 2022, vol. 55, no. 12, pp. 19–24, doi: <a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>.","short":"O. Schön, R.-S. Götte, J. Timmermann, in: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 2022, pp. 19–24.","chicago":"Schön, Oliver, Ricarda-Samantha Götte, and Julia Timmermann. “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems.” In <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>, 55:19–24, 2022. <a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>.","mla":"Schön, Oliver, et al. “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems.” <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>, vol. 55, no. 12, 2022, pp. 19–24, doi:<a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>.","ama":"Schön O, Götte R-S, Timmermann J. Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. In: <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>. Vol 55. ; 2022:19-24. doi:<a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>","bibtex":"@inproceedings{Schön_Götte_Timmermann_2022, title={Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems}, volume={55}, DOI={<a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>}, number={12}, booktitle={14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)}, author={Schön, Oliver and Götte, Ricarda-Samantha and Timmermann, Julia}, year={2022}, pages={19–24} }"},"user_id":"43992","volume":55,"page":"19-24","_id":"31066","status":"public","conference":{"end_date":"2022-07-01","location":"Casablanca, Morocco","name":"14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)","start_date":"2022-06-29"}},{"_id":"21004","language":[{"iso":"eng"}],"page":"1-1","doi":"10.1109/tpami.2021.3051276","user_id":"5786","author":[{"id":"33176","first_name":"Marcel Dominik","last_name":"Wever","orcid":" https://orcid.org/0000-0001-9782-6818","full_name":"Wever, Marcel Dominik"},{"last_name":"Tornede","first_name":"Alexander","full_name":"Tornede, Alexander","id":"38209"},{"last_name":"Mohr","first_name":"Felix","full_name":"Mohr, Felix"},{"id":"48129","last_name":"Hüllermeier","first_name":"Eyke","full_name":"Hüllermeier, Eyke"}],"publication_identifier":{"issn":["0162-8828","2160-9292","1939-3539"]},"year":"2021","title":"AutoML for Multi-Label Classification: Overview and Empirical Evaluation","status":"public","date_updated":"2022-01-06T06:54:42Z","publication_status":"published","date_created":"2021-01-16T14:48:13Z","department":[{"_id":"34"},{"_id":"355"},{"_id":"26"}],"keyword":["Automated Machine Learning","Multi Label Classification","Hierarchical Planning","Bayesian Optimization"],"type":"journal_article","citation":{"ieee":"M. D. Wever, A. Tornede, F. Mohr, and E. Hüllermeier, “AutoML for Multi-Label Classification: Overview and Empirical Evaluation,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, pp. 1–1, 2021, doi: <a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>.","mla":"Wever, Marcel Dominik, et al. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, 2021, pp. 1–1, doi:<a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>.","apa":"Wever, M. D., Tornede, A., Mohr, F., &#38; Hüllermeier, E. (2021). AutoML for Multi-Label Classification: Overview and Empirical Evaluation. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, 1–1. <a href=\"https://doi.org/10.1109/tpami.2021.3051276\">https://doi.org/10.1109/tpami.2021.3051276</a>","bibtex":"@article{Wever_Tornede_Mohr_Hüllermeier_2021, title={AutoML for Multi-Label Classification: Overview and Empirical Evaluation}, DOI={<a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, author={Wever, Marcel Dominik and Tornede, Alexander and Mohr, Felix and Hüllermeier, Eyke}, year={2021}, pages={1–1} }","chicago":"Wever, Marcel Dominik, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, 2021, 1–1. <a href=\"https://doi.org/10.1109/tpami.2021.3051276\">https://doi.org/10.1109/tpami.2021.3051276</a>.","short":"M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) 1–1.","ama":"Wever MD, Tornede A, Mohr F, Hüllermeier E. AutoML for Multi-Label Classification: Overview and Empirical Evaluation. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. Published online 2021:1-1. doi:<a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>"},"publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"_id":"10","name":"SFB 901 - Subproject B2"},{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"abstract":[{"text":"Automated machine learning (AutoML) supports the algorithmic construction and data-specific customization of machine learning pipelines, including the selection, combination, and parametrization of machine learning algorithms as main constituents. Generally speaking, AutoML approaches comprise two major components: a search space model and an optimizer for traversing the space. Recent approaches have shown impressive results in the realm of supervised learning, most notably (single-label) classification (SLC). Moreover, first attempts at extending these approaches towards multi-label classification (MLC) have been made. While the space of candidate pipelines is already huge in SLC, the complexity of the search space is raised to an even higher power in MLC. One may wonder, therefore, whether and to what extent optimizers established for SLC can scale to this increased complexity, and how they compare to each other. This paper makes the following contributions: First, we survey existing approaches to AutoML for MLC. Second, we augment these approaches with optimizers not previously tried for MLC. Third, we propose a benchmarking framework that supports a fair and systematic comparison. Fourth, we conduct an extensive experimental study, evaluating the methods on a suite of MLC problems. We find a grammar-based best-first search to compare favorably to other optimizers.","lang":"eng"}]},{"citation":{"chicago":"Schneider, Stefan Balthasar, Ramin Khalili, Adnan Manzoor, Haydar Qarawlus, Rafael Schellenberg, Holger Karl, and Artur Hecker. “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning.” <i>Transactions on Network and Service Management</i>, 2021. <a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">https://doi.org/10.1109/TNSM.2021.3076503</a>.","short":"S.B. Schneider, R. Khalili, A. Manzoor, H. Qarawlus, R. Schellenberg, H. Karl, A. Hecker, Transactions on Network and Service Management (2021).","apa":"Schneider, S. B., Khalili, R., Manzoor, A., Qarawlus, H., Schellenberg, R., Karl, H., &#38; Hecker, A. (2021). Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning. <i>Transactions on Network and Service Management</i>. <a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">https://doi.org/10.1109/TNSM.2021.3076503</a>","ieee":"S. B. Schneider <i>et al.</i>, “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning,” <i>Transactions on Network and Service Management</i>, 2021.","ama":"Schneider SB, Khalili R, Manzoor A, et al. Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning. <i>Transactions on Network and Service Management</i>. 2021. doi:<a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">10.1109/TNSM.2021.3076503</a>","bibtex":"@article{Schneider_Khalili_Manzoor_Qarawlus_Schellenberg_Karl_Hecker_2021, title={Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning}, DOI={<a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">10.1109/TNSM.2021.3076503</a>}, journal={Transactions on Network and Service Management}, publisher={IEEE}, author={Schneider, Stefan Balthasar and Khalili, Ramin and Manzoor, Adnan and Qarawlus, Haydar and Schellenberg, Rafael and Karl, Holger and Hecker, Artur}, year={2021} }","mla":"Schneider, Stefan Balthasar, et al. “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning.” <i>Transactions on Network and Service Management</i>, IEEE, 2021, doi:<a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">10.1109/TNSM.2021.3076503</a>."},"file_date_updated":"2021-04-27T08:01:26Z","project":[{"_id":"1","name":"SFB 901"},{"_id":"4","name":"SFB 901 - Project Area C"},{"name":"SFB 901 - Subproject C4","_id":"16"}],"oa":"1","status":"public","has_accepted_license":"1","publisher":"IEEE","_id":"21808","user_id":"35343","ddc":["000"],"publication":"Transactions on Network and Service Management","abstract":[{"text":"Modern services consist of interconnected components,e.g., microservices in a service mesh or machine learning functions in a pipeline. These services can scale and run across multiple network nodes on demand. To process incoming traffic, service components have to be instantiated and traffic assigned to these instances, taking capacities, changing demands, and Quality of Service (QoS) requirements into account. This challenge is usually solved with custom approaches designed by experts. While this typically works well for the considered scenario, the models often rely on unrealistic assumptions or on knowledge that is not available in practice (e.g., a priori knowledge).