[{"publication":"Industry 4.0 Science","abstract":[{"lang":"eng","text":"Technical systems are characterized by increasing interdisciplinarity, complexity and networking. A product and its corresponding production systems require interdisciplinary multi-objective optimization. Sustainability and recyclability demands increase said complexity. The efficiency of previously established engineering methods is reaching its limits, which can only be overcome by systematic integration of extreme data. The aim of \"hybrid decision support\" is as follows: Data science and artificial intelligence should be used to supplement human capabilities in conjunction with existing heuristics, methods, modeling and simulation to increase the efficiency of product creation."}],"keyword":["AI","artificial intelligence","Data Science","decision support","extreme data","Künstliche Intelligenz","product creation","product development"],"language":[{"iso":"eng"}],"quality_controlled":"1","issue":"1","year":"2025","publisher":"GITO mbH Verlag","date_created":"2025-02-15T09:31:30Z","title":"Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence","type":"journal_article","status":"public","_id":"58650","user_id":"405","department":[{"_id":"152"}],"article_type":"original","alternative_title":["Hybride Entscheidungsunterstützung in der Produktentstehung - Mit Data Science und Künstlicher Intelligenz die Leistungsfähigkeit erhöhen"],"publication_status":"published","publication_identifier":{"issn":["2942-6170"]},"citation":{"ieee":"I. Gräßler, J. Pottebaum, P. Nyhuis, R. Stark, K.-D. Thoben, and P. Wiederkehr, “Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence,” <i>Industry 4.0 Science</i>, vol. 2025, no. 1, 2025, doi: <a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>.","chicago":"Gräßler, Iris, Jens Pottebaum, Peter Nyhuis, Rainer Stark, Klaus-Dieter Thoben, and Petra Wiederkehr. “Hybrid Decision Support in Product Creation - Improving Performance with Data Science and Artificial Intelligence.” <i>Industry 4.0 Science</i> 2025, no. 1 (2025). <a href=\"https://doi.org/10.30844/i4sd.25.1.18\">https://doi.org/10.30844/i4sd.25.1.18</a>.","ama":"Gräßler I, Pottebaum J, Nyhuis P, Stark R, Thoben K-D, Wiederkehr P. Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence. <i>Industry 40 Science</i>. 2025;2025(1). doi:<a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>","apa":"Gräßler, I., Pottebaum, J., Nyhuis, P., Stark, R., Thoben, K.-D., &#38; Wiederkehr, P. (2025). Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence. <i>Industry 4.0 Science</i>, <i>2025</i>(1). <a href=\"https://doi.org/10.30844/i4sd.25.1.18\">https://doi.org/10.30844/i4sd.25.1.18</a>","short":"I. Gräßler, J. Pottebaum, P. Nyhuis, R. Stark, K.-D. Thoben, P. Wiederkehr, Industry 4.0 Science 2025 (2025).","mla":"Gräßler, Iris, et al. “Hybrid Decision Support in Product Creation - Improving Performance with Data Science and Artificial Intelligence.” <i>Industry 4.0 Science</i>, vol. 2025, no. 1, GITO mbH Verlag, 2025, doi:<a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>.","bibtex":"@article{Gräßler_Pottebaum_Nyhuis_Stark_Thoben_Wiederkehr_2025, title={Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence}, volume={2025}, DOI={<a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>}, number={1}, journal={Industry 4.0 Science}, publisher={GITO mbH Verlag}, author={Gräßler, Iris and Pottebaum, Jens and Nyhuis, Peter and Stark, Rainer and Thoben, Klaus-Dieter and Wiederkehr, Petra}, year={2025} }"},"intvolume":"      2025","oa":"1","date_updated":"2025-02-15T09:40:52Z","author":[{"first_name":"Iris","full_name":"Gräßler, Iris","id":"47565","last_name":"Gräßler","orcid":"0000-0001-5765-971X"},{"last_name":"Pottebaum","orcid":"http://orcid.org/0000-0001-8778-2989","full_name":"Pottebaum, Jens","id":"405","first_name":"Jens"},{"last_name":"Nyhuis","full_name":"Nyhuis, Peter","first_name":"Peter"},{"first_name":"Rainer","full_name":"Stark, Rainer","last_name":"Stark"},{"full_name":"Thoben, Klaus-Dieter","last_name":"Thoben","first_name":"Klaus-Dieter"},{"first_name":"Petra","last_name":"Wiederkehr","full_name":"Wiederkehr, Petra"}],"volume":2025,"main_file_link":[{"open_access":"1"}],"doi":"10.30844/i4sd.25.1.18"},{"status":"public","abstract":[{"lang":"eng","text":"Algorithmic