[{"user_id":"15504","department":[{"_id":"34"},{"_id":"819"}],"_id":"46357","language":[{"iso":"eng"}],"type":"book_chapter","publication":"Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings","status":"public","abstract":[{"lang":"eng","text":"The liner shipping fleet repositioning problem (LSFRP) is a central optimization problem within the container shipping industry. Several approaches exist for solving this problem using exact and heuristic techniques, however all of them use a single objective function for determining an optimal solution. We propose a multi-objective approach based on a simulated annealing heuristic so that repositioning coordinators can better balance profit making with cost-savings and environmental sustainability. As the first multi-objective approach in the area of liner shipping routing, we show that giving more options to decision makers need not be costly. Indeed, our approach requires no extra runtime than a weighted objective heuristic and provides a rich set of solutions along the Pareto front."}],"editor":[{"first_name":"H","last_name":"Trautmann","full_name":"Trautmann, H"},{"first_name":"G","full_name":"Rudolph, G","last_name":"Rudolph"},{"full_name":"Klamroth, K","last_name":"Klamroth","first_name":"K"},{"first_name":"O","last_name":"Schütze","full_name":"Schütze, O"},{"first_name":"M","full_name":"Wiecek, M","last_name":"Wiecek"},{"first_name":"Y","last_name":"Jin","full_name":"Jin, Y"},{"first_name":"C","last_name":"Grimme","full_name":"Grimme, C"}],"date_created":"2023-08-04T15:03:17Z","author":[{"last_name":"Tierney","full_name":"Tierney, K","first_name":"K"},{"full_name":"Handali, J","last_name":"Handali","first_name":"J"},{"first_name":"C","last_name":"Grimme","full_name":"Grimme, C"},{"first_name":"Heike","full_name":"Trautmann, Heike","id":"100740","orcid":"0000-0002-9788-8282","last_name":"Trautmann"}],"date_updated":"2023-10-16T13:35:41Z","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-54157-0_42","title":"Multi-objective Optimization for Liner Shipping Fleet Repositioning","publication_identifier":{"isbn":["978-3-319-54157-0"]},"citation":{"ama":"Tierney K, Handali J, Grimme C, Trautmann H. Multi-objective Optimization for Liner Shipping Fleet Repositioning. In: Trautmann H, Rudolph G, Klamroth K, et al., eds. <i>Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings</i>. Springer International Publishing; 2017:622–638. doi:<a href=\"https://doi.org/10.1007/978-3-319-54157-0_42\">10.1007/978-3-319-54157-0_42</a>","chicago":"Tierney, K, J Handali, C Grimme, and Heike Trautmann. “Multi-Objective Optimization for Liner Shipping Fleet Repositioning.” In <i>Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings</i>, edited by H Trautmann, G Rudolph, K Klamroth, O Schütze, M Wiecek, Y Jin, and C Grimme, 622–638. Cham: Springer International Publishing, 2017. <a href=\"https://doi.org/10.1007/978-3-319-54157-0_42\">https://doi.org/10.1007/978-3-319-54157-0_42</a>.","ieee":"K. Tierney, J. Handali, C. Grimme, and H. Trautmann, “Multi-objective Optimization for Liner Shipping Fleet Repositioning,” in <i>Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings</i>, H. Trautmann, G. Rudolph, K. Klamroth, O. Schütze, M. Wiecek, Y. Jin, and C. Grimme, Eds. Cham: Springer International Publishing, 2017, pp. 622–638.","bibtex":"@inbook{Tierney_Handali_Grimme_Trautmann_2017, place={Cham}, title={Multi-objective Optimization for Liner Shipping Fleet Repositioning}, DOI={<a href=\"https://doi.org/10.1007/978-3-319-54157-0_42\">10.1007/978-3-319-54157-0_42</a>}, booktitle={Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings}, publisher={Springer International Publishing}, author={Tierney, K and Handali, J and Grimme, C and Trautmann, Heike}, editor={Trautmann, H and Rudolph, G and Klamroth, K and Schütze, O and Wiecek, M and Jin, Y and Grimme, C}, year={2017}, pages={622–638} }","mla":"Tierney, K., et al. “Multi-Objective Optimization for Liner Shipping Fleet Repositioning.” <i>Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings</i>, edited by H Trautmann et al., Springer International Publishing, 2017, pp. 622–638, doi:<a href=\"https://doi.org/10.1007/978-3-319-54157-0_42\">10.1007/978-3-319-54157-0_42</a>.","short":"K. Tierney, J. Handali, C. Grimme, H. Trautmann, in: H. Trautmann, G. Rudolph, K. Klamroth, O. Schütze, M. Wiecek, Y. Jin, C. Grimme (Eds.), Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings, Springer International Publishing, Cham, 2017, pp. 622–638.","apa":"Tierney, K., Handali, J., Grimme, C., &#38; Trautmann, H. (2017). Multi-objective Optimization for Liner Shipping Fleet Repositioning. In H. Trautmann, G. Rudolph, K. Klamroth, O. Schütze, M. Wiecek, Y. Jin, &#38; C. Grimme (Eds.), <i>Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings</i> (pp. 622–638). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-319-54157-0_42\">https://doi.org/10.1007/978-3-319-54157-0_42</a>"},"page":"622–638","year":"2017","place":"Cham"},{"language":[{"iso":"eng"}],"_id":"46359","user_id":"15504","department":[{"_id":"34"},{"_id":"819"}],"abstract":[{"text":"This paper proposes a new stream clustering algorithm for text streams. The algorithm combines concepts from stream clustering and text analysis in order to incrementally maintain a number of text droplets that represent topics within the stream. Our algorithm adapts to changes of topic over time and can handle noise and outliers gracefully by decaying the importance of irrelevant clusters. We demonstrate the performance of our approach by using more than one million real-world texts from the video streaming platform Twitch.tv.","lang":"eng"}],"editor":[{"first_name":"Sergio","full_name":"de Cesare, Sergio","last_name":"de Cesare"},{"last_name":"Ulrich","full_name":"Ulrich, Frank","first_name":"Frank"}],"status":"public","type":"conference","publication":"Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17)","title":"Stream Clustering of Chat Messages with Applications to Twitch Streams","doi":"10.1007/978-3-319-70625-2_8","publisher":"Springer International Publishing","date_updated":"2023-10-16T13:36:23Z","date_created":"2023-08-04T15:04:57Z","author":[{"first_name":"Matthias","full_name":"Carnein, Matthias","last_name":"Carnein"},{"first_name":"Dennis","full_name":"Assenmacher, Dennis","last_name":"Assenmacher"},{"full_name":"Trautmann, Heike","id":"100740","last_name":"Trautmann","orcid":"0000-0002-9788-8282","first_name":"Heike"}],"year":"2017","place":"Valencia, Spain","citation":{"apa":"Carnein, M., Assenmacher, D., &#38; Trautmann, H. (2017). Stream Clustering of Chat Messages with Applications to Twitch Streams. In S. de Cesare &#38; F. Ulrich (Eds.), <i>Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17)</i> (pp. 79–88). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-319-70625-2_8\">https://doi.org/10.1007/978-3-319-70625-2_8</a>","mla":"Carnein, Matthias, et al. “Stream Clustering of Chat Messages with Applications to Twitch Streams.” <i>Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17)</i>, edited by Sergio de Cesare and Frank Ulrich, Springer International Publishing, 2017, pp. 79–88, doi:<a href=\"https://doi.org/10.1007/978-3-319-70625-2_8\">10.1007/978-3-319-70625-2_8</a>.","short":"M. Carnein, D. Assenmacher, H. Trautmann, in: S. de Cesare, F. Ulrich (Eds.), Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17), Springer International Publishing, Valencia, Spain, 2017, pp. 79–88.","bibtex":"@inproceedings{Carnein_Assenmacher_Trautmann_2017, place={Valencia, Spain}, title={Stream Clustering of Chat Messages with Applications to Twitch Streams}, DOI={<a href=\"https://doi.org/10.1007/978-3-319-70625-2_8\">10.1007/978-3-319-70625-2_8</a>}, booktitle={Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17)}, publisher={Springer International Publishing}, author={Carnein, Matthias and Assenmacher, Dennis and Trautmann, Heike}, editor={de Cesare, Sergio and Ulrich, Frank}, year={2017}, pages={79–88} }","chicago":"Carnein, Matthias, Dennis Assenmacher, and Heike Trautmann. “Stream Clustering of Chat Messages with Applications to Twitch Streams.” In <i>Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17)</i>, edited by Sergio de Cesare and Frank Ulrich, 79–88. Valencia, Spain: Springer International Publishing, 2017. <a href=\"https://doi.org/10.1007/978-3-319-70625-2_8\">https://doi.org/10.1007/978-3-319-70625-2_8</a>.","ieee":"M. Carnein, D. Assenmacher, and H. Trautmann, “Stream Clustering of Chat Messages with Applications to Twitch Streams,” in <i>Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17)</i>, 2017, pp. 79–88, doi: <a href=\"https://doi.org/10.1007/978-3-319-70625-2_8\">10.1007/978-3-319-70625-2_8</a>.","ama":"Carnein M, Assenmacher D, Trautmann H. Stream Clustering of Chat Messages with Applications to Twitch Streams. In: de Cesare S, Ulrich F, eds. <i>Proceedings of the 36$^th$ International Conference on Conceptual Modeling (ER’17)</i>. Springer International Publishing; 2017:79–88. doi:<a href=\"https://doi.org/10.1007/978-3-319-70625-2_8\">10.1007/978-3-319-70625-2_8</a>"},"page":"79–88","publication_identifier":{"isbn":["978-3-319-70625-2"]}},{"language":[{"iso":"eng"}],"_id":"46362","department":[{"_id":"34"},{"_id":"819"}],"user_id":"15504","abstract":[{"text":"Social bots are currently regarded an influential but also somewhat mysterious factor in public discourse and opinion making. They are considered to be capable of massively distributing propaganda in social and online media, and their application is even suspected to be partly responsible for recent election results. Astonishingly, the term social bot is not well defined and different scientific disciplines use divergent definitions. This work starts with a balanced definition attempt, before providing an overview of how social bots actually work (taking the example of Twitter) and what their current technical limitations are. Despite recent research progress in Deep Learning and Big Data, there are many activities bots cannot handle well. We then discuss how bot capabilities can be extended and controlled by integrating humans into the process and reason that this is currently the most promising way to realize meaningful interactions with other humans. This finally leads to the conclusion that hybridization is a challenge for current detection mechanisms and has to be handled with more sophisticated approaches to identify political propaganda distributed with social bots.","lang":"eng"}],"status":"public","publication":"Big Data","type":"journal_article","title":"Social Bots: Human-Like by Means of Human Control?","doi":"10.1089/big.2017.0044","date_updated":"2023-10-16T13:37:14Z","volume":5,"date_created":"2023-08-04T15:07:56Z","author":[{"first_name":"C","full_name":"Grimme, C","last_name":"Grimme"},{"first_name":"M","full_name":"Preuss, M","last_name":"Preuss"},{"first_name":"L","last_name":"Adam","full_name":"Adam, L"},{"first_name":"Heike","last_name":"Trautmann","orcid":"0000-0002-9788-8282","full_name":"Trautmann, Heike","id":"100740"}],"year":"2017","page":"279–293","intvolume":"         5","citation":{"mla":"Grimme, C., et al. “Social Bots: Human-Like by Means of Human Control?” <i>Big Data</i>, vol. 5, no. 4, 2017, pp. 279–293, doi:<a href=\"https://doi.org/10.1089/big.2017.0044\">10.1089/big.2017.0044</a>.","bibtex":"@article{Grimme_Preuss_Adam_Trautmann_2017, title={Social Bots: Human-Like by Means of Human Control?}, volume={5}, DOI={<a href=\"https://doi.org/10.1089/big.2017.0044\">10.1089/big.2017.0044</a>}, number={4}, journal={Big Data}, author={Grimme, C and Preuss, M and Adam, L and Trautmann, Heike}, year={2017}, pages={279–293} }","short":"C. Grimme, M. Preuss, L. Adam, H. Trautmann, Big Data 5 (2017) 279–293.","apa":"Grimme, C., Preuss, M., Adam, L., &#38; Trautmann, H. (2017). Social Bots: Human-Like by Means of Human Control? <i>Big Data</i>, <i>5</i>(4), 279–293. <a href=\"https://doi.org/10.1089/big.2017.0044\">https://doi.org/10.1089/big.2017.0044</a>","ama":"Grimme C, Preuss M, Adam L, Trautmann H. Social Bots: Human-Like by Means of Human Control? <i>Big Data</i>. 2017;5(4):279–293. doi:<a href=\"https://doi.org/10.1089/big.2017.0044\">10.1089/big.2017.0044</a>","chicago":"Grimme, C, M Preuss, L Adam, and Heike Trautmann. “Social Bots: Human-Like by Means of Human Control?” <i>Big Data</i> 5, no. 4 (2017): 279–293. <a href=\"https://doi.org/10.1089/big.2017.0044\">https://doi.org/10.1089/big.2017.0044</a>.","ieee":"C. Grimme, M. Preuss, L. Adam, and H. Trautmann, “Social Bots: Human-Like by Means of Human Control?,” <i>Big Data</i>, vol. 5, no. 4, pp. 279–293, 2017, doi: <a href=\"https://doi.org/10.1089/big.2017.0044\">10.1089/big.2017.0044</a>."},"issue":"4"},{"abstract":[{"lang":"eng","text":"Analysing streaming data has received considerable attention over the recent years. A key research area in this field is stream clustering which aims to recognize patterns in a possibly unbounded data stream of varying speed and structure. Over the past decades a multitude of new stream clustering algorithms have been proposed. However, to the best of our knowledge, no rigorous analysis and comparison of the different approaches has been performed. Our paper fills this gap and provides extensive experiments for a total of ten popular algorithms. We utilize a number of standard data sets of both, real and synthetic data and identify key weaknesses and strengths of the existing algorithms."