\r\n\r\nWe propose DeepCoord, a novel deep reinforcement learning approach that learns how to best coordinate services and is geared towards realistic assumptions. It interacts with the network and relies on available, possibly delayed monitoring information. Rather than defining a complex model or an algorithm on how to achieve an objective, our model-free approach adapts to various objectives and traffic patterns. An agent is trained offline without expert knowledge and then applied online with minimal overhead. Compared to a state-of-the-art heuristic, DeepCoord significantly improves flow throughput (up to 76%) and overall network utility (more than 2x) on realworld network topologies and traffic traces. It also supports optimizing multiple, possibly competing objectives, learns to respect QoS requirements, generalizes to scenarios with unseen, stochastic traffic, and scales to large real-world networks. For reproducibility and reuse, our code is publicly available.","lang":"eng"}],"date_created":"2021-04-27T08:04:16Z","file":[{"description":"Author version of the accepted paper","date_created":"2021-04-27T08:01:26Z","creator":"stschn","content_type":"application/pdf","file_id":"21809","date_updated":"2021-04-27T08:01:26Z","relation":"main_file","file_size":4172270,"access_level":"open_access","file_name":"ris-accepted-version.pdf"}],"department":[{"_id":"75"}],"type":"journal_article","keyword":["network management","service management","coordination","reinforcement learning","self-learning","self-adaptation","multi-objective"],"author":[{"orcid":"0000-0001-8210-4011","first_name":"Stefan Balthasar","last_name":"Schneider","full_name":"Schneider, Stefan Balthasar","id":"35343"},{"full_name":"Khalili, Ramin","last_name":"Khalili","first_name":"Ramin"},{"first_name":"Adnan","last_name":"Manzoor","full_name":"Manzoor, Adnan"},{"full_name":"Qarawlus, Haydar","first_name":"Haydar","last_name":"Qarawlus"},{"last_name":"Schellenberg","first_name":"Rafael","full_name":"Schellenberg, Rafael"},{"last_name":"Karl","first_name":"Holger","full_name":"Karl, Holger","id":"126"},{"full_name":"Hecker, Artur","first_name":"Artur","last_name":"Hecker"}],"title":"Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning","year":"2021","article_type":"original","date_updated":"2022-01-06T06:55:15Z","language":[{"iso":"eng"}],"doi":"10.1109/TNSM.2021.3076503"},{"has_accepted_license":"1","date_updated":"2022-11-18T09:59:27Z","author":[{"orcid":"0000-0001-8210-4011","last_name":"Schneider","first_name":"Stefan Balthasar","full_name":"Schneider, Stefan Balthasar","id":"35343"},{"full_name":"Karl, Holger","last_name":"Karl","first_name":"Holger","id":"126"},{"first_name":"Ramin","last_name":"Khalili","full_name":"Khalili, Ramin"},{"last_name":"Hecker","first_name":"Artur","full_name":"Hecker, Artur"}],"year":"2021","status":"public","title":"DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning","ddc":["004"],"user_id":"477","_id":"33854","language":[{"iso":"eng"}],"project":[{"_id":"4","name":"SFB 901 - C: SFB 901 - Project Area C"},{"name":"SFB 901 - C4: SFB 901 - Subproject C4","_id":"16"},{"name":"SFB 901: SFB 901","_id":"1"}],"abstract":[{"text":"Macrodiversity is a key technique to increase the capacity of mobile networks. It can be realized using coordinated multipoint (CoMP), simultaneously connecting users to multiple overlapping cells. Selecting which users to serve by how many and which cells is NP-hard but needs to happen continuously in real time as users move and channel state changes. Existing approaches often require strict assumptions about or perfect knowledge of the underlying radio system, its resource allocation scheme, or user movements, none of which is readily available in practice.\r\n\r\nInstead, we propose three novel self-learning and self-adapting approaches using model-free deep reinforcement learning (DRL): DeepCoMP, DD-CoMP, and D3-CoMP. DeepCoMP leverages central observations and control of all users to select cells almost optimally. DD-CoMP and D3-CoMP use multi-agent DRL, which allows distributed, robust, and highly scalable coordination. All three approaches learn from experience and self-adapt to varying scenarios, reaching 2x higher Quality of Experience than other approaches. They have very few built-in assumptions and do not need prior system knowledge, making them more robust to change and better applicable in practice than existing approaches.","lang":"eng"}],"citation":{"bibtex":"@book{Schneider_Karl_Khalili_Hecker_2021, title={DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning}, author={Schneider, Stefan Balthasar and Karl, Holger and Khalili, Ramin and Hecker, Artur}, year={2021} }","ama":"Schneider SB, Karl H, Khalili R, Hecker A. <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>.; 2021.","mla":"Schneider, Stefan Balthasar, et al. <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>. 2021.","chicago":"Schneider, Stefan Balthasar, Holger Karl, Ramin Khalili, and Artur Hecker. <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>, 2021.","short":"S.B. Schneider, H. Karl, R. Khalili, A. Hecker, DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning, 2021.","ieee":"S. B. Schneider, H. Karl, R. Khalili, and A. Hecker, <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>. 2021.","apa":"Schneider, S. B., Karl, H., Khalili, R., &#38; Hecker, A. (2021). <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>."},"file_date_updated":"2022-10-20T16:41:10Z","oa":"1","department":[{"_id":"75"}],"keyword":["mobility management","coordinated multipoint","CoMP","cell selection","resource management","reinforcement learning","multi agent","MARL","self-learning","self-adaptation","QoE"],"type":"working_paper","date_created":"2022-10-20T16:44:19Z","file":[{"file_id":"33855","content_type":"application/pdf","relation":"main_file","date_updated":"2022-10-20T16:41:10Z","file_name":"preprint.pdf","file_size":2521656,"access_level":"open_access","date_created":"2022-10-20T16:41:10Z","creator":"stschn"}]},{"date_created":"2021-09-27T07:07:58Z","type":"journal_article","keyword":["prognostics","RUL predictions","particle filter","uncertainty consideration","Multi-Model-Particle Filter","model-based approach","rubber-metal-elements","predictive maintenance"],"department":[{"_id":"151"}],"issue":"10","publication":"Machines","abstract":[{"lang":"eng","text":"<jats:p>While increasing digitalization enables multiple advantages for a reliable operation of technical systems, a remaining challenge in the context of condition monitoring is seen in suitable consideration of uncertainties affecting the monitored system. Therefore, a suitable prognostic approach to predict the remaining useful lifetime of complex technical systems is required. To handle different kinds of uncertainties, a novel Multi-Model-Particle Filtering-based prognostic approach is developed and evaluated by the use case of rubber-metal-elements. These elements are maintained preventively due to the strong influence of uncertainties on their behavior. In this paper, two measurement quantities are compared concerning their ability to establish a prediction of the remaining useful lifetime of the monitored elements and the influence of present uncertainties. Based on three performance indices, the results are evaluated. A comparison with predictions of a classical Particle Filter underlines the superiority of the developed Multi-Model-Particle Filter. Finally, the value of the developed method for enabling condition monitoring of technical systems related to uncertainties is given exemplary by a comparison between the preventive and the predictive maintenance strategy for the use case.</jats:p>"}],"main_file_link":[{"url":"https://www.mdpi.com/2075-1702/9/10/210","open_access":"1"}],"article_number":"210","language":[{"iso":"eng"}],"doi":"10.3390/machines9100210","title":"A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions","year":"2021","author":[{"first_name":"Amelie","last_name":"Bender","full_name":"Bender, Amelie","id":"54290"}],"publication_identifier":{"issn":["2075-1702"]},"date_updated":"2022-11-03T11:42:46Z","publication_status":"published","intvolume":"         9","article_type":"original","oa":"1","citation":{"bibtex":"@article{Bender_2021, title={A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions}, volume={9}, DOI={<a href=\"https://doi.org/10.3390/machines9100210\">10.3390/machines9100210</a>}, number={10210}, journal={Machines}, author={Bender, Amelie}, year={2021} }","ama":"Bender A. A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions. <i>Machines</i>. 2021;9(10). doi:<a href=\"https://doi.org/10.3390/machines9100210\">10.3390/machines9100210</a>","short":"A. Bender, Machines 9 (2021).","chicago":"Bender, Amelie. “A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions.” <i>Machines</i> 9, no. 10 (2021). <a href=\"https://doi.org/10.3390/machines9100210\">https://doi.org/10.3390/machines9100210</a>.","ieee":"A. Bender, “A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions,” <i>Machines</i>, vol. 9, no. 10, Art. no. 210, 2021, doi: <a href=\"https://doi.org/10.3390/machines9100210\">10.3390/machines9100210</a>.","mla":"Bender, Amelie. “A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions.” <i>Machines</i>, vol. 9, no. 10, 210, 2021, doi:<a href=\"https://doi.org/10.3390/machines9100210\">10.3390/machines9100210</a>.","apa":"Bender, A. (2021). A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions. <i>Machines</i>, <i>9</i>(10), Article 210. <a href=\"https://doi.org/10.3390/machines9100210\">https://doi.org/10.3390/machines9100210</a>"},"quality_controlled":"1","_id":"25046","user_id":"54290","volume":9,"status":"public"},{"status":"public","year":"2021","title":"Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization","publication_identifier":{"issn":["0305-0548"]},"author":[{"full_name":"Grimme, Christian","first_name":"Christian","last_name":"Grimme"},{"last_name":"Kerschke","first_name":"Pascal","full_name":"Kerschke, Pascal"},{"full_name":"Aspar, Pelin","last_name":"Aspar","first_name":"Pelin"},{"id":"100740","orcid":"0000-0002-9788-8282","first_name":"Heike","last_name":"Trautmann","full_name":"Trautmann, Heike"},{"first_name":"Mike","last_name":"Preuss","full_name":"Preuss, Mike"},{"first_name":"André H.","last_name":"Deutz","full_name":"Deutz, André H."},{"first_name":"Hao","last_name":"Wang","full_name":"Wang, Hao"},{"full_name":"Emmerich, Michael","first_name":"Michael","last_name":"Emmerich"}],"date_updated":"2023-10-16T12:58:42Z","intvolume":"       136","page":"105489","language":[{"iso":"eng"}],"_id":"46318","user_id":"15504","doi":"https://doi.org/10.1016/j.cor.2021.105489","volume":136,"publication":"Computers & Operations Research","citation":{"mla":"Grimme, Christian, et al. “Peeking beyond Peaks: Challenges and Research Potentials of Continuous Multimodal Multi-Objective Optimization.” <i>Computers &#38; Operations Research</i>, vol. 136, 2021, p. 105489, doi:<a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>.","ama":"Grimme C, Kerschke P, Aspar P, et al. Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. <i>Computers &#38; Operations Research</i>. 2021;136:105489. doi:<a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>","bibtex":"@article{Grimme_Kerschke_Aspar_Trautmann_Preuss_Deutz_Wang_Emmerich_2021, title={Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization}, volume={136}, DOI={<a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>}, journal={Computers &#38; Operations Research}, author={Grimme, Christian and Kerschke, Pascal and Aspar, Pelin and Trautmann, Heike and Preuss, Mike and Deutz, André H. and Wang, Hao and Emmerich, Michael}, year={2021}, pages={105489} }","apa":"Grimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A. H., Wang, H., &#38; Emmerich, M. (2021). Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. <i>Computers &#38; Operations Research</i>, <i>136</i>, 105489. <a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>","ieee":"C. Grimme <i>et al.</i>, “Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization,” <i>Computers &#38; Operations Research</i>, vol. 136, p. 105489, 2021, doi: <a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>.","short":"C. Grimme, P. Kerschke, P. Aspar, H. Trautmann, M. Preuss, A.H. Deutz, H. Wang, M. Emmerich, Computers &#38; Operations Research 136 (2021) 105489.","chicago":"Grimme, Christian, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, and Michael Emmerich. “Peeking beyond Peaks: Challenges and Research Potentials of Continuous Multimodal Multi-Objective Optimization.” <i>Computers &#38; Operations Research</i> 136 (2021): 105489. <a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>."},"abstract":[{"text":"Multi-objective (MO) optimization, i.e., the simultaneous optimization of multiple conflicting objectives, is gaining more and more attention in various research areas, such as evolutionary computation, machine learning (e.g., (hyper-)parameter optimization), or logistics (e.g., vehicle routing). Many works in this domain mention the structural problem property of multimodality as a challenge from two classical perspectives: (1) finding all globally optimal solution sets, and (2) avoiding to get trapped in local optima. Interestingly, these streams seem to transfer many traditional concepts of single-objective (SO) optimization into claims, assumptions, or even terminology regarding the MO domain, but mostly neglect the understanding of the structural properties as well as the algorithmic search behavior on a problem’s landscape. However, some recent works counteract this trend, by investigating the fundamentals and characteristics of MO problems using new visualization techniques and gaining surprising insights. Using these visual insights, this work proposes a step towards a unified terminology to capture multimodality and locality in a broader way than it is usually done. This enables us to investigate current research activities in multimodal continuous MO optimization and to highlight new implications and promising research directions for the design of benchmark suites, the discovery of MO landscape features, the development of new MO (or even SO) optimization algorithms, and performance indicators. For all these topics, we provide a review of ideas and methods but also an outlook on future challenges, research potential and perspectives that result from recent developments.","lang":"eng"}],"date_created":"2023-08-04T07:28:34Z","keyword":["Multimodal optimization","Multi-objective continuous optimization","Landscape analysis","Visualization","Benchmarking","Theory","Algorithms"],"type":"journal_article","department":[{"_id":"34"},{"_id":"819"}]},{"doi":"10.1108/JOSM-03-2020-0066","language":[{"iso":"eng"}],"intvolume":"        32","article_type":"original","date_updated":"2024-04-18T12:46:37Z","publication_status":"published","publication_identifier":{"issn":["507-532"]},"author":[{"last_name":"Beverungen","first_name":"Daniel","full_name":"Beverungen, Daniel","id":"59677"},{"id":"21117","last_name":"Kundisch","first_name":"Dennis","full_name":"Kundisch, Dennis"},{"full_name":"Wünderlich, Nancy","last_name":"Wünderlich","first_name":"Nancy","id":"36392"}],"title":"Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers","year":"2021","department":[{"_id":"276"},{"_id":"181"}],"type":"journal_article","keyword":["Smart service","Platform","Interdisciplinary research","Manufacturing company","Smart service provider","Platform economics","Information systems","Multi-sided markets","Business-to-business (B2B) markets"],"date_created":"2020-08-12T12:12:36Z","abstract":[{"lang":"eng","text":"Purpose\r\nThe purpose of this paper is to identify strategic options and challenges that arise when an industrial firm moves from providing smart service toward providing a platform.\r\n\r\nDesign/methodology/approach\r\nThis conceptual study takes on a multidisciplinary research perspective that integrates concepts, theories and insights from service management and marketing, information systems and platform economics.\r\n\r\nFindings\r\nThe paper outlines three platform types – smart data platform, smart product platform and matching platform – as strategic options for firms that wish to evolve from smart service providers to platform providers.\r\n\r\nResearch limitations/implications\r\nInvestigating smart service platforms calls for launching interdisciplinary research initiatives. Promising research avenues are outlined to span boundaries that separate different research disciplines today.\r\n\r\nPractical implications\r\nManaging a successful transition from providing smart service toward providing a platform requires making significant investments in IT, platform-related capabilities and skills, as well as implement new approaches toward relationship management and brand-building.\r\n\r\nOriginality/value\r\nThe findings described in this paper are valuable to researchers in multiple disciplines seeking to develop and to justify theory related to platforms in industrial scenarios."}],"issue":"4","publication":"Journal of Service Management","volume":32,"ddc":["380"],"user_id":"59677","publisher":"Emerald Insight","_id":"17860","page":"507-532","status":"public","project":[{"name":"SFB 901","grant_number":"160364472","_id":"1"},{"name":"SFB 901 - Project Area C","_id":"4"},{"_id":"17","name":"SFB 901 - Subproject C5"}],"quality_controlled":"1","citation":{"bibtex":"@article{Beverungen_Kundisch_Wünderlich_2021, title={Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers}, volume={32}, DOI={<a href=\"https://doi.org/10.1108/JOSM-03-2020-0066\">10.1108/JOSM-03-2020-0066</a>}, number={4}, journal={Journal of Service Management}, publisher={Emerald Insight}, author={Beverungen, Daniel and Kundisch, Dennis and Wünderlich, Nancy}, year={2021}, pages={507–532} }","short":"D. Beverungen, D. Kundisch, N. Wünderlich, Journal of Service Management 32 (2021) 507–532.","ama":"Beverungen D, Kundisch D, Wünderlich N. Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers. <i>Journal of Service Management</i>. 2021;32(4):507-532. doi:<a href=\"https://doi.org/10.1108/JOSM-03-2020-0066\">10.1108/JOSM-03-2020-0066</a>","chicago":"Beverungen, Daniel, Dennis Kundisch, and Nancy Wünderlich. “Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers.” <i>Journal of Service Management</i> 32, no. 4 (2021): 507–32. <a href=\"https://doi.org/10.1108/JOSM-03-2020-0066\">https://doi.org/10.1108/JOSM-03-2020-0066</a>.","ieee":"D. Beverungen, D. Kundisch, and N. Wünderlich, “Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers,” <i>Journal of Service Management</i>, vol. 32, no. 4, pp. 507–532, 2021, doi: <a href=\"https://doi.org/10.1108/JOSM-03-2020-0066\">10.1108/JOSM-03-2020-0066</a>.","mla":"Beverungen, Daniel, et al. “Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers.” <i>Journal of Service Management</i>, vol. 32, no. 4, Emerald Insight, 2021, pp. 507–32, doi:<a href=\"https://doi.org/10.1108/JOSM-03-2020-0066\">10.1108/JOSM-03-2020-0066</a>.","apa":"Beverungen, D., Kundisch, D., &#38; Wünderlich, N. (2021). Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers. <i>Journal of Service Management</i>, <i>32</i>(4), 507–532. <a href=\"https://doi.org/10.1108/JOSM-03-2020-0066\">https://doi.org/10.1108/JOSM-03-2020-0066</a>"}},{"language":[{"iso":"eng"}],"main_file_link":[{"url":"https://papers.phmsociety.org/index.php/phme/article/view/2843","open_access":"1"}],"doi":"https://doi.org/10.36001/phme.2021.v6i1.2843 ","author":[{"full_name":"Bender, Amelie","last_name":"Bender","first_name":"Amelie","id":"54290"},{"full_name":"Sextro, Walter","first_name":"Walter","last_name":"Sextro","id":"21220"}],"publication_identifier":{"unknown":["978-1-936263-34-9"]},"year":"2021","title":"Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties","intvolume":"         6","publication_status":"published","date_updated":"2023-09-22T07:19:48Z","date_created":"2021-07-14T06:29:08Z","department":[{"_id":"151"}],"keyword":["Hybrid prediction method","Multi-model particle filtering","Uncertainty quantification","RUL estimation"],"type":"conference","issue":"1","publication":"Proceedings of the European Conference of the PHM Society 2021","abstract":[{"lang":"eng","text":"\r\nPredictive Maintenance as a desirable maintenance strategy in industrial applications relies on suitable condition monitoring solutions to reduce costs and risks of the monitored technical systems. In general, those solutions utilize model-based or data-driven methods to diagnose the current state or predict future states of monitored technical systems. However, both methods have their advantages and drawbacks. Combining both methods can improve uncertainty consideration and accuracy. Different combination approaches of those hybrid methods exist to exploit synergy effects. The choice of an appropriate approach depends on different requirements and the goal behind the selection of a hybrid approach.\r\n\r\n \r\n\r\nIn this work, the hybrid approach for estimating remaining useful lifetime takes potential uncertainties into account. Therefore, a data-driven estimation of new measurements is integrated within a model-based method. To consider uncertainties within the system, a differentiation between different system behavior is realized throughout diverse states of degradation.\r\n\r\nThe developed hybrid prediction approach bases on a particle filtering method combined with a machine learning method, to estimate the remaining useful lifetime of technical systems. Particle filtering as a Monte Carlo simulation technique is suitable to map and propagate uncertainties. Moreover, it is a state-of-the-art model-based method for predicting remaining useful lifetime of technical systems. To integrate uncertainties a multi-model particle filtering approach is employed. In general, resampling as a part of the particle filtering approach has the potential to lead to an accurate prediction. However, in the case where no future measurements are available, it may increase the uncertainty of the prediction. By estimating new measurements, those uncertainties are reduced within the data-driven part of the approach. Hence, both parts of the hybrid approach strive to account for and reduce uncertainties.