bias has long been recognized as a key problem affecting decision-making processes that integrate artificial intelligence (AI) technologies. The increased use of AI in making military decisions relevant to the use of force has sustained such questions about biases in these technologies and in how human users programme with and rely on data based on hierarchized socio-cultural norms, knowledges, and modes of attention.\r\n\r\nIn this post, Dr Ingvild Bode, Professor at the Center for War Studies, University of Southern Denmark, and Ishmael Bhila, PhD researcher at the “Meaningful Human Control: Between Regulation and Reflexion” project, Paderborn University, unpack the problem of algorithmic bias with reference to AI-based decision support systems (AI DSS). They examine three categories of algorithmic bias – preexisting bias, technical bias, and emergent bias – across four lifecycle stages of an AI DSS, concluding that stakeholders in the ongoing discussion about AI in the military domain should consider the impact of algorithmic bias on AI DSS more seriously."}],"type":"misc","language":[{"iso":"eng"}],"keyword":["Algorithmic Bias","AI","Decision Support Systems","Autonomous Weapons Systems"],"user_id":"105772","_id":"56282","citation":{"ama":"Bhila I, Bode I. <i>The Problem of Algorithmic Bias in AI-Based Military Decision Support Systems</i>. ICRC Humanitarian Law &#38; Policy Blog; 2024.","chicago":"Bhila, Ishmael, and Ingvild Bode. <i>The Problem of Algorithmic Bias in AI-Based Military Decision Support Systems</i>. ICRC Humanitarian Law &#38; Policy Blog, 2024.","ieee":"I. Bhila and I. Bode, <i>The problem of algorithmic bias in AI-based military decision support systems</i>. ICRC Humanitarian Law &#38; Policy Blog, 2024.","bibtex":"@book{Bhila_Bode_2024, title={The problem of algorithmic bias in AI-based military decision support systems}, publisher={ICRC Humanitarian Law &#38; Policy Blog}, author={Bhila, Ishmael and Bode, Ingvild}, year={2024} }","mla":"Bhila, Ishmael, and Ingvild Bode. <i>The Problem of Algorithmic Bias in AI-Based Military Decision Support Systems</i>. ICRC Humanitarian Law &#38; Policy Blog, 2024.","short":"I. Bhila, I. Bode, The Problem of Algorithmic Bias in AI-Based Military Decision Support Systems, ICRC Humanitarian Law &#38; Policy Blog, 2024.","apa":"Bhila, I., &#38; Bode, I. (2024). <i>The problem of algorithmic bias in AI-based military decision support systems</i>. ICRC Humanitarian Law &#38; Policy Blog."},"year":"2024","related_material":{"link":[{"relation":"confirmation","url":"https://blogs.icrc.org/law-and-policy/2024/09/03/the-problem-of-algorithmic-bias-in-ai-based-military-decision-support-systems/"}]},"publication_status":"published","has_accepted_license":"1","main_file_link":[{"open_access":"1","url":"https://blogs.icrc.org/law-and-policy/2024/09/03/the-problem-of-algorithmic-bias-in-ai-based-military-decision-support-systems/"}],"title":"The problem of algorithmic bias in AI-based military decision support systems","date_created":"2024-09-30T11:44:28Z","author":[{"first_name":"Ishmael","last_name":"Bhila","full_name":"Bhila, Ishmael","id":"105772"},{"full_name":"Bode, Ingvild","last_name":"Bode","first_name":"Ingvild"}],"date_updated":"2024-11-26T09:49:48Z","publisher":"ICRC Humanitarian Law & Policy Blog","oa":"1"},{"date_updated":"2024-10-09T15:04:53Z","author":[{"first_name":"Felix","full_name":"Liedeker, Felix","id":"93275","last_name":"Liedeker"},{"first_name":"Philipp","last_name":"Cimiano","full_name":"Cimiano, Philipp"}],"date_created":"2024-10-09T14:50:09Z","title":"A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations","conference":{"location":"Lissabon","end_date":"2023-07-28","start_date":"2023-07-26","name":"xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023)"},"year":"2023","citation":{"apa":"Liedeker, F., &#38; Cimiano, P. (2023). <i>A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations</i>. xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023), Lissabon.","mla":"Liedeker, Felix, and Philipp Cimiano. <i>A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations</i>. 