}],"status":"public","type":"conference","publication":"Proceedings of the ACM International Conference on Computing Frontiers (CF ’17)","language":[{"iso":"eng"}],"_id":"46358","user_id":"15504","department":[{"_id":"34"},{"_id":"819"}],"year":"2017","place":"Siena, Italy","citation":{"ama":"Carnein M, Assenmacher D, Trautmann H. An Empirical Comparison of Stream Clustering Algorithms. In: <i>Proceedings of the ACM International Conference on Computing Frontiers (CF ’17)</i>. ; 2017:361–365. doi:<a href=\"https://doi.org/10.1145/3075564.3078887\">10.1145/3075564.3078887</a>","ieee":"M. Carnein, D. Assenmacher, and H. Trautmann, “An Empirical Comparison of Stream Clustering Algorithms,” in <i>Proceedings of the ACM International Conference on Computing Frontiers (CF ’17)</i>, 2017, pp. 361–365, doi: <a href=\"https://doi.org/10.1145/3075564.3078887\">10.1145/3075564.3078887</a>.","chicago":"Carnein, Matthias, Dennis Assenmacher, and Heike Trautmann. “An Empirical Comparison of Stream Clustering Algorithms.” In <i>Proceedings of the ACM International Conference on Computing Frontiers (CF ’17)</i>, 361–365. Siena, Italy, 2017. <a href=\"https://doi.org/10.1145/3075564.3078887\">https://doi.org/10.1145/3075564.3078887</a>.","apa":"Carnein, M., Assenmacher, D., &#38; Trautmann, H. (2017). An Empirical Comparison of Stream Clustering Algorithms. <i>Proceedings of the ACM International Conference on Computing Frontiers (CF ’17)</i>, 361–365. <a href=\"https://doi.org/10.1145/3075564.3078887\">https://doi.org/10.1145/3075564.3078887</a>","bibtex":"@inproceedings{Carnein_Assenmacher_Trautmann_2017, place={Siena, Italy}, title={An Empirical Comparison of Stream Clustering Algorithms}, DOI={<a href=\"https://doi.org/10.1145/3075564.3078887\">10.1145/3075564.3078887</a>}, booktitle={Proceedings of the ACM International Conference on Computing Frontiers (CF ’17)}, author={Carnein, Matthias and Assenmacher, Dennis and Trautmann, Heike}, year={2017}, pages={361–365} }","mla":"Carnein, Matthias, et al. “An Empirical Comparison of Stream Clustering Algorithms.” <i>Proceedings of the ACM International Conference on Computing Frontiers (CF ’17)</i>, 2017, pp. 361–365, doi:<a href=\"https://doi.org/10.1145/3075564.3078887\">10.1145/3075564.3078887</a>.","short":"M. Carnein, D. Assenmacher, H. Trautmann, in: Proceedings of the ACM International Conference on Computing Frontiers (CF ’17), Siena, Italy, 2017, pp. 361–365."},"page":"361–365","publication_identifier":{"isbn":["978-1-4503-4487-6/17/05"]},"title":"An Empirical Comparison of Stream Clustering Algorithms","doi":"10.1145/3075564.3078887","date_updated":"2023-10-16T13:35:59Z","date_created":"2023-08-04T15:04:09Z","author":[{"full_name":"Carnein, Matthias","last_name":"Carnein","first_name":"Matthias"},{"full_name":"Assenmacher, Dennis","last_name":"Assenmacher","first_name":"Dennis"},{"first_name":"Heike","last_name":"Trautmann","orcid":"0000-0002-9788-8282","id":"100740","full_name":"Trautmann, Heike"}]},{"keyword":["evolutionary optimization","software-tools"],"language":[{"iso":"eng"}],"extern":"1","_id":"48863","department":[{"_id":"819"}],"series_title":"GECCO ’17","user_id":"102979","abstract":[{"lang":"eng","text":"The novel R package ecr (version 2), short for Evolutionary Computation in R, provides a comprehensive collection of building blocks for constructing powerful evolutionary algorithms for single- and multi-objective continuous and combinatorial optimization problems. It allows to solve standard optimization tasks with few lines of code using a black-box approach. Moreover, rapid prototyping of non-standard ideas is possible via an explicit, white-box approach. This paper describes the design principles of the package and gives some introductory examples on how to use the package in practise."}],"status":"public","publication":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","type":"conference","title":"Ecr 2.0: A Modular Framework for Evolutionary Computation in R","doi":"10.1145/3067695.3082470","date_updated":"2023-12-13T10:45:05Z","publisher":"Association for Computing Machinery","date_created":"2023-11-14T15:58:55Z","author":[{"last_name":"Bossek","orcid":"0000-0002-4121-4668","id":"102979","full_name":"Bossek, Jakob","first_name":"Jakob"}],"year":"2017","place":"New York, NY, USA","page":"1187–1193","citation":{"short":"J. Bossek, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2017, pp. 1187–1193.","bibtex":"@inproceedings{Bossek_2017, place={New York, NY, USA}, series={GECCO ’17}, title={Ecr 2.0: A Modular Framework for Evolutionary Computation in R}, DOI={<a href=\"https://doi.org/10.1145/3067695.3082470\">10.1145/3067695.3082470</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion}, publisher={Association for Computing Machinery}, author={Bossek, Jakob}, year={2017}, pages={1187–1193}, collection={GECCO ’17} }","mla":"Bossek, Jakob. “Ecr 2.0: A Modular Framework for Evolutionary Computation in R.” <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, Association for Computing Machinery, 2017, pp. 1187–1193, doi:<a href=\"https://doi.org/10.1145/3067695.3082470\">10.1145/3067695.3082470</a>.","apa":"Bossek, J. (2017). Ecr 2.0: A Modular Framework for Evolutionary Computation in R. <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 1187–1193. <a href=\"https://doi.org/10.1145/3067695.3082470\">https://doi.org/10.1145/3067695.3082470</a>","ama":"Bossek J. Ecr 2.0: A Modular Framework for Evolutionary Computation in R. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>. GECCO ’17. Association for Computing Machinery; 2017:1187–1193. doi:<a href=\"https://doi.org/10.1145/3067695.3082470\">10.1145/3067695.3082470</a>","chicago":"Bossek, Jakob. “Ecr 2.0: A Modular Framework for Evolutionary Computation in R.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 1187–1193. GECCO ’17. New York, NY, USA: Association for Computing Machinery, 2017. <a href=\"https://doi.org/10.1145/3067695.3082470\">https://doi.org/10.1145/3067695.3082470</a>.","ieee":"J. Bossek, “Ecr 2.0: A Modular Framework for Evolutionary Computation in R,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 2017, pp. 1187–1193, doi: <a href=\"https://doi.org/10.1145/3067695.3082470\">10.1145/3067695.3082470</a>."