\r\n\r\n \r\n\r\nRubber-metal-elements are employed as a use-case to evaluate the developed approach. Rubber-metal-elements, which are used to isolate vibrations in various systems, such as railways, trucks and wind turbines, show various uncertainties in their behavior and their degradation. Those uncertainties are caused by diverse inner and outer factors, such as manufacturing influences and operating conditions. By expert knowledge the influences are described, analyzed and if possible reduced. However, the remaining uncertainties are considered within the hybrid prediction method. Relative temperature is the selected measurand to describe the element’s degradation. In lifetime tests, it is measured as the difference between the element’s temperature and the ambient temperature. Thereby, the influence of the ambient temperature on the element’s temperature is taken into account. Those elements show three typical states of degradation that are identified within the temperature measurements. Depending on the particular state of degradation a new measurement is estimated within the hybrid approach to reduce potential uncertainties.\r\n\r\nFinally, the performance of the developed hybrid method is compared to a model-based method for estimating the remaining useful lifetime of the same elements. Suitable performance indices are implemented to underline the differences between the results."}],"_id":"22724","volume":6,"editor":[{"full_name":"Do, Phuc ","last_name":"Do","first_name":"Phuc "},{"last_name":"King","first_name":"Steve","full_name":"King, Steve"},{"full_name":"Fink,  Olga","last_name":"Fink","first_name":" Olga"}],"user_id":"54290","conference":{"end_date":"2021-07-02","start_date":"2021-06-28","name":"6th European Conference of Prognostics and Health Management"},"status":"public","oa":"1","citation":{"apa":"Bender, A., &#38; Sextro, W. (2021). Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties. In P. Do, S. King, &#38;  Olga Fink (Eds.), <i>Proceedings of the European Conference of the PHM Society 2021</i> (Vol. 6, Issue 1). <a href=\"https://doi.org/10.36001/phme.2021.v6i1.2843 \">https://doi.org/10.36001/phme.2021.v6i1.2843 </a>","ieee":"A. Bender and W. Sextro, “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties,” in <i>Proceedings of the European Conference of the PHM Society 2021</i>, 2021, vol. 6, no. 1, doi: <a href=\"https://doi.org/10.36001/phme.2021.v6i1.2843 \">https://doi.org/10.36001/phme.2021.v6i1.2843 </a>.","short":"A. Bender, W. Sextro, in: P. Do, S. King,  Olga Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021, 2021.","chicago":"Bender, Amelie, and Walter Sextro. “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties.” In <i>Proceedings of the European Conference of the PHM Society 2021</i>, edited by Phuc  Do, Steve King, and  Olga Fink, Vol. 6, 2021. <a href=\"https://doi.org/10.36001/phme.2021.v6i1.2843 \">https://doi.org/10.36001/phme.2021.v6i1.2843 </a>.","mla":"Bender, Amelie, and Walter Sextro. “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties.” <i>Proceedings of the European Conference of the PHM Society 2021</i>, edited by Phuc  Do et al., vol. 6, no. 1, 2021, doi:<a href=\"https://doi.org/10.36001/phme.2021.v6i1.2843 \">https://doi.org/10.36001/phme.2021.v6i1.2843 </a>.","ama":"Bender A, Sextro W. Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties. In: Do P, King S, Fink  Olga, eds. <i>Proceedings of the European Conference of the PHM Society 2021</i>. Vol 6. ; 2021. doi:<a href=\"https://doi.org/10.36001/phme.2021.v6i1.2843 \">https://doi.org/10.36001/phme.2021.v6i1.2843 </a>","bibtex":"@inproceedings{Bender_Sextro_2021, title={Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties}, volume={6}, DOI={<a href=\"https://doi.org/10.36001/phme.2021.v6i1.2843 \">https://doi.org/10.36001/phme.2021.v6i1.2843 </a>}, number={1}, booktitle={Proceedings of the European Conference of the PHM Society 2021}, author={Bender, Amelie and Sextro, Walter}, editor={Do, Phuc  and King, Steve and Fink,  Olga}, year={2021} }"},"quality_controlled":"1"},{"publication":"Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures","abstract":[{"text":" We consider a natural extension to the metric uncapacitated Facility Location Problem (FLP) in which requests ask for different commodities out of a finite set \\( S \\) of commodities.\r\n  Ravi and Sinha (SODA 2004) introduced the model as the \\emph{Multi-Commodity Facility Location Problem} (MFLP) and considered it an offline optimization problem.\r\n  The model itself is similar to the FLP: i.e., requests are located at points of a finite metric space and the task of an algorithm is to construct facilities and assign requests to facilities while minimizing the construction cost and the sum over all assignment distances.\r\n  In addition, requests and facilities are heterogeneous; they request or offer multiple commodities out of $S$.\r\n  A request has to be connected to a set of facilities jointly offering the commodities demanded by it.\r\n  In comparison to the FLP, an algorithm has to decide not only if and where to place facilities, but also which commodities to offer at each.\r\n\r\n  To the best of our knowledge we are the first to study the problem in its online variant in which requests, their positions and their commodities are not known beforehand but revealed over time.\r\n  We present results regarding the competitive ratio.\r\n  On the one hand, we show that heterogeneity influences the competitive ratio by developing a lower bound on the competitive ratio for any randomized online algorithm of \\( \\Omega (  \\sqrt{|S|} + \\frac{\\log n}{\\log \\log n}  ) \\) that already holds for simple line metrics.\r\n  Here, \\( n \\) is the number of requests.\r\n  On the other side, we establish a deterministic \\( \\mathcal{O}(\\sqrt{|S|} \\cdot \\log n) \\)-competitive algorithm and a randomized \\( \\mathcal{O}(\\sqrt{|S|} \\cdot \\frac{\\log n}{\\log \\log n} ) \\)-competitive algorithm.\r\n  Further, we show that when considering a more special class of cost functions for the construction cost of a facility, the competitive ratio decreases given by our deterministic algorithm depending on the function.","lang":"eng"}],"date_created":"2020-07-14T07:53:20Z","file":[{"relation":"main_file","date_updated":"2020-07-14T07:56:52Z","file_name":"3350755.3400281.pdf","file_size":1271416,"access_level":"closed","file_id":"17373","success":1,"content_type":"application/pdf","creator":"tillk","date_created":"2020-07-14T07:56:52Z"}],"department":[{"_id":"63"}],"type":"conference","keyword":["Online Multi-Commodity Facility Location","Competitive Ratio","Online Optimization","Facility Location Problem"],"publication_identifier":{"isbn":["9781450369350"]},"author":[{"full_name":"Castenow, Jannik","first_name":"Jannik","last_name":"Castenow","id":"38705"},{"id":"22704","first_name":"Björn","last_name":"Feldkord","full_name":"Feldkord, Björn"},{"last_name":"Knollmann","first_name":"Till","orcid":"0000-0003-2014-4696","full_name":"Knollmann, Till","id":"39241"},{"last_name":"Malatyali","first_name":"Manuel","full_name":"Malatyali, Manuel"},{"id":"15523","full_name":"Meyer auf der Heide, Friedhelm","last_name":"Meyer auf der Heide","first_name":"Friedhelm"}],"title":"The Online Multi-Commodity Facility Location Problem","year":"2020","publication_status":"published","date_updated":"2022-01-06T06:53:10Z","language":[{"iso":"eng"}],"doi":"10.1145/3350755.3400281","citation":{"bibtex":"@inproceedings{Castenow_Feldkord_Knollmann_Malatyali_Meyer auf der Heide_2020, title={The Online Multi-Commodity Facility Location Problem}, DOI={<a href=\"https://doi.org/10.1145/3350755.3400281\">10.1145/3350755.3400281</a>}, booktitle={Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures}, author={Castenow, Jannik and Feldkord, Björn and Knollmann, Till and Malatyali, Manuel and Meyer auf der Heide, Friedhelm}, year={2020} }","ama":"Castenow J, Feldkord B, Knollmann T, Malatyali M, Meyer auf der Heide F. The Online Multi-Commodity Facility Location Problem. In: <i>Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures</i>. ; 2020. doi:<a href=\"https://doi.org/10.1145/3350755.3400281\">10.1145/3350755.3400281</a>","mla":"Castenow, Jannik, et al. “The Online Multi-Commodity Facility Location Problem.” <i>Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures</i>, 2020, doi:<a href=\"https://doi.org/10.1145/3350755.3400281\">10.1145/3350755.3400281</a>.","short":"J. Castenow, B. Feldkord, T. Knollmann, M. Malatyali, F. Meyer auf der Heide, in: Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures, 2020.","chicago":"Castenow, Jannik, Björn Feldkord, Till Knollmann, Manuel Malatyali, and Friedhelm Meyer auf der Heide. “The Online Multi-Commodity Facility Location Problem.” In <i>Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures</i>, 2020. <a href=\"https://doi.org/10.1145/3350755.3400281\">https://doi.org/10.1145/3350755.3400281</a>.","ieee":"J. Castenow, B. Feldkord, T. Knollmann, M. Malatyali, and F. Meyer auf der Heide, “The Online Multi-Commodity Facility Location Problem,” in <i>Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures</i>, 2020.","apa":"Castenow, J., Feldkord, B., Knollmann, T., Malatyali, M., &#38; Meyer auf der Heide, F. (2020). The Online Multi-Commodity Facility Location Problem. In <i>Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures</i>. <a href=\"https://doi.org/10.1145/3350755.3400281\">https://doi.org/10.1145/3350755.3400281</a>"},"file_date_updated":"2020-07-14T07:56:52Z","project":[{"name":"SFB 901","_id":"1"},{"_id":"2","name":"SFB 901 - Project Area A"},{"_id":"5","name":"SFB 901 - Subproject A1"}],"external_id":{"arxiv":["2005.08391"]},"status":"public","has_accepted_license":"1","_id":"17370","user_id":"39241","ddc":["000"]},{"project":[{"grant_number":"762057","_id":"23","name":"5G Programmable Infrastructure Converging disaggregated neTwork and compUte Resources"}],"abstract":[{"text":"Despite recent progress in orchestration of Virtual Network Functions (VNFs) and in multi-technology SDN connectivity, the automated provisioning of end-to-end network services composed of virtual functions deployed across distributed compute locations remains an open challenge. This problem is especially relevant to support the deployment of future 5G networks, comprising virtual access and core network functions connected through a potentially multi-domain transport network.