2023.","short":"F. Liedeker, P. Cimiano, in: 2023.","bibtex":"@inproceedings{Liedeker_Cimiano_2023, title={A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations}, author={Liedeker, Felix and Cimiano, Philipp}, year={2023} }","ama":"Liedeker F, Cimiano P. A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations. In: ; 2023.","chicago":"Liedeker, Felix, and Philipp Cimiano. “A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations,” 2023.","ieee":"F. Liedeker and P. Cimiano, “A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations,” presented at the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023), Lissabon, 2023."},"project":[{"_id":"128","name":"TRR 318 - C5: TRR 318 - Subproject C5"}],"_id":"56477","user_id":"93275","department":[{"_id":"660"}],"keyword":["Explainable AI","Clinical decision support","Bayesian network","Counterfactual explanations"],"language":[{"iso":"eng"}],"type":"conference","abstract":[{"lang":"eng","text":"We describe a prototype of a Clinical Decision Support System (CDSS) that provides (counterfactual) explanations to support accurate medical diagnosis. The prototype is based on an inherently interpretable Bayesian network (BN). Our research aims to investigate which explanations are most useful for medical experts and whether co-constructing explanations can foster trust and acceptance of CDSS."}],"status":"public"},{"year":"2022","citation":{"apa":"Kucklick, J.-P. (2022). Towards a model- and data-focused taxonomy of XAI systems. <i>Wirtschaftsinformatik 2022 Proceedings</i>. Wirtschaftsinformatik 2022 (WI22), Nürnberg (online).","mla":"Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI Systems.” <i>Wirtschaftsinformatik 2022 Proceedings</i>, 2022.","bibtex":"@inproceedings{Kucklick_2022, title={Towards a model- and data-focused taxonomy of XAI systems}, booktitle={Wirtschaftsinformatik 2022 Proceedings}, author={Kucklick, Jan-Peter}, year={2022} }","short":"J.-P. Kucklick, in: Wirtschaftsinformatik 2022 Proceedings, 2022.","ieee":"J.-P. Kucklick, “Towards a model- and data-focused taxonomy of XAI systems,” presented at the Wirtschaftsinformatik 2022 (WI22), Nürnberg (online), 2022.","chicago":"Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI Systems.” In <i>Wirtschaftsinformatik 2022 Proceedings</i>, 2022.","ama":"Kucklick J-P. Towards a model- and data-focused taxonomy of XAI systems. In: <i>Wirtschaftsinformatik 2022 Proceedings</i>. ; 2022."},"oa":"1","date_updated":"2022-01-26T08:24:30Z","date_created":"2022-01-26T08:22:03Z","author":[{"full_name":"Kucklick, Jan-Peter","id":"77066","last_name":"Kucklick","first_name":"Jan-Peter"}],"title":"Towards a model- and data-focused taxonomy of XAI systems","conference":{"location":"Nürnberg (online)","end_date":"2022-02-23","start_date":"2022-02-21","name":"Wirtschaftsinformatik 2022 (WI22)"},"main_file_link":[{"url":"https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1056&context=wi2022","open_access":"1"}],"publication":"Wirtschaftsinformatik 2022 Proceedings","type":"conference","abstract":[{"text":"Explainable Artificial Intelligence (XAI) is currently an important topic for the application of Machine Learning (ML) in high-stakes decision scenarios. Related research focuses on evaluating ML algorithms in terms of interpretability. However, providing a human understandable explanation of an intelligent system does not only