},"publication_identifier":{"isbn":["978-1-4503-4939-0"]},"publication_status":"published"},{"publication_status":"published","year":"2017","page":"1–8","citation":{"apa":"Bossek, J., &#38; Grimme, C. (2017). A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem. <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>, 1–8. <a href=\"https://doi.org/10.1109/SSCI.2017.8285183\">https://doi.org/10.1109/SSCI.2017.8285183</a>","short":"J. Bossek, C. Grimme, in: 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017, pp. 1–8.","bibtex":"@inproceedings{Bossek_Grimme_2017, title={A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem}, DOI={<a href=\"https://doi.org/10.1109/SSCI.2017.8285183\">10.1109/SSCI.2017.8285183</a>}, booktitle={2017 IEEE Symposium Series on Computational Intelligence (SSCI)}, author={Bossek, Jakob and Grimme, Christian}, year={2017}, pages={1–8} }","mla":"Bossek, Jakob, and Christian Grimme. “A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem.” <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>, 2017, pp. 1–8, doi:<a href=\"https://doi.org/10.1109/SSCI.2017.8285183\">10.1109/SSCI.2017.8285183</a>.","chicago":"Bossek, Jakob, and Christian Grimme. “A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem.” In <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>, 1–8, 2017. <a href=\"https://doi.org/10.1109/SSCI.2017.8285183\">https://doi.org/10.1109/SSCI.2017.8285183</a>.","ieee":"J. Bossek and C. Grimme, “A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem,” in <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>, 2017, pp. 1–8, doi: <a href=\"https://doi.org/10.1109/SSCI.2017.8285183\">10.1109/SSCI.2017.8285183</a>.","ama":"Bossek J, Grimme C. A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem. In: <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>. ; 2017:1–8. doi:<a href=\"https://doi.org/10.1109/SSCI.2017.8285183\">10.1109/SSCI.2017.8285183</a>"},"date_updated":"2023-12-13T10:44:28Z","author":[{"first_name":"Jakob","orcid":"0000-0002-4121-4668","last_name":"Bossek","full_name":"Bossek, Jakob","id":"102979"},{"first_name":"Christian","full_name":"Grimme, Christian","last_name":"Grimme"}],"date_created":"2023-11-14T15:58:54Z","title":"A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem","doi":"10.1109/SSCI.2017.8285183","publication":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","type":"conference","abstract":[{"lang":"eng","text":"While finding minimum-cost spanning trees (MST) in undirected graphs is solvable in polynomial time, the multi-criteria minimum spanning tree problem (mcMST) is NP-hard. Interestingly, the mcMST problem has not been in focus of evolutionary computation research for a long period of time, although, its relevance for real world problems is easy to see. The available and most notable approaches by Zhou and Gen as well as by Knowles and Corne concentrate on solution encoding and on fairly dated selection mechanisms. In this work, we revisit the mcMST and focus on the mutation operators as exploratory components of evolutionary algorithms neglected so far. We investigate optimal solution characteristics to discuss current mutation strategies, identify shortcomings of these operators, and propose a sub-tree based operator which offers what we term Pareto-beneficial behavior: ensuring convergence and diversity at the same time. The operator is empirically evaluated inside modern standard evolutionary meta-heuristics for multi-criteria optimization and compared to hitherto applied mutation operators in the context of mcMST."}],"status":"public","_id":"48857","department":[{"_id":"819"}],"user_id":"102979","keyword":["Convergence","Encoding","Euclidean distance","Evolutionary computation","Heating systems","Optimization","Standards"],"extern":"1","language":[{"iso":"eng"}]},{"date_created":"2023-11-14T15:58:54Z","author":[{"first_name":"Jakob","orcid":"0000-0002-4121-4668","last_name":"Bossek","id":"102979","full_name":"Bossek, Jakob"},{"first_name":"Christian","full_name":"Grimme, Christian","last_name":"Grimme"}],"date_updated":"2023-12-13T10:44:36Z","doi":"10.1109/SSCI.2017.8285224","title":"An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling","publication_status":"published","citation":{"apa":"Bossek, J., &#38; Grimme, C. (2017). An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling. <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>, 1–8. <a href=\"https://doi.org/10.1109/SSCI.2017.8285224\">https://doi.org/10.1109/SSCI.2017.8285224</a>","mla":"Bossek, Jakob, and Christian Grimme. “An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling.” <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>, 2017, pp. 1–8, doi:<a href=\"https://doi.org/10.1109/SSCI.2017.8285224\">10.1109/SSCI.2017.8285224</a>.","bibtex":"@inproceedings{Bossek_Grimme_2017, title={An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling}, DOI={<a href=\"https://doi.org/10.1109/SSCI.2017.8285224\">10.1109/SSCI.2017.8285224</a>}, booktitle={2017 IEEE Symposium Series on Computational Intelligence (SSCI)}, author={Bossek, Jakob and Grimme, Christian}, year={2017}, pages={1–8} }","short":"J. Bossek, C. Grimme, in: 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017, pp. 1–8.","ama":"Bossek J, Grimme C. An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling. In: <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>. ; 2017:1–8. doi:<a href=\"https://doi.org/10.1109/SSCI.2017.8285224\">10.1109/SSCI.2017.8285224</a>","ieee":"J. Bossek and C. Grimme, “An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling,” in <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>, 2017, pp. 1–8, doi: <a href=\"https://doi.org/10.1109/SSCI.2017.8285224\">10.1109/SSCI.2017.8285224</a>.","chicago":"Bossek, Jakob, and Christian Grimme. “An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling.” In <i>2017 IEEE Symposium Series on Computational Intelligence (SSCI)</i>, 1–8, 2017. <a href=\"https://doi.org/10.1109/SSCI.2017.8285224\">https://doi.org/10.1109/SSCI.2017.8285224</a>."},"page":"1–8","year":"2017","user_id":"102979","department":[{"_id":"819"}],"_id":"48856","language":[{"iso":"eng"}],"extern":"1","keyword":["Evolutionary computation","Processor scheduling","Schedules","Scheduling","Sociology","Standards","Statistics"],"type":"conference","publication":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","status":"public","abstract":[{"text":"There exist many optimal or heuristic priority rules for machine scheduling problems, which can easily be integrated into single-objective evolutionary algorithms via mutation operators. However, in the multi-objective case, simultaneously applying different priorities for different objectives may cause severe disruptions in the genome and may lead to inferior solutions. In this paper, we combine an existing mutation operator concept with new insights from detailed observation of the structure of solutions for multi-objective machine scheduling problems. This allows the comprehensive integration of priority rules to produce better Pareto-front approximations. We evaluate the extended operator concept compared to standard swap mutation and the stand-alone components of our hybrid scheme, which performs best in all evaluated