\r\nIn this paper, we present and demonstrate the 5GOS, a lightweight end-to-end orchestration framework that enables the\r\nautomated provisioning of virtual radio access network services. Using an experimental multi-domain testbed we demonstrate that the 5GOS can provision multi-domain virtual Wi-Fi and LTE services in less than three minutes.","lang":"eng"}],"citation":{"ieee":"D. Camps-Mur <i>et al.</i>, “5GOS: Demonstrating multi-domain orchestration of end-to-end virtual RAN services,” in <i>the 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020)</i>, Ghent, Belgium.","apa":"Camps-Mur, D.,  Canellas, F., Machwe, A., Paracuellos, J., Choumas, K., Giatsios, D., … Razzaghi Kouchaksaraei, H. (n.d.). 5GOS: Demonstrating multi-domain orchestration of end-to-end virtual RAN services. In <i>the 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020)</i>. Ghent, Belgium.","short":"D. Camps-Mur, F.  Canellas, A. Machwe, J. Paracuellos, K. Choumas, D. Giatsios, T. Korakis, H. Razzaghi Kouchaksaraei, in: The 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020), n.d.","chicago":"Camps-Mur, Daniel, Ferran  Canellas, Azahar Machwe, Jorge Paracuellos, Kostas Choumas, Dimitris Giatsios, Thanasis Korakis, and Hadi Razzaghi Kouchaksaraei. “5GOS: Demonstrating Multi-Domain Orchestration of End-to-End Virtual RAN Services.” In <i>The 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020)</i>, n.d.","mla":"Camps-Mur, Daniel, et al. “5GOS: Demonstrating Multi-Domain Orchestration of End-to-End Virtual RAN Services.” <i>The 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020)</i>.","bibtex":"@inproceedings{Camps-Mur_ Canellas_Machwe_Paracuellos_Choumas_Giatsios_Korakis_Razzaghi Kouchaksaraei, title={5GOS: Demonstrating multi-domain orchestration of end-to-end virtual RAN services}, booktitle={the 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020)}, author={Camps-Mur, Daniel and  Canellas, Ferran and Machwe, Azahar and Paracuellos, Jorge and Choumas, Kostas and Giatsios, Dimitris and Korakis, Thanasis and Razzaghi Kouchaksaraei, Hadi} }","ama":"Camps-Mur D,  Canellas F, Machwe A, et al. 5GOS: Demonstrating multi-domain orchestration of end-to-end virtual RAN services. In: <i>The 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020)</i>."},"publication":"the 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020)","keyword":["Orchestration","multi-domain","cellular network virtualization","SDN","5G"],"type":"conference","date_created":"2020-03-03T11:49:41Z","date_updated":"2022-01-06T06:52:45Z","publication_status":"accepted","conference":{"end_date":"2020-07-3","location":"Ghent, Belgium","start_date":"2020-06-29","name":"IEEE Conference on Network Softwarization (NetSoft)"},"author":[{"first_name":"Daniel","last_name":"Camps-Mur","full_name":"Camps-Mur, Daniel"},{"full_name":" Canellas, Ferran","first_name":"Ferran","last_name":" Canellas"},{"last_name":"Machwe","first_name":"Azahar","full_name":"Machwe, Azahar"},{"full_name":"Paracuellos, Jorge","last_name":"Paracuellos","first_name":"Jorge"},{"last_name":"Choumas","first_name":"Kostas","full_name":"Choumas, Kostas"},{"first_name":"Dimitris","last_name":"Giatsios","full_name":"Giatsios, Dimitris"},{"full_name":"Korakis, Thanasis","first_name":"Thanasis","last_name":"Korakis"},{"id":"60845","full_name":"Razzaghi Kouchaksaraei, Hadi","first_name":"Hadi","last_name":"Razzaghi Kouchaksaraei"}],"title":"5GOS: Demonstrating multi-domain orchestration of end-to-end virtual RAN services","year":"2020","status":"public","user_id":"60845","language":[{"iso":"eng"}],"_id":"16218"},{"user_id":"102979","_id":"48845","publisher":"Association for Computing Machinery","page":"166–174","status":"public","place":"New York, NY, USA","citation":{"mla":"Bossek, Jakob, et al. “Dynamic Bi-Objective Routing of Multiple Vehicles.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2020, pp. 166–174, doi:<a href=\"https://doi.org/10.1145/3377930.3390146\">10.1145/3377930.3390146</a>.","ama":"Bossek J, Grimme C, Trautmann H. Dynamic Bi-Objective Routing of Multiple Vehicles. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. GECCO ’20. Association for Computing Machinery; 2020:166–174. doi:<a href=\"https://doi.org/10.1145/3377930.3390146\">10.1145/3377930.3390146</a>","bibtex":"@inproceedings{Bossek_Grimme_Trautmann_2020, place={New York, NY, USA}, series={GECCO ’20}, title={Dynamic Bi-Objective Routing of Multiple Vehicles}, DOI={<a href=\"https://doi.org/10.1145/3377930.3390146\">10.1145/3377930.3390146</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Bossek, Jakob and Grimme, Christian and Trautmann, Heike}, year={2020}, pages={166–174}, collection={GECCO ’20} }","apa":"Bossek, J., Grimme, C., &#38; Trautmann, H. (2020). Dynamic Bi-Objective Routing of Multiple Vehicles. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 166–174. <a href=\"https://doi.org/10.1145/3377930.3390146\">https://doi.org/10.1145/3377930.3390146</a>","ieee":"J. Bossek, C. Grimme, and H. Trautmann, “Dynamic Bi-Objective Routing of Multiple Vehicles,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2020, pp. 166–174, doi: <a href=\"https://doi.org/10.1145/3377930.3390146\">10.1145/3377930.3390146</a>.","chicago":"Bossek, Jakob, Christian Grimme, and Heike Trautmann. “Dynamic Bi-Objective Routing of Multiple Vehicles.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 166–174. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. <a href=\"https://doi.org/10.1145/3377930.3390146\">https://doi.org/10.1145/3377930.3390146</a>.","short":"J. Bossek, C. Grimme, H. Trautmann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 166–174."},"doi":"10.1145/3377930.3390146","series_title":"GECCO ’20","language":[{"iso":"eng"}],"publication_status":"published","date_updated":"2023-12-13T10:43:24Z","author":[{"full_name":"Bossek, Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","first_name":"Jakob","id":"102979"},{"last_name":"Grimme","first_name":"Christian","full_name":"Grimme, Christian"},{"full_name":"Trautmann, Heike","last_name":"Trautmann","first_name":"Heike"}],"publication_identifier":{"isbn":["978-1-4503-7128-5"]},"title":"Dynamic Bi-Objective Routing of Multiple Vehicles","year":"2020","department":[{"_id":"819"}],"keyword":["decision making","dynamic optimization","evolutionary algorithms","multi-objective optimization","vehicle routing"],"type":"conference","date_created":"2023-11-14T15:58:52Z","extern":"1","abstract":[{"text":"In practice, e.g. in delivery and service scenarios, Vehicle-Routing-Problems (VRPs) often imply repeated decision making on dynamic customer requests. As in classical VRPs, tours have to be planned short while the number of serviced customers has to be maximized at the same time resulting in a multi-objective problem. Beyond that, however, dynamic requests lead to the need for re-planning of not yet realized tour parts, while already realized tour parts are irreversible. In this paper we study this type of bi-objective dynamic VRP including sequential decision making and concurrent realization of decisions. We adopt a recently proposed Dynamic Evolutionary Multi-Objective Algorithm (DEMOA) for a related VRP problem and extend it to the more realistic (here considered) scenario of multiple vehicles. We empirically show that our DEMOA is competitive with a multi-vehicle offline and clairvoyant variant of the proposed DEMOA as well as with the dynamic single-vehicle approach proposed earlier.","lang":"eng"}],"publication":"Proceedings of the Genetic and Evolutionary Computation Conference"},{"date_updated":"2023-12-13T10:52:17Z","intvolume":"        88","title":"A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms","year":"2020","status":"public","publication_identifier":{"issn":["1568-4946"]},"author":[{"id":"102979","full_name":"Bossek, Jakob","orcid":"0000-0002-4121-4668","last_name":"Bossek","first_name":"Jakob"},{"last_name":"Kerschke","first_name":"Pascal","full_name":"Kerschke, Pascal"},{"last_name":"Trautmann","first_name":"Heike","full_name":"Trautmann, Heike"}],"user_id":"102979","doi":"10.1016/j.asoc.2019.105901","volume":88,"language":[{"iso":"eng"}],"_id":"48848","abstract":[{"lang":"eng","text":"We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs \\textendash both to be minimized \\textendash is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers. \\textbullet The multi-objective perspective is naturally generalizable to multiple objectives. \\textbullet Proof of relationship between HV and the PAR in the considered bi-objective space. \\textbullet New insights into complementary behavior of stochastic optimization algorithms."}],"issue":"C","publication":"Applied Soft Computing","citation":{"chicago":"Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” <i>Applied Soft Computing</i> 88, no. C (2020). <a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>.","short":"J. Bossek, P. Kerschke, H. Trautmann, Applied Soft Computing 88 (2020).","ama":"Bossek J, Kerschke P, Trautmann H. A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms. <i>Applied Soft Computing</i>. 2020;88(C). doi:<a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">10.1016/j.asoc.2019.105901</a>","bibtex":"@article{Bossek_Kerschke_Trautmann_2020, title={A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms}, volume={88}, DOI={<a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">10.1016/j.asoc.2019.105901</a>}, number={C}, journal={Applied Soft Computing}, author={Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}, year={2020} }","apa":"Bossek, J., Kerschke, P., &#38; Trautmann, H. (2020). A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms. <i>Applied Soft Computing</i>, <i>88</i>(C). <a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>","mla":"Bossek, Jakob, et al. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” <i>Applied Soft Computing</i>, vol. 88, no. C, 2020, doi:<a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">10.1016/j.asoc.2019.105901</a>.","ieee":"J. Bossek, P. Kerschke, and H. Trautmann, “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms,” <i>Applied Soft Computing</i>, vol. 88, no. C, 2020, doi: <a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">10.1016/j.asoc.2019.105901</a>."