relate to the used ML algorithm. The data and features used also have a considerable impact on interpretability. In this paper, we develop a taxonomy for describing XAI systems based on aspects about the algorithm and data. The proposed taxonomy gives researchers and practitioners opportunities to describe and evaluate current XAI systems with respect to interpretability and guides the future development of this class of systems.","lang":"eng"}],"status":"public","_id":"29539","department":[{"_id":"195"},{"_id":"196"}],"user_id":"77066","keyword":["Explainable Artificial Intelligence","XAI","Interpretability","Decision Support Systems","Taxonomy"],"language":[{"iso":"eng"}]},{"type":"conference","publication":"Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management","file":[{"file_name":"2018_ISCRAM_Conference_Proceedings - Publication Version.pdf","file_id":"6020","access_level":"open_access","file_size":488472,"date_created":"2018-12-07T11:25:06Z","creator":"hsiemes","date_updated":"2018-12-13T15:05:44Z","relation":"main_file","content_type":"application/pdf"}],"status":"public","abstract":[{"lang":"eng","text":"When responding to natural disasters, professional relief units are often supported by many volunteers which are not affiliated to humanitarian organizations. The effective coordination of these volunteers is crucial to leverage their capabilities and to avoid conflicts with professional relief units. In this paper, we empirically identify key requirements that professional relief units pose on this coordination. Based on these requirements, we suggest a decision model. We computationally solve a real-world instance of the model and empirically validate the computed solution in interviews with practitioners. Our results show that the suggested model allows for solving volunteer coordination tasks of realistic size near-optimally within short time, with the determined solution being well accepted by practitioners. We also describe in this article how the suggested decision support model is integrated in the volunteer coordination system which we develop in joint cooperation with a disaster management authority and a software development company."}],"user_id":"61579","department":[{"_id":"277"}],"_id":"5675","language":[{"iso":"eng"}],"file_date_updated":"2018-12-13T15:05:44Z","extern":"1","ddc":["000"],"keyword":["Coordination of spontaneous volunteers","volunteer coordination system","decision support","scheduling optimization model","linear programming"],"has_accepted_license":"1","citation":{"ieee":"G. Rauchecker and G. Schryen, “Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief,” in <i>Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management</i>, Rochester, NY, USA, 2018.","chicago":"Rauchecker, Gerhard, and Guido Schryen. “Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief.” In <i>Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management</i>, 2018.","ama":"Rauchecker G, Schryen G. Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief. In: <i>Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management</i>. ; 2018.","apa":"Rauchecker, G., &#38; Schryen, G. (2018). Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief. In <i>Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management</i>. Rochester, NY, USA.","mla":"Rauchecker, Gerhard, and Guido Schryen. “Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief.” <i>Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management</i>, 2018.","bibtex":"@inproceedings{Rauchecker_Schryen_2018, title={Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief}, booktitle={Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management}, author={Rauchecker, Gerhard and Schryen, Guido}, year={2018} }","short":"G. Rauchecker, G. Schryen, in: Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management, 2018."