cases.","lang":"eng"}]},{"date_updated":"2023-12-13T10:52:04Z","volume":2,"author":[{"last_name":"Bossek","orcid":"0000-0002-4121-4668","id":"102979","full_name":"Bossek, Jakob","first_name":"Jakob"}],"date_created":"2023-11-14T15:58:55Z","title":"mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem","doi":"10.21105/joss.00374","publication_identifier":{"issn":["2475-9066"]},"issue":"17","year":"2017","page":"374","intvolume":"         2","citation":{"apa":"Bossek, J. (2017). mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem. <i>Journal of Open Source Software</i>, <i>2</i>(17), 374. <a href=\"https://doi.org/10.21105/joss.00374\">https://doi.org/10.21105/joss.00374</a>","bibtex":"@article{Bossek_2017, title={mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem}, volume={2}, DOI={<a href=\"https://doi.org/10.21105/joss.00374\">10.21105/joss.00374</a>}, number={17}, journal={Journal of Open Source Software}, author={Bossek, Jakob}, year={2017}, pages={374} }","short":"J. Bossek, Journal of Open Source Software 2 (2017) 374.","mla":"Bossek, Jakob. “McMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem.” <i>Journal of Open Source Software</i>, vol. 2, no. 17, 2017, p. 374, doi:<a href=\"https://doi.org/10.21105/joss.00374\">10.21105/joss.00374</a>.","ama":"Bossek J. mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem. <i>Journal of Open Source Software</i>. 2017;2(17):374. doi:<a href=\"https://doi.org/10.21105/joss.00374\">10.21105/joss.00374</a>","ieee":"J. Bossek, “mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem,” <i>Journal of Open Source Software</i>, vol. 2, no. 17, p. 374, 2017, doi: <a href=\"https://doi.org/10.21105/joss.00374\">10.21105/joss.00374</a>.","chicago":"Bossek, Jakob. “McMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem.” <i>Journal of Open Source Software</i> 2, no. 17 (2017): 374. <a href=\"https://doi.org/10.21105/joss.00374\">https://doi.org/10.21105/joss.00374</a>."},"_id":"48864","department":[{"_id":"819"}],"user_id":"102979","language":[{"iso":"eng"}],"publication":"Journal of Open Source Software","type":"journal_article","abstract":[{"text":"Bossek, (2017), mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem, Journal of Open Source Software, 2(17), 374, doi:10.21105/joss.00374","lang":"eng"}],"status":"public"},{"issue":"1","publication_identifier":{"issn":["2073-4859"]},"page":"103–113","intvolume":"         9","citation":{"apa":"Bossek, J. (2017). Smoof: Single- and Multi-Objective Optimization Test Functions. <i>The R Journal</i>, <i>9</i>(1), 103–113.","mla":"Bossek, Jakob. “Smoof: Single- and Multi-Objective Optimization Test Functions.” <i>The R Journal</i>, vol. 9, no. 1, 2017, pp. 103–113.","short":"J. Bossek, The R Journal 9 (2017) 103–113.","bibtex":"@article{Bossek_2017, title={Smoof: Single- and Multi-Objective Optimization Test Functions}, volume={9}, number={1}, journal={The R Journal}, author={Bossek, Jakob}, year={2017}, pages={103–113} }","chicago":"Bossek, Jakob. “Smoof: Single- and Multi-Objective Optimization Test Functions.” <i>The R Journal</i> 9, no. 1 (2017): 103–113.","ieee":"J. Bossek, “Smoof: Single- and Multi-Objective Optimization Test Functions,” <i>The R Journal</i>, vol. 9, no. 1, pp. 103–113, 2017.","ama":"Bossek J. Smoof: Single- and Multi-Objective Optimization Test Functions. <i>The R Journal</i>. 2017;9(1):103–113."},"year":"2017","volume":9,"date_created":"2023-11-14T15:58:56Z","author":[{"first_name":"Jakob","id":"102979","full_name":"Bossek, Jakob","orcid":"0000-0002-4121-4668","last_name":"Bossek"}],"date_updated":"2023-12-13T10:51:57Z","title":"Smoof: Single- and Multi-Objective Optimization Test Functions","publication":"The R Journal","type":"journal_article","status":"public","department":[{"_id":"819"}],"user_id":"102979","_id":"48865","language":[{"iso":"eng"}]},{"author":[{"first_name":"Bernd","last_name":"Bischl","full_name":"Bischl, Bernd"},{"full_name":"Richter, Jakob","last_name":"Richter","first_name":"Jakob"},{"first_name":"Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","id":"102979","full_name":"Bossek, Jakob"},{"full_name":"Horn, Daniel","last_name":"Horn","first_name":"Daniel"},{"first_name":"Janek","full_name":"Thomas, Janek","last_name":"Thomas"},{"last_name":"Lang","full_name":"Lang, Michel","first_name":"Michel"}],"date_created":"2023-11-14T15:58:51Z","date_updated":"2023-12-13T10:52:31Z","title":"mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions","citation":{"ama":"Bischl B, Richter J, Bossek J, Horn D, Thomas J, Lang M. mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions. <i>CoRR</i>. Published online 2017.","chicago":"Bischl, Bernd, Jakob Richter, Jakob Bossek, Daniel Horn, Janek Thomas, and Michel Lang. “MlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions.” <i>CoRR</i>, 2017.","ieee":"B. Bischl, J. Richter, J. Bossek, D. Horn, J. Thomas, and M. Lang, “mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions,” <i>CoRR</i>, 2017.","apa":"Bischl, B., Richter, J., Bossek, J., Horn, D., Thomas, J., &#38; Lang, M. (2017). mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions. <i>CoRR</i>.","bibtex":"@article{Bischl_Richter_Bossek_Horn_Thomas_Lang_2017, title={mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions}, journal={CoRR}, author={Bischl, Bernd and Richter, Jakob and Bossek, Jakob and Horn, Daniel and Thomas, Janek and Lang, Michel}, year={2017} }","short":"B. Bischl, J. Richter, J. Bossek, D. Horn, J. Thomas, M. Lang, CoRR (2017).","mla":"Bischl, Bernd, et al. “MlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions.” <i>CoRR</i>, 2017."},"year":"2017","user_id":"102979","department":[{"_id":"819"}],"_id":"48837","language":[{"iso":"eng"}],"type":"journal_article","publication":"CoRR","status":"public"},{"language":[{"iso":"eng"}],"publication":"LION 2016: Learning and Intelligent Optimization","abstract":[{"lang":"eng","text":"Automated algorithm configuration procedures play an increasingly important role in the development and application of algorithms for a wide range of computationally challenging problems. Until very recently, these configuration procedures were limited to optimising a single performance objective, such as the running time or solution quality achieved by the algorithm being configured. However, in many applications there is more than one performance objective of interest. This gives rise to the multi-objective automatic algorithm configuration problem, which involves finding a Pareto set of configurations of a given target algorithm that characterises trade-offs between multiple performance objectives. In this work, we introduce MO-ParamILS, a multi-objective extension of the state-of-the-art single-objective algorithm configuration framework ParamILS, and demonstrate that it produces good results on several challenging bi-objective algorithm configuration scenarios compared to a base-line obtained from using a state-of-the-art single-objective algorithm configurator."