},"keyword":["Algorithm selection","Combinatorial optimization","Multi-objective optimization","Performance measurement","Traveling Salesperson Problem"],"type":"journal_article","department":[{"_id":"819"}],"date_created":"2023-11-14T15:58:53Z"},{"keyword":["Algorithm selection","Multi-objective optimization","Performance measurement","Combinatorial optimization","Traveling Salesperson Problem"],"type":"journal_article","department":[{"_id":"34"},{"_id":"819"}],"date_created":"2023-08-04T07:42:26Z","abstract":[{"lang":"eng","text":"We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs – both to be minimized – is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers."}],"publication":"Applied Soft Computing","citation":{"mla":"Bossek, Jakob, et al. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” <i>Applied Soft Computing</i>, vol. 88, 2020, p. 105901, doi:<a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>.","bibtex":"@article{Bossek_Kerschke_Trautmann_2020, title={A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms}, volume={88}, DOI={<a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>}, journal={Applied Soft Computing}, author={Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}, year={2020}, pages={105901} }","ama":"Bossek J, Kerschke P, Trautmann H. A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. <i>Applied Soft Computing</i>. 2020;88:105901. doi:<a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>","ieee":"J. Bossek, P. Kerschke, and H. Trautmann, “A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms,” <i>Applied Soft Computing</i>, vol. 88, p. 105901, 2020, doi: <a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>.","apa":"Bossek, J., Kerschke, P., &#38; Trautmann, H. (2020). A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. <i>Applied Soft Computing</i>, <i>88</i>, 105901. <a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>","chicago":"Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” <i>Applied Soft Computing</i> 88 (2020): 105901. <a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>.","short":"J. Bossek, P. Kerschke, H. Trautmann, Applied Soft Computing 88 (2020) 105901."},"user_id":"15504","doi":"https://doi.org/10.1016/j.asoc.2019.105901","volume":88,"page":"105901","language":[{"iso":"eng"}],"_id":"46334","date_updated":"2024-06-10T12:00:46Z","intvolume":"        88","year":"2020","status":"public","title":"A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms","author":[{"last_name":"Bossek","orcid":"0000-0002-4121-4668","first_name":"Jakob","full_name":"Bossek, Jakob","id":"102979"},{"full_name":"Kerschke, Pascal","last_name":"Kerschke","first_name":"Pascal"},{"id":"100740","orcid":"0000-0002-9788-8282","last_name":"Trautmann","first_name":"Heike","full_name":"Trautmann, Heike"}],"publication_identifier":{"issn":["1568-4946"]}},{"status":"public","user_id":"15278","_id":"21632","quality_controlled":"1","project":[{"_id":"52","name":"Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"citation":{"mla":"Meyer, Marius, et al. “Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of Selected Benchmarks of the HPCChallenge Benchmark Suite.” <i>2020 IEEE/ACM International Workshop on Heterogeneous High-Performance Reconfigurable Computing (H2RC)</i>, 2020, doi:<a href=\"https://doi.org/10.1109/h2rc51942.2020.00007\">10.1109/h2rc51942.2020.00007</a>.","apa":"Meyer, M., Kenter, T., &#38; Plessl, C. (2020). Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of Selected Benchmarks of the HPCChallenge Benchmark Suite. <i>2020 IEEE/ACM International Workshop on Heterogeneous High-Performance Reconfigurable Computing (H2RC)</i>. <a href=\"https://doi.org/10.1109/h2rc51942.2020.00007\">https://doi.org/10.1109/h2rc51942.2020.00007</a>","ieee":"M. Meyer, T. Kenter, and C. Plessl, “Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of Selected Benchmarks of the HPCChallenge Benchmark Suite,” 2020, doi: <a href=\"https://doi.org/10.1109/h2rc51942.2020.00007\">10.1109/h2rc51942.2020.00007</a>.","chicago":"Meyer, Marius, Tobias Kenter, and Christian Plessl. “Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of Selected Benchmarks of the HPCChallenge Benchmark Suite.” In <i>2020 IEEE/ACM International Workshop on Heterogeneous High-Performance Reconfigurable Computing (H2RC)</i>, 2020. <a href=\"https://doi.org/10.1109/h2rc51942.2020.00007\">https://doi.org/10.1109/h2rc51942.2020.00007</a>.","ama":"Meyer M, Kenter T, Plessl C. Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of Selected Benchmarks of the HPCChallenge Benchmark Suite. In: <i>2020 IEEE/ACM International Workshop on Heterogeneous High-Performance Reconfigurable Computing (H2RC)</i>. ; 2020. doi:<a href=\"https://doi.org/10.1109/h2rc51942.2020.00007\">10.1109/h2rc51942.2020.00007</a>","short":"M. Meyer, T. Kenter, C. Plessl, in: 2020 IEEE/ACM International Workshop on Heterogeneous High-Performance Reconfigurable Computing (H2RC), 2020.","bibtex":"@inproceedings{Meyer_Kenter_Plessl_2020, title={Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of Selected Benchmarks of the HPCChallenge Benchmark Suite}, DOI={<a href=\"https://doi.org/10.1109/h2rc51942.2020.00007\">10.1109/h2rc51942.2020.00007</a>}, booktitle={2020 IEEE/ACM International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC)}, author={Meyer, Marius and Kenter, Tobias and Plessl, Christian}, year={2020} }"},"publication_status":"published","date_updated":"2023-09-26T11:42:53Z","title":"Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of Selected Benchmarks of the HPCChallenge Benchmark Suite","year":"2020","publication_identifier":{"isbn":["9781665415927"]},"author":[{"id":"40778","full_name":"Meyer, Marius","first_name":"Marius","last_name":"Meyer"},{"full_name":"Kenter, Tobias","last_name":"Kenter","first_name":"Tobias","id":"3145"},{"id":"16153","first_name":"Christian","orcid":"0000-0001-5728-9982","last_name":"Plessl","full_name":"Plessl, Christian"}],"doi":"10.1109/h2rc51942.2020.00007","main_file_link":[{"url":"https://ieeexplore.ieee.org/document/9306963"}],"language":[{"iso":"eng"}],"related_material":{"link":[{"description":"Official repository of the benchmark suite on GitHub","url":"https://github.com/pc2/HPCC_FPGA","relation":"supplementary_material"}]},"abstract":[{"lang":"eng","text":"FPGAs have found increasing adoption in data center applications since a new generation of high-level tools have become available which noticeably reduce development time for FPGA accelerators and still provide high-quality results. There is, however, no high-level benchmark suite available, which specifically enables a comparison of FPGA architectures, programming tools, and libraries for HPC applications. To fill this gap, we have developed an OpenCL-based open-source implementation of the HPCC benchmark suite for Xilinx and Intel FPGAs. This benchmark can serve to analyze the current capabilities of FPGA devices, cards, and development tool flows, track progress over time, and point out specific difficulties for FPGA acceleration in the HPC domain. Additionally, the benchmark documents proven performance optimization patterns. We will continue optimizing and porting the benchmark for new generations of FPGAs and design tools and encourage active participation to create a valuable tool for the community. To fill this gap, we have developed an OpenCL-based open-source implementation of the HPCC benchmark suite for Xilinx and Intel FPGAs. This benchmark can serve to analyze the current capabilities of FPGA devices, cards, and development tool flows, track progress over time, and point out specific difficulties for FPGA acceleration in the HPC domain. Additionally, the benchmark documents proven performance optimization patterns. We will continue optimizing and porting the benchmark for new generations of FPGAs and design tools and encourage active participation to create a valuable tool for the community."}],"publication":"2020 IEEE/ACM International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC)","type":"conference","keyword":["FPGA","OpenCL","High Level Synthesis","HPC benchmarking"],"department":[{"_id":"27"},{"_id":"518"}],"date_created":"2021-04-16T10:17:22Z"},{"language":[{"iso":"eng"}],"doi":"10.1007/s11740-020-00973-w","author":[{"full_name":"Uhe, Benedikt","last_name":"Uhe","first_name":"Benedikt","id":"38131"},{"last_name":"Kuball","first_name":"Clara-Maria","full_name":"Kuball, Clara-Maria"},{"full_name":"Merklein, Marion","last_name":"Merklein","first_name":"Marion"},{"last_name":"Meschut","first_name":"Gerson","orcid":"0000-0002-2763-1246","full_name":"Meschut, Gerson","id":"32056"}],"title":"Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints","year":"2020","intvolume":"        14","article_type":"original","date_updated":"2026-02-27T10:41:55Z","publication_status":"published","date_created":"2020-10-12T08:14:13Z","department":[{"_id":"157"}],"keyword":["Self-piercing riveting","Joining technology","Rivet geometry","Multi-material design","High-strength steel","Aluminium"],"type":"journal_article","publication":"Production Engineering","abstract":[{"text":"As a result of lightweight design, increased use is being made of high-strength steel and aluminium in car bodies. Self-piercing riveting is an established technique for joining these materials. The dissimilar properties of the two materials have led to a number of different rivet geometries in the past. Each rivet geometry fulfils the requirements of the materials within a limited range. In the present investigation, an improved rivet geometry is developed, which permits the reliable joining of two material combinations that could only be joined by two different rivet geometries up until now. Material combination 1 consists of high-strength steel on both sides, while material combination 2 comprises aluminium on the punch side and high-strength steel on the die side. The material flow and the stress and strain conditions prevailing during the joining process are analysed by means of numerical simulation. The rivet geometry is then improved step-by-step on the basis of this analysis. Finally, the improved rivet geometry is manufactured and the findings of the investigation are verified in experimental joining tests.","lang":"eng"}],"_id":"19973","page":"417-423","volume":14,"user_id":"53912","status":"public","citation":{"apa":"Uhe, B., Kuball, C.