},"year":"2018","author":[{"first_name":"Gerhard","full_name":"Rauchecker, Gerhard","last_name":"Rauchecker"},{"first_name":"Guido","last_name":"Schryen","id":"72850","full_name":"Schryen, Guido"}],"date_created":"2018-11-14T15:35:54Z","date_updated":"2022-01-06T07:02:28Z","oa":"1","conference":{"name":"15th International Conference on Information Systems for Crisis Response and Management","location":"Rochester, NY, USA"},"title":"Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief"},{"publication":"European Journal of Operational Research","abstract":[{"lang":"eng","text":"Multi-attribute value theory (MAVT)-based recommender systems have been proposed for dealing with issues of existing recommender systems, such as the cold-start problem and changing preferences. However, as we argue in this paper, existing MAVT-based methods for measuring attribute importance weights do not fit the shopping tasks for which recommender systems are typically used. These methods assume well-trained decision makers who are willing to invest time and cognitive effort, and who are familiar with the attributes describing the available alternatives and the ranges of these attribute levels. Yet, recommender systems are most often used by consumers who are usually not familiar with the available attributes and ranges and who wish to save time and effort. Against this background, we develop a new method, based on a product configuration process, which is tailored to the characteristics of these particular decision makers. We empirically compare our method to SWING, ranking-based conjoint analysis and TRADEOFF in a between-subjects laboratory experiment with 153 participants. Results indicate that our proposed method performs better than TRADEOFF and CONJOINT and at least as well as SWING in terms of recommendation accuracy, better than SWING and TRADEOFF and at least as well as CONJOINT in terms of cognitive load, and that participants were faster with our method than with any other method. We conclude that our method is a promising option to help support consumers' decision processes in e-commerce shopping tasks."}],"file":[{"file_id":"6025","access_level":"open_access","file_name":"EJOR article.pdf","file_size":762889,"date_created":"2018-12-07T11:30:59Z","creator":"hsiemes","date_updated":"2018-12-13T15:06:56Z","relation":"main_file","content_type":"application/pdf"}],"ddc":["000"],"keyword":["E-Commerce","Recommender System","Attribute Weights","Configuration System","Decision Support"],"language":[{"iso":"eng"}],"issue":"1","year":"2017","publisher":"Elsevier","date_created":"2018-11-14T15:06:18Z","title":"A configuration-based recommender system for supporting e-commerce decisions","type":"journal_article","status":"public","_id":"5671","user_id":"61579","department":[{"_id":"277"}],"file_date_updated":"2018-12-13T15:06:56Z","extern":"1","has_accepted_license":"1","citation":{"mla":"Scholz, Michael, et al. “A Configuration-Based Recommender System for Supporting e-Commerce Decisions.” <i>European Journal of Operational Research</i>, vol. 259, no. 1, Elsevier, 2017, pp. 205–15.","short":"M. Scholz, V. Dorner, G. Schryen, A. Benlian, European Journal of Operational Research 259 (2017) 205–215.","bibtex":"@article{Scholz_Dorner_Schryen_Benlian_2017, title={A configuration-based recommender system for supporting e-commerce decisions}, volume={259}, number={1}, journal={European Journal of Operational Research}, publisher={Elsevier}, author={Scholz, Michael and Dorner, Verena and Schryen, Guido and Benlian, Alexander}, year={2017}, pages={205–215} }","apa":"Scholz, M., Dorner, V., Schryen, G., &#38; Benlian, A. (2017). A configuration-based recommender system for supporting e-commerce decisions. <i>European Journal of Operational Research</i>, <i>259</i>(1), 205–215.","ama":"Scholz M, Dorner V, Schryen G, Benlian A. A configuration-based recommender system for supporting e-commerce decisions. <i>European Journal of Operational Research</i>. 2017;259(1):205-215.","ieee":"M. Scholz, V. Dorner, G. Schryen, and A. Benlian, “A configuration-based recommender system for supporting e-commerce decisions,” <i>European Journal of Operational Research</i>, vol. 259, no. 1, pp. 205–215, 2017.","chicago":"Scholz, Michael, Verena Dorner, Guido Schryen, and Alexander Benlian. “A Configuration-Based Recommender System for Supporting e-Commerce Decisions.” <i>European Journal of Operational Research</i> 259, no. 1 (2017): 205–15."},"intvolume":"       259","page":"205 - 215","date_updated":"2022-01-06T07:02:27Z","oa":"1","author":[{"first_name":"Michael","full_name":"Scholz, Michael","last_name":"Scholz"},{"full_name":"Dorner, Verena","last_name":"Dorner","first_name":"Verena"},{"first_name":"Guido","last_name":"Schryen","id":"72850","full_name":"Schryen, Guido"},{"full_name":"Benlian, Alexander","last_name":"Benlian","first_name":"Alexander"}],"volume":259},{"publication":"Australasian Conference on Information Systems","type":"conference","status":"public","file":[{"date_updated":"2018-12-13T15:08:28Z","date_created":"2018-12-07T11:40:18Z","creator":"hsiemes","file_size":6771871,"file_id":"6031","access_level":"open_access","file_name":"ACIS_2015_paper_7.pdf","content_type":"application/pdf","relation":"main_file"}],"abstract":[{"text":"Many academic disciplines - including information systems, computer science, and operations management - face scheduling problems as important decision making tasks. Since many scheduling problems are NP-hard in the strong sense, there is a need for developing solution heuristics. For scheduling problems with setup times on unrelated parallel machines, there is limited research on solution methods and to the best of our knowledge, parallel computer architectures have not yet been taken advantage of. We address this gap by proposing and implementing a new solution heuristic and by testing different parallelization strategies. In our computational experiments, we show that our heuristic calculates near-optimal solutions even for large instances and that computing time can be reduced substantially by our parallelization approach.","lang":"eng"}],"department":[{"_id":"277"}],"user_id":"61579","_id":"5678","file_date_updated":"2018-12-13T15:08:28Z","extern":"1","language":[{"iso":"eng"}],"keyword":["scheduling","decision support","heuristic","high performance computing","parallel algorithms"],"ddc":["000"],"has_accepted_license":"1","page":"1-13","citation":{"chicago":"Rauchecker, Gerhard, and Guido Schryen. “High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic.” In <i>Australasian Conference on Information Systems</i>, 1–13, 2015.","ieee":"G. Rauchecker and G. Schryen, “High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic,” in <i>Australasian Conference on Information Systems</i>, 2015, pp. 1–13.","ama":"Rauchecker G, Schryen G. High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic. In: <i>Australasian Conference on Information Systems</i>. ; 2015:1-13.","apa":"Rauchecker, G., &#38; Schryen, G. (2015). High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic. In <i>Australasian Conference on Information Systems</i> (pp. 1–13).","mla":"Rauchecker, Gerhard, and Guido Schryen. “High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic.” <i>Australasian Conference on Information Systems</i>, 2015, pp. 1–13.","bibtex":"@inproceedings{Rauchecker_Schryen_2015, title={High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic}, booktitle={Australasian Conference on Information Systems}, author={Rauchecker, Gerhard and Schryen, Guido}, year={2015}, pages={1–13} }","short":"G. Rauchecker, G. Schryen, in: Australasian Conference on Information Systems, 2015, pp. 1–13."