-M., Merklein, M., &#38; Meschut, G. (2020). Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints. <i>Production Engineering</i>, <i>14</i>, 417–423. <a href=\"https://doi.org/10.1007/s11740-020-00973-w\">https://doi.org/10.1007/s11740-020-00973-w</a>","ieee":"B. Uhe, C.-M. Kuball, M. Merklein, and G. Meschut, “Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints,” <i>Production Engineering</i>, vol. 14, pp. 417–423, 2020, doi: <a href=\"https://doi.org/10.1007/s11740-020-00973-w\">10.1007/s11740-020-00973-w</a>.","short":"B. Uhe, C.-M. Kuball, M. Merklein, G. Meschut, Production Engineering 14 (2020) 417–423.","chicago":"Uhe, Benedikt, Clara-Maria Kuball, Marion Merklein, and Gerson Meschut. “Improvement of a Rivet Geometry for the Self-Piercing Riveting of High-Strength Steel and Multi-Material Joints.” <i>Production Engineering</i> 14 (2020): 417–23. <a href=\"https://doi.org/10.1007/s11740-020-00973-w\">https://doi.org/10.1007/s11740-020-00973-w</a>.","mla":"Uhe, Benedikt, et al. “Improvement of a Rivet Geometry for the Self-Piercing Riveting of High-Strength Steel and Multi-Material Joints.” <i>Production Engineering</i>, vol. 14, 2020, pp. 417–23, doi:<a href=\"https://doi.org/10.1007/s11740-020-00973-w\">10.1007/s11740-020-00973-w</a>.","ama":"Uhe B, Kuball C-M, Merklein M, Meschut G. Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints. <i>Production Engineering</i>. 2020;14:417-423. doi:<a href=\"https://doi.org/10.1007/s11740-020-00973-w\">10.1007/s11740-020-00973-w</a>","bibtex":"@article{Uhe_Kuball_Merklein_Meschut_2020, title={Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints}, volume={14}, DOI={<a href=\"https://doi.org/10.1007/s11740-020-00973-w\">10.1007/s11740-020-00973-w</a>}, journal={Production Engineering}, author={Uhe, Benedikt and Kuball, Clara-Maria and Merklein, Marion and Meschut, Gerson}, year={2020}, pages={417–423} }"},"quality_controlled":"1"},{"publication":"2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)","extern":"1","abstract":[{"lang":"eng","text":"Resolving distributed attacks benefits from collaboration between networks. We present three approaches for the same multi-domain defensive action that can be applied in such an alliance: 1) Counteract Everywhere, 2) Minimize Countermeasures, and 3) Minimize Propagation. First, we provide a formula to compute efficiency of a defense; then we use this formula to compute the efficiency of the approaches under various circumstances. Finally, we discuss how task execution order and timing influence defense efficiency. Our results show that the Minimize Propagation approach is the most efficient method when defending against the chosen attack."}],"date_created":"2020-08-06T15:23:23Z","department":[{"_id":"63"},{"_id":"541"}],"type":"conference","keyword":["computer network security","multinetwork environments","multidomain defensive action","task execution order","timing influence defense efficiency","distributed attacks","collaborative security defence approach","minimize propagation approach","minimize countermeasure approach","counteract everywhere approach","Conferences","Cloud computing","Computer crime","Edge computing","Security","Defense Approaches","Multi-Domain Defense","Collaborative Defense","Defense Algorithms","Computer Networks"],"author":[{"last_name":"Koning","first_name":"Ralph","full_name":"Koning, Ralph"},{"full_name":"Polevoy, Gleb","first_name":"Gleb","last_name":"Polevoy","id":"83983"},{"full_name":"Meijer, Lydia","first_name":"Lydia","last_name":"Meijer"},{"last_name":"de Laat","first_name":"Cees","full_name":"de Laat, Cees"},{"full_name":"Grosso, Paola","first_name":"Paola","last_name":"Grosso"}],"publication_identifier":{"issn":["null"]},"title":"Approaches for Collaborative Security Defences in Multi Network Environments","year":"2019","date_updated":"2022-01-06T06:53:16Z","series_title":"2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://ieeexplore.ieee.org/abstract/document/8854057/authors#authors"}],"doi":"10.1109/CSCloud/EdgeCom.2019.000-9","citation":{"chicago":"Koning, Ralph, Gleb Polevoy, Lydia Meijer, Cees de Laat, and Paola Grosso. “Approaches for Collaborative Security Defences in Multi Network Environments.” In <i>2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)</i>, 113–23. 2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom), 2019. <a href=\"https://doi.org/10.1109/CSCloud/EdgeCom.2019.000-9\">https://doi.org/10.1109/CSCloud/EdgeCom.2019.000-9</a>.","short":"R. Koning, G. Polevoy, L. Meijer, C. de Laat, P. Grosso, in: 2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom), 2019, pp. 113–123.","ieee":"R. Koning, G. Polevoy, L. Meijer, C. de Laat, and P. Grosso, “Approaches for Collaborative Security Defences in Multi Network Environments,” in <i>2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)</i>, 2019, pp. 113–123.","apa":"Koning, R., Polevoy, G., Meijer, L., de Laat, C., &#38; Grosso, P. (2019). Approaches for Collaborative Security Defences in Multi Network Environments. In <i>2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)</i> (pp. 113–123). <a href=\"https://doi.org/10.1109/CSCloud/EdgeCom.2019.000-9\">https://doi.org/10.1109/CSCloud/EdgeCom.2019.000-9</a>","bibtex":"@inproceedings{Koning_Polevoy_Meijer_de Laat_Grosso_2019, series={2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)}, title={Approaches for Collaborative Security Defences in Multi Network Environments}, DOI={<a href=\"https://doi.org/10.1109/CSCloud/EdgeCom.2019.000-9\">10.1109/CSCloud/EdgeCom.2019.000-9</a>}, booktitle={2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)}, author={Koning, Ralph and Polevoy, Gleb and Meijer, Lydia and de Laat, Cees and Grosso, Paola}, year={2019}, pages={113–123}, collection={2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)} }","ama":"Koning R, Polevoy G, Meijer L, de Laat C, Grosso P. Approaches for Collaborative Security Defences in Multi Network Environments. In: <i>2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)</i>. 2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom). ; 2019:113-123. doi:<a href=\"https://doi.org/10.1109/CSCloud/EdgeCom.2019.000-9\">10.1109/CSCloud/EdgeCom.2019.000-9</a>","mla":"Koning, Ralph, et al. “Approaches for Collaborative Security Defences in Multi Network Environments.” <i>2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)</i>, 2019, pp. 113–23, doi:<a href=\"https://doi.org/10.1109/CSCloud/EdgeCom.2019.000-9\">10.1109/CSCloud/EdgeCom.2019.000-9</a>."},"quality_controlled":"1","conference":{"name":"2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)"},"status":"public","_id":"17667","page":"113-123","user_id":"83983"},{"abstract":[{"lang":"eng","text":"Advances in electromyographic (EMG) sensor technology and machine learning algorithms have led to an increased research effort into high density EMG-based pattern recognition methods for prosthesis control. With the goal set on an autonomous multi-movement prosthesis capable of performing training and classification of an amputee’s EMG signals, the focus of this paper lies in the acceleration of the embedded signal processing chain. We present two Xilinx Zynq-based architectures for accelerating two inherently different high density EMG-based control algorithms. The first hardware accelerated design achieves speed-ups of up to 4.8 over the software-only solution, allowing for a processing delay lower than the sample period of 1 ms. The second system achieved a speed-up of 5.5 over the software-only version and operates at a still satisfactory low processing delay of up to 15 ms while providing a higher reliability and robustness against electrode shift and noisy channels."}],"publication":"Journal of Parallel and Distributed Computing","keyword":["High density electromyography","FPGA acceleration","Medical signal processing","Pattern recognition","Prosthetics"],"type":"journal_article","department":[{"_id":"78"}],"date_created":"2019-07-12T13:13:55Z","date_updated":"2022-01-06T06:51:13Z","publication_status":"published","intvolume":"       123","year":"2019","title":"Zynq-based acceleration of robust high density myoelectric signal processing","publication_identifier":{"issn":["0743-7315"]},"author":[{"last_name":"Boschmann","first_name":"Alexander","full_name":"Boschmann, Alexander"},{"full_name":"Agne, Andreas","first_name":"Andreas","last_name":"Agne"},{"full_name":"Thombansen, Georg","first_name":"Georg","last_name":"Thombansen"},{"id":"49051","first_name":"Linus Matthias","last_name":"Witschen","full_name":"Witschen, Linus Matthias"},{"first_name":"Florian","last_name":"Kraus","full_name":"Kraus, Florian"},{"id":"398","first_name":"Marco","last_name":"Platzner","full_name":"Platzner, Marco"}],"doi":"10.1016/j.jpdc.2018.07.004","language":[{"iso":"eng"}],"citation":{"ama":"Boschmann A, Agne A, Thombansen G, Witschen LM, Kraus F, Platzner M. Zynq-based acceleration of robust high density myoelectric signal processing. <i>Journal of Parallel and Distributed Computing</i>. 2019;123:77-89. doi:<a href=\"https://doi.org/10.1016/j.jpdc.2018.07.004\">10.1016/j.jpdc.2018.07.004</a>","bibtex":"@article{Boschmann_Agne_Thombansen_Witschen_Kraus_Platzner_2019, title={Zynq-based acceleration of robust high density myoelectric signal processing}, volume={123}, DOI={<a href=\"https://doi.org/10.1016/j.jpdc.2018.07.004\">10.1016/j.jpdc.2018.07.004</a>}, journal={Journal of Parallel and Distributed Computing}, publisher={Elsevier}, author={Boschmann, Alexander and Agne, Andreas and Thombansen, Georg and Witschen, Linus Matthias and Kraus, Florian and Platzner, Marco}, year={2019}, pages={77–89} }","mla":"Boschmann, Alexander, et al. “Zynq-Based Acceleration of Robust High Density Myoelectric Signal Processing.” <i>Journal of Parallel and Distributed Computing</i>, vol. 123, Elsevier, 2019, pp. 77–89, doi:<a href=\"https://doi.org/10.1016/j.jpdc.2018.07.004\">10.1016/j.jpdc.2018.07.004</a>.","short":"A. Boschmann, A. Agne, G. Thombansen, L.M. Witschen, F. Kraus, M. Platzner, Journal of Parallel and Distributed Computing 123 (2019) 77–89.","chicago":"Boschmann, Alexander, Andreas Agne, Georg Thombansen, Linus Matthias Witschen, Florian Kraus, and Marco Platzner. “Zynq-Based Acceleration of Robust High Density Myoelectric Signal Processing.” <i>Journal of Parallel and Distributed Computing</i> 123 (2019): 77–89. <a href=\"https://doi.org/10.1016/j.jpdc.2018.07.004\">https://doi.org/10.1016/j.jpdc.2018.07.004</a>.","apa":"Boschmann, A., Agne, A., Thombansen, G., Witschen, L. M., Kraus, F., &#38; Platzner, M. (2019). Zynq-based acceleration of robust high density myoelectric signal processing. <i>Journal of Parallel and Distributed Computing</i>, <i>123</i>, 77–89. <a href=\"https://doi.org/10.1016/j.jpdc.2018.07.004\">https://doi.org/10.1016/j.jpdc.2018.07.004</a>","ieee":"A. Boschmann, A. Agne, G. Thombansen, L. M. Witschen, F. Kraus, and M. Platzner, “Zynq-based acceleration of robust high density myoelectric signal processing,” <i>Journal of Parallel and Distributed Computing</i>, vol. 123, pp. 77–89, 2019."},"status":"public","user_id":"398","volume":123,"page":"77-89","_id":"11950","publisher":"Elsevier"},{"publication_status":"published","date_updated":"2023-12-13T10:43:07Z","publication_identifier":{"isbn":["978-3-030-12598-1"]},"author":[{"first_name":"Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","full_name":"Bossek, Jakob","id":"102979"},{"last_name":"Grimme","first_name":"Christian","full_name":"Grimme, Christian"},{"last_name":"Meisel","first_name":"Stephan","full_name":"Meisel, Stephan"},{"full_name":"Rudolph, Günter","last_name":"Rudolph","first_name":"Günter"},{"first_name":"Heike","last_name":"Trautmann","full_name":"Trautmann, Heike"}],"year":"2019","title":"Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm","doi":"10.1007/978-3-030-12598-1_41","language":[{"iso":"eng"}],"series_title":"Lecture Notes in Computer Science","extern":"1","abstract":[{"text":"We tackle a bi-objective dynamic orienteering problem where customer requests arise as time passes by. The goal is to minimize the tour length traveled by a single delivery vehicle while simultaneously keeping the number of dismissed dynamic customers to a minimum. We propose a dynamic Evolutionary Multi-Objective Algorithm which is grounded on insights gained from a previous series of work on an a-posteriori version of the problem, where all request times are known in advance. In our experiments, we simulate different decision maker strategies and evaluate the development of the Pareto-front approximations on exemplary problem instances. It turns out, that despite severely reduced computational budget and no oracle-knowledge of request times the dynamic EMOA is capable of producing approximations which partially dominate the results of the a-posteriori EMOA and dynamic integer linear programming strategies.","lang":"eng"}],"publication":"Evolutionary Multi-Criterion Optimization (EMO)","department":[{"_id":"819"}],"type":"conference","keyword":["Combinatorial optimization","Dynamic optimization","Metaheuristics","Multi-objective optimization","Vehicle routing"],"date_created":"2023-11-14T15:58:52Z","status":"public","editor":[{"first_name":"Kalyanmoy","last_name":"Deb","full_name":"Deb, Kalyanmoy"},{"last_name":"Goodman","first_name":"Erik","full_name":"Goodman, Erik"},{"first_name":"Carlos A.","last_name":"Coello Coello","full_name":"Coello Coello, Carlos A."},{"full_name":"Klamroth, Kathrin","last_name":"Klamroth","first_name":"Kathrin"},{"full_name":"Miettinen, Kaisa","first_name":"Kaisa","last_name":"Miettinen"},{"full_name":"Mostaghim, Sanaz","first_name":"Sanaz","last_name":"Mostaghim"},{"first_name":"Patrick","last_name":"Reed","full_name":"Reed, Patrick"}],"user_id":"102979","_id":"48841","publisher":"Springer International Publishing","page":"516–528","citation":{"chicago":"Bossek, Jakob, Christian Grimme, Stephan Meisel, Günter Rudolph, and Heike Trautmann. “Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm.” In <i>Evolutionary Multi-Criterion Optimization (EMO)</i>, edited by Kalyanmoy Deb, Erik Goodman, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, and Patrick Reed, 516–528. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019. <a href=\"https://doi.org/10.1007/978-3-030-12598-1_41\">https://doi.org/10.1007/978-3-030-12598-1_41</a>.","short":"J. Bossek, C. Grimme, S. Meisel, G. Rudolph, H. Trautmann, in: K. Deb, E. Goodman, C.A. Coello Coello, K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO), Springer International Publishing, Cham, 2019, pp. 516–528.","apa":"Bossek, J., Grimme, C., Meisel, S., Rudolph, G., &#38; Trautmann, H. (2019). Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm. In K. Deb, E. Goodman, C. A. Coello Coello, K. Klamroth, K. Miettinen, S. Mostaghim, &#38; P. Reed (Eds.), <i>Evolutionary Multi-Criterion Optimization (EMO)</i> (pp. 516–528). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-030-12598-1_41\">https://doi.org/10.1007/978-3-030-12598-1_41</a>","ieee":"J. Bossek, C. Grimme, S. Meisel, G. Rudolph, and H. Trautmann, “Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm,” in <i>Evolutionary Multi-Criterion Optimization (EMO)</i>, 2019, pp. 516–528, doi: <a href=\"https://doi.org/10.1007/978-3-030-12598-1_41\">10.1007/978-3-030-12598-1_41</a>.","ama":"Bossek J, Grimme C, Meisel S, Rudolph G, Trautmann H. Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm. In: Deb K, Goodman E, Coello Coello CA, et al., eds. <i>Evolutionary Multi-Criterion Optimization (EMO)</i>. Lecture Notes in Computer Science. Springer International Publishing; 2019:516–528. doi:<a href=\"https://doi.org/10.1007/978-3-030-12598-1_41\">10.1007/978-3-030-12598-1_41</a>","bibtex":"@inproceedings{Bossek_Grimme_Meisel_Rudolph_Trautmann_2019, place={Cham}, series={Lecture Notes in Computer Science}, title={Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-12598-1_41\">10.1007/978-3-030-12598-1_41</a>}, booktitle={Evolutionary Multi-Criterion Optimization (EMO)}, publisher={Springer International Publishing}, author={Bossek, Jakob and Grimme, Christian and Meisel, Stephan and Rudolph, Günter and Trautmann, Heike}, editor={Deb, Kalyanmoy and Goodman, Erik and Coello Coello, Carlos A. and Klamroth, Kathrin and Miettinen, Kaisa and Mostaghim, Sanaz and Reed, Patrick}, year={2019}, pages={516–528}, collection={Lecture Notes in Computer Science} }","mla":"Bossek, Jakob, et al. “Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm.” <i>Evolutionary Multi-Criterion Optimization (EMO)</i>, edited by Kalyanmoy Deb et al., Springer International Publishing, 2019, pp. 516–528, doi:<a href=\"https://doi.org/10.1007/978-3-030-12598-1_41\">10.1007/978-3-030-12598-1_41</a>."},"place":"Cham"},{"extern":"1","abstract":[{"text":"Research has shown that for many single-objective graph problems where optimum solutions are composed of low weight sub-graphs, such as the minimum spanning tree problem (MST), mutation operators favoring low weight edges show superior performance. Intuitively, similar observations should hold for multi-criteria variants of such problems. In this work, we focus on the multi-criteria MST problem. A thorough experimental study is conducted where we estimate the probability of edges being part of non-dominated spanning trees as a function of the edges’ non-domination level or domination count, respectively. Building on gained insights, we propose several biased one-edge-exchange mutation operators that differ in the used edge-selection probability distribution (biased towards edges of low rank). Our empirical analysis shows that among different graph types (dense and sparse) and edge weight types (both uniformly random and combinations of Euclidean and uniformly random) biased edge-selection strategies perform superior in contrast to the baseline uniform edge-selection. Our findings are in particular strong for dense graphs.","lang":"eng"}],"publication":"Proceedings of the Genetic and Evolutionary Computation Conference","type":"conference","keyword":["biased mutation","combinatorial optimization","minimum spanning tree","multi-objective optimization"],"department":[{"_id":"819"}],"date_created":"2023-11-14T15:58:52Z","publication_status":"published","date_updated":"2023-12-13T10:42:24Z","year":"2019","title":"On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem","author":[{"last_name":"Bossek","first_name":"Jakob","orcid":"0000-0002-4121-4668","full_name":"Bossek, Jakob","id":"102979"},{"full_name":"Grimme, Christian","first_name":"Christian","last_name":"Grimme"},{"full_name":"Neumann, Frank","last_name":"Neumann","first_name":"Frank"}],"publication_identifier":{"isbn":["978-1-4503-6111-8"]},"doi":"10.1145/3321707.3321818","language":[{"iso":"eng"}],"series_title":"GECCO ’19","citation":{"ieee":"J. Bossek, C. Grimme, and F. Neumann, “On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2019, pp. 516–523, doi: <a href=\"https://doi.org/10.1145/3321707.3321818\">10.1145/3321707.3321818</a>.","apa":"Bossek, J., Grimme, C., &#38; Neumann, F. (2019). On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 516–523. <a href=\"https://doi.org/10.1145/3321707.3321818\">https://doi.org/10.1145/3321707.3321818</a>","chicago":"Bossek, Jakob, Christian Grimme, and Frank Neumann. “On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 516–523. GECCO ’19. New York, NY, USA: Association for Computing Machinery, 2019. <a href=\"https://doi.org/10.1145/3321707.3321818\">https://doi.org/10.1145/3321707.3321818</a>.","short":"J. Bossek, C. Grimme, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2019, pp. 516–523.","mla":"Bossek, Jakob, et al. “On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2019, pp. 516–523, doi:<a href=\"https://doi.org/10.1145/3321707.3321818\">10.1145/3321707.3321818</a>.","bibtex":"@inproceedings{Bossek_Grimme_Neumann_2019, place={New York, NY, USA}, series={GECCO ’19}, title={On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem}, DOI={<a href=\"https://doi.org/10.1145/3321707.3321818\">10.1145/3321707.3321818</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Bossek, Jakob and Grimme, Christian and Neumann, Frank}, year={2019}, pages={516–523}, collection={GECCO ’19} }","ama":"Bossek J, Grimme C, Neumann F. On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. GECCO ’19. Association for Computing Machinery; 2019:516–523. doi:<a href=\"https://doi.org/10.1145/3321707.3321818\">10.1145/3321707.3321818</a>"},"place":"New York, NY, USA","status":"public","user_id":"102979","page":"516–523","_id":"48840","publisher":"Association for Computing Machinery"}]