},"year":"2015","author":[{"last_name":"Rauchecker","full_name":"Rauchecker, Gerhard","first_name":"Gerhard"},{"first_name":"Guido","id":"72850","full_name":"Schryen, Guido","last_name":"Schryen"}],"date_created":"2018-11-14T15:39:50Z","date_updated":"2022-01-06T07:02:30Z","oa":"1","title":"High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic"},{"author":[{"first_name":"Josef","last_name":"Finkbeiner","full_name":"Finkbeiner, Josef"},{"first_name":"Christian","full_name":"Bodenstein, Christian","last_name":"Bodenstein"},{"full_name":"Schryen, Guido","id":"72850","last_name":"Schryen","first_name":"Guido"},{"last_name":"Neumann","full_name":"Neumann, Dirk","first_name":"Dirk"}],"date_created":"2018-11-14T15:45:11Z","oa":"1","date_updated":"2022-01-06T07:02:32Z","title":"Applying heuristic methods for job scheduling in storage markets","has_accepted_license":"1","citation":{"ama":"Finkbeiner J, Bodenstein C, Schryen G, Neumann D. Applying heuristic methods for job scheduling in storage markets. In: <i>18th European Conference on Information Systems (ECIS 2010)</i>. ; 2010.","ieee":"J. Finkbeiner, C. Bodenstein, G. Schryen, and D. Neumann, “Applying heuristic methods for job scheduling in storage markets,” in <i>18th European Conference on Information Systems (ECIS 2010)</i>, 2010.","chicago":"Finkbeiner, Josef, Christian Bodenstein, Guido Schryen, and Dirk Neumann. “Applying Heuristic Methods for Job Scheduling in Storage Markets.” In <i>18th European Conference on Information Systems (ECIS 2010)</i>, 2010.","apa":"Finkbeiner, J., Bodenstein, C., Schryen, G., &#38; Neumann, D. (2010). Applying heuristic methods for job scheduling in storage markets. In <i>18th European Conference on Information Systems (ECIS 2010)</i>.","bibtex":"@inproceedings{Finkbeiner_Bodenstein_Schryen_Neumann_2010, title={Applying heuristic methods for job scheduling in storage markets}, booktitle={18th European Conference on Information Systems (ECIS 2010)}, author={Finkbeiner, Josef and Bodenstein, Christian and Schryen, Guido and Neumann, Dirk}, year={2010} }","mla":"Finkbeiner, Josef, et al. “Applying Heuristic Methods for Job Scheduling in Storage Markets.” <i>18th European Conference on Information Systems (ECIS 2010)</i>, 2010.","short":"J. Finkbeiner, C. Bodenstein, G. Schryen, D. Neumann, in: 18th European Conference on Information Systems (ECIS 2010), 2010."},"year":"2010","department":[{"_id":"277"}],"user_id":"61579","_id":"5685","extern":"1","file_date_updated":"2018-12-13T15:19:40Z","language":[{"iso":"eng"}],"keyword":["Decision Support System","Algorithms","Optimization","Market Engineering"],"ddc":["000"],"publication":"18th European Conference on Information Systems (ECIS 2010)","type":"conference","status":"public","file":[{"date_created":"2018-12-11T15:21:06Z","creator":"hsiemes","date_updated":"2018-12-13T15:19:40Z","access_level":"open_access","file_name":"s1-ln7055316-1881058806-1939656818Hwf-1884822883IdV-5442784107055316PDF_HI0001.pdf","file_id":"6188","file_size":171336,"content_type":"application/pdf","relation":"main_file"}],"abstract":[{"text":"In double-sided markets for computing resources an optimal allocation schedule among job offers and requests subject to relevant capacity constraints can be determined. With increasing storage demands and emerging storage services the question how to schedule storage jobs becomes more and more interesting. Since such scheduling problems are often in the class NP-complete an exact computation is not feasible in practice. On the other hand an approximation to the optimal solution can easily be found by means of using heuristics. The problem with this attempt is that the suggested solution may not be exactly optimal and is thus less satisfying. Considering the two above mentioned solution approaches one can clearly find a trade-off between the optimality of the solution and the efficiency to get to a solution at all. This work proposes to apply and combine heuristics in optimization to gain from both of their benefits while reducing the problematic aspects. Following this method it is assumed to get closer to the optimal solution in a shorter time compared to a full optimization.","lang":"eng"}]}]