}],"publisher":"Springer International Publishing","date_created":"2023-08-04T15:10:09Z","title":"MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework","year":"2016","_id":"46364","user_id":"15504","series_title":"LNTCS","department":[{"_id":"34"},{"_id":"819"}],"type":"conference","editor":[{"last_name":"et al. Joaquin","full_name":"et al. Joaquin, Vanschooren","first_name":"Vanschooren"}],"status":"public","date_updated":"2023-10-16T13:37:50Z","author":[{"full_name":"Blot, A","last_name":"Blot","first_name":"A"},{"full_name":"Hoos, H","last_name":"Hoos","first_name":"H"},{"first_name":"L","full_name":"Jourdan, L","last_name":"Jourdan"},{"first_name":"M","last_name":"Marmion","full_name":"Marmion, M"},{"id":"100740","full_name":"Trautmann, Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","first_name":"Heike"}],"volume":10079,"doi":"10.1007/978-3-319-50349-3_3","place":"Cham","citation":{"ama":"Blot A, Hoos H, Jourdan L, Marmion M, Trautmann H. MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework. In: et al. Joaquin V, ed. <i>LION 2016: Learning and Intelligent Optimization</i>. Vol 10079. LNTCS. Springer International Publishing; 2016:32–47. doi:<a href=\"https://doi.org/10.1007/978-3-319-50349-3_3\">10.1007/978-3-319-50349-3_3</a>","chicago":"Blot, A, H Hoos, L Jourdan, M Marmion, and Heike Trautmann. “MO-ParamILS: A Multi-Objective Automatic Algorithm Configuration Framework.” In <i>LION 2016: Learning and Intelligent Optimization</i>, edited by Vanschooren et al. Joaquin, 10079:32–47. LNTCS. Cham: Springer International Publishing, 2016. <a href=\"https://doi.org/10.1007/978-3-319-50349-3_3\">https://doi.org/10.1007/978-3-319-50349-3_3</a>.","ieee":"A. Blot, H. Hoos, L. Jourdan, M. Marmion, and H. Trautmann, “MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework,” in <i>LION 2016: Learning and Intelligent Optimization</i>, 2016, vol. 10079, pp. 32–47, doi: <a href=\"https://doi.org/10.1007/978-3-319-50349-3_3\">10.1007/978-3-319-50349-3_3</a>.","apa":"Blot, A., Hoos, H., Jourdan, L., Marmion, M., &#38; Trautmann, H. (2016). MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework. In V. et al. Joaquin (Ed.), <i>LION 2016: Learning and Intelligent Optimization</i> (Vol. 10079, pp. 32–47). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-319-50349-3_3\">https://doi.org/10.1007/978-3-319-50349-3_3</a>","bibtex":"@inproceedings{Blot_Hoos_Jourdan_Marmion_Trautmann_2016, place={Cham}, series={LNTCS}, title={MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework}, volume={10079}, DOI={<a href=\"https://doi.org/10.1007/978-3-319-50349-3_3\">10.1007/978-3-319-50349-3_3</a>}, booktitle={LION 2016: Learning and Intelligent Optimization}, publisher={Springer International Publishing}, author={Blot, A and Hoos, H and Jourdan, L and Marmion, M and Trautmann, Heike}, editor={et al. Joaquin, Vanschooren}, year={2016}, pages={32–47}, collection={LNTCS} }","short":"A. Blot, H. Hoos, L. Jourdan, M. Marmion, H. Trautmann, in: V. et al. Joaquin (Ed.), LION 2016: Learning and Intelligent Optimization, Springer International Publishing, Cham, 2016, pp. 32–47.","mla":"Blot, A., et al. “MO-ParamILS: A Multi-Objective Automatic Algorithm Configuration Framework.” <i>LION 2016: Learning and Intelligent Optimization</i>, edited by Vanschooren et al. Joaquin, vol. 10079, Springer International Publishing, 2016, pp. 32–47, doi:<a href=\"https://doi.org/10.1007/978-3-319-50349-3_3\">10.1007/978-3-319-50349-3_3</a>."},"page":"32–47","intvolume":"     10079"},{"title":"On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front","doi":"10.1007/978-3-319-31153-1_4","publisher":"Springer International Publishing","date_updated":"2023-10-16T13:37:33Z","author":[{"first_name":"G","full_name":"Rudolph, G","last_name":"Rudolph"},{"full_name":"Schütze, O","last_name":"Schütze","first_name":"O"},{"id":"100740","full_name":"Trautmann, Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","first_name":"Heike"}],"date_created":"2023-08-04T15:09:14Z","place":"Cham","year":"2016","citation":{"chicago":"Rudolph, G, O Schütze, and Heike Trautmann. “On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front.” In <i>Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II</i>, edited by G Squillero and P Burelli, 42–55. Cham: Springer International Publishing, 2016. <a href=\"https://doi.org/10.1007/978-3-319-31153-1_4\">https://doi.org/10.1007/978-3-319-31153-1_4</a>.","ieee":"G. Rudolph, O. Schütze, and H. Trautmann, “On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front,” in <i>Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II</i>, G. Squillero and P. Burelli, Eds. Cham: Springer International Publishing, 2016, pp. 42–55.","ama":"Rudolph G, Schütze O, Trautmann H. On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front. In: Squillero G, Burelli P, eds. <i>Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II</i>. Springer International Publishing; 2016:42–55. doi:<a href=\"https://doi.org/10.1007/978-3-319-31153-1_4\">10.1007/978-3-319-31153-1_4</a>","short":"G. Rudolph, O. Schütze, H. Trautmann, in: G. Squillero, P. Burelli (Eds.), Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II, Springer International Publishing, Cham, 2016, pp. 42–55.","mla":"Rudolph, G., et al. “On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front.” <i>Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II</i>, edited by G Squillero and P Burelli, Springer International Publishing, 2016, pp. 42–55, doi:<a href=\"https://doi.org/10.1007/978-3-319-31153-1_4\">10.1007/978-3-319-31153-1_4</a>.","bibtex":"@inbook{Rudolph_Schütze_Trautmann_2016, place={Cham}, title={On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front}, DOI={<a href=\"https://doi.org/10.1007/978-3-319-31153-1_4\">10.1007/978-3-319-31153-1_4</a>}, booktitle={Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II}, publisher={Springer International Publishing}, author={Rudolph, G and Schütze, O and Trautmann, Heike}, editor={Squillero, G and Burelli, P}, year={2016}, pages={42–55} }","apa":"Rudolph, G., Schütze, O., &#38; Trautmann, H. (2016). On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front. In G. Squillero &#38; P. Burelli (Eds.), <i>Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II</i> (pp. 42–55). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-319-31153-1_4\">https://doi.org/10.1007/978-3-319-31153-1_4</a>"},"page":"42–55","publication_identifier":{"isbn":["978-3-319-31153-1"]},"language":[{"iso":"eng"}],"_id":"46363","user_id":"15504","department":[{"_id":"34"},{"_id":"819"}],"editor":[{"full_name":"Squillero, G","last_name":"Squillero","first_name":"G"},{"first_name":"P","full_name":"Burelli, P","last_name":"Burelli"}],"abstract":[{"text":"The averaged Hausdorff distance has been proposed as an indicator for assessing the quality of finitely sized approximations of the Pareto front of a multiobjective problem. Since many set-based, iterative optimization algorithms store their currently best approximation in an internal archive these approximations are also termed archives. In case of two objectives and continuous variables it is known that the best approximations in terms of averaged Hausdorff distance are subsets of the Pareto front if it is concave. If it is linear or circularly concave the points of the best approximation are equally spaced.\r\n\r\nHere, it is proven that the optimal averaged Hausdorff approximation and the Pareto front have an empty intersection if the Pareto front is circularly convex. But the points of the best approximation are equally spaced and they rapidly approach the Pareto front for increasing size of the approximation.","lang":"eng"}],"status":"public","type":"book_chapter","publication":"Applications of Evolutionary Computation: 19$^th$ European Conference, EvoApplications 2016, Porto, Portugal, March 30 — April 1, 2016, Proceedings, Part II"},{"publication":"Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV)","type":"conference","abstract":[{"lang":"eng","text":"This paper formally defines multimodality in multiobjective optimization (MO). We introduce a test-bed in which multimodal MO problems with known properties can be constructed as well as numerical characteristics of the resulting landscape. Gradient- and local search based strategies are compared on exemplary problems together with specific performance indicators in the multimodal MO setting. By this means the foundation for Exploratory Landscape Analysis in MO is provided."}],"status":"public","_id":"46369","department":[{"_id":"34"},{"_id":"819"}],"series_title":"Lecture Notes in Computer Science","user_id":"15504","language":[{"iso":"eng"}],"year":"2016","place":"Edinburgh, Scotland","page":"962–972","citation":{"bibtex":"@inproceedings{Kerschke_Wang_Preuss_Grimme_Deutz_Trautmann_Emmerich_2016, place={Edinburgh, Scotland}, series={Lecture Notes in Computer Science}, title={Towards Analyzing Multimodality of Multiobjective Landscapes}, DOI={<a href=\"https://doi.org/10.1007/978-3-319-45823-6_90\">10.1007/978-3-319-45823-6_90</a>}, booktitle={Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV)}, publisher={Springer}, author={Kerschke, Pascal and Wang, Hao and Preuss, Mike and Grimme, Christian and Deutz, André and Trautmann, Heike and Emmerich, Michael}, year={2016}, pages={962–972}, collection={Lecture Notes in Computer Science} }","short":"P. Kerschke, H. Wang, M. Preuss, C. Grimme, A. Deutz, H. Trautmann, M. Emmerich, in: Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV), Springer, Edinburgh, Scotland, 2016, pp. 962–972.","mla":"Kerschke, Pascal, et al. “Towards Analyzing Multimodality of Multiobjective Landscapes.” <i>Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV)</i>, Springer, 2016, pp. 962–972, doi:<a href=\"https://doi.org/10.1007/978-3-319-45823-6_90\">10.1007/978-3-319-45823-6_90</a>.","apa":"Kerschke, P., Wang, H., Preuss, M., Grimme, C., Deutz, A., Trautmann, H., &#38; Emmerich, M. (2016). Towards Analyzing Multimodality of Multiobjective Landscapes. <i>Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV)</i>, 962–972. <a href=\"https://doi.org/10.1007/978-3-319-45823-6_90\">https://doi.org/10.1007/978-3-319-45823-6_90</a>","ama":"Kerschke P, Wang H, Preuss M, et al. Towards Analyzing Multimodality of Multiobjective Landscapes. In: <i>Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV)</i>. Lecture Notes in Computer Science. Springer; 2016:962–972. doi:<a href=\"https://doi.org/10.1007/978-3-319-45823-6_90\">10.1007/978-3-319-45823-6_90</a>","ieee":"P. Kerschke <i>et al.</i>, “Towards Analyzing Multimodality of Multiobjective Landscapes,” in <i>Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV)</i>, 2016, pp. 962–972, doi: <a href=\"https://doi.org/10.1007/978-3-319-45823-6_90\">10.1007/978-3-319-45823-6_90</a>.","chicago":"Kerschke, Pascal, Hao Wang, Mike Preuss, Christian Grimme, André Deutz, Heike Trautmann, and Michael Emmerich. “Towards Analyzing Multimodality of Multiobjective Landscapes.” In <i>Proceedings of the 14$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XIV)</i>, 962–972. Lecture Notes in Computer Science. Edinburgh, Scotland: Springer, 2016. <a href=\"https://doi.org/10.1007/978-3-319-45823-6_90\">https://doi.org/10.1007/978-3-319-45823-6_90</a>."},"date_updated":"2023-10-16T13:39:42Z","publisher":"Springer","author":[{"first_name":"Pascal","last_name":"Kerschke","full_name":"Kerschke, Pascal"},{"first_name":"Hao","last_name":"Wang","full_name":"Wang, Hao"},{"full_name":"Preuss, Mike","last_name":"Preuss","first_name":"Mike"},{"first_name":"Christian","last_name":"Grimme","full_name":"Grimme, Christian"},{"last_name":"Deutz","full_name":"Deutz, André","first_name":"André"},{"last_name":"Trautmann","orcid":"0000-0002-9788-8282","id":"100740","full_name":"Trautmann, Heike","first_name":"Heike"},{"first_name":"Michael","last_name":"Emmerich","full_name":"Emmerich, Michael"}],"date_created":"2023-08-04T15:16:02Z","title":"Towards Analyzing Multimodality of Multiobjective Landscapes","doi":"10.1007/978-3-319-45823-6_90"},{"language":[{"iso":"eng"}],"department":[{"_id":"34"},{"_id":"819"}],"user_id":"15504","_id":"46367","status":"public","abstract":[{"text":"When selecting the best suited algorithm for an unknown optimization problem, it is useful to possess some a priori knowledge of the problem at hand. In the context of single-objective, continuous optimization problems such knowledge can be retrieved by means of Exploratory Landscape Analysis (ELA), which automatically identifies properties of a landscape, e.g., the so-called funnel structures, based on an initial sample. In this paper, we extract the relevant features (for detecting funnels) out of a large set of landscape features when only given a small initial sample consisting of 50 x D observations, where D is the number of decision space dimensions. This is already in the range of the start population sizes of many evolutionary algorithms. The new Multiple Peaks Model Generator (MPM2) is used for training the classifier, and the approach is then very successfully validated on the Black-Box Optimization Benchmark (BBOB) and a subset of the CEC 2013 niching competition problems.","lang":"eng"}],"publication":"Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation","type":"conference","doi":"10.1145/2908812.2908845","title":"Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models","author":[{"full_name":"Kerschke, Pascal","last_name":"Kerschke","first_name":"Pascal"},{"full_name":"Preuss, Mike","last_name":"Preuss","first_name":"Mike"},{"first_name":"Simon","full_name":"Wessing, Simon","last_name":"Wessing"},{"first_name":"Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","id":"100740","full_name":"Trautmann, Heike"}],"date_created":"2023-08-04T15:14:06Z","date_updated":"2023-10-16T13:38:47Z","page":"229–236","citation":{"apa":"Kerschke, P., Preuss, M., Wessing, S., &#38; Trautmann, H. (2016). Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models. <i>Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation</i>, 229–236. <a href=\"https://doi.org/10.1145/2908812.2908845\">https://doi.org/10.1145/2908812.2908845</a>","short":"P. Kerschke, M. Preuss, S. Wessing, H. Trautmann, in: Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation, Denver, CO, USA, 2016, pp. 229–236.","mla":"Kerschke, Pascal, et al. “Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models.” <i>Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation</i>, 2016, pp. 229–236, doi:<a href=\"https://doi.org/10.1145/2908812.2908845\">10.1145/2908812.2908845</a>.","bibtex":"@inproceedings{Kerschke_Preuss_Wessing_Trautmann_2016, place={Denver, CO, USA}, title={Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models}, DOI={<a href=\"https://doi.org/10.1145/2908812.2908845\">10.1145/2908812.2908845</a>}, booktitle={Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation}, author={Kerschke, Pascal and Preuss, Mike and Wessing, Simon and Trautmann, Heike}, year={2016}, pages={229–236} }","chicago":"Kerschke, Pascal, Mike Preuss, Simon Wessing, and Heike Trautmann. “Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models.” In <i>Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation</i>, 229–236. Denver, CO, USA, 2016. <a href=\"https://doi.org/10.1145/2908812.2908845\">https://doi.org/10.1145/2908812.2908845</a>.","ieee":"P. Kerschke, M. Preuss, S. Wessing, and H. Trautmann, “Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models,” in <i>Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation</i>, 2016, pp. 229–236, doi: <a href=\"https://doi.org/10.1145/2908812.2908845\">10.1145/2908812.2908845</a>.","ama":"Kerschke P, Preuss M, Wessing S, Trautmann H. Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models. In: <i>Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation</i>. ; 2016:229–236. doi:<a href=\"https://doi.org/10.1145/2908812.2908845\">10.1145/2908812.2908845</a>"},"year":"2016","place":"Denver, CO, USA","publication_identifier":{"isbn":["978-1-4503-4206-3"]}},{"issue":"2","page":"589–618","intvolume":"        64","citation":{"ama":"Rudolph G, Schütze O, Grimme C, Domínguez-Medina C, Trautmann H. Optimal averaged Hausdorff archives for bi-objective problems: theoretical and numerical results. <i>Computational Optimization and Applications (Comput Optim Appl)</i>. 2016;64(2):589–618. doi:<a href=\"https://doi.org/10.1007/s10589-015-9815-8\">10.1007/s10589-015-9815-8</a>","apa":"Rudolph, G., Schütze, O., Grimme, C., Domínguez-Medina, C., &#38; Trautmann, H. (2016). Optimal averaged Hausdorff archives for bi-objective problems: theoretical and numerical results. <i>Computational Optimization and Applications (Comput. Optim. Appl.)</i>, <i>64</i>(2), 589–618. <a href=\"https://doi.org/10.1007/s10589-015-9815-8\">https://doi.org/10.1007/s10589-015-9815-8</a>","bibtex":"@article{Rudolph_Schütze_Grimme_Domínguez-Medina_Trautmann_2016, title={Optimal averaged Hausdorff archives for bi-objective problems: theoretical and numerical results}, volume={64}, DOI={<a href=\"https://doi.org/10.1007/s10589-015-9815-8\">10.1007/s10589-015-9815-8</a>}, number={2}, journal={Computational Optimization and Applications (Comput. Optim. Appl.)}, author={Rudolph, G and Schütze, O and Grimme, C and Domínguez-Medina, C and Trautmann, Heike}, year={2016}, pages={589–618} }","mla":"Rudolph, G., et al. “Optimal Averaged Hausdorff Archives for Bi-Objective Problems: Theoretical and Numerical Results.” <i>Computational Optimization and Applications (Comput. Optim. Appl.)</i>, vol. 64, no. 2, 2016, pp. 589–618, doi:<a href=\"https://doi.org/10.1007/s10589-015-9815-8\">10.1007/s10589-015-9815-8</a>.","short":"G. Rudolph, O. Schütze, C. Grimme, C. Domínguez-Medina, H. Trautmann, Computational Optimization and Applications (Comput. Optim. Appl.) 64 (2016) 589–618.","chicago":"Rudolph, G, O Schütze, C Grimme, C Domínguez-Medina, and Heike Trautmann. “Optimal Averaged Hausdorff Archives for Bi-Objective Problems: Theoretical and Numerical Results.” <i>Computational Optimization and Applications (Comput. Optim. Appl.)</i> 64, no. 2 (2016): 589–618. <a href=\"https://doi.org/10.1007/s10589-015-9815-8\">https://doi.org/10.1007/s10589-015-9815-8</a>.","ieee":"G. Rudolph, O. Schütze, C. Grimme, C. Domínguez-Medina, and H. Trautmann, “Optimal averaged Hausdorff archives for bi-objective problems: theoretical and numerical results,” <i>Computational Optimization and Applications (Comput. Optim. Appl.)</i>, vol. 64, no. 2, pp. 589–618, 2016, doi: <a href=\"https://doi.org/10.1007/s10589-015-9815-8\">10.1007/s10589-015-9815-8</a>."},"year":"2016","volume":64,"author":[{"full_name":"Rudolph, G","last_name":"Rudolph","first_name":"G"},{"first_name":"O","full_name":"Schütze, O","last_name":"Schütze"},{"first_name":"C","full_name":"Grimme, C","last_name":"Grimme"},{"full_name":"Domínguez-Medina, C","last_name":"Domínguez-Medina","first_name":"C"},{"first_name":"Heike","id":"100740","full_name":"Trautmann, Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann"}],"date_created":"2023-08-04T15:17:48Z","date_updated":"2023-10-16T13:40:21Z","doi":"10.1007/s10589-015-9815-8","title":"Optimal averaged Hausdorff archives for bi-objective problems: theoretical and numerical results","publication":"Computational Optimization and Applications (Comput. Optim. Appl.)","type":"journal_article","status":"public","abstract":[{"lang":"eng","text":"One main task in evolutionary multiobjective optimization (EMO) is to obtain a suitable finite size approximation of the Pareto front which is the image of the solution set, termed the Pareto set, of a given multiobjective optimization problem. In the technical literature, the characteristic of the desired approximation is commonly expressed by closeness to the Pareto front and a sufficient spread of the solutions obtained. In this paper, we first make an effort to show by theoretical and empirical findings that the recently proposed Averaged Hausdorff (or Δ𝑝-) indicator indeed aims at fulfilling both performance criteria for bi-objective optimization problems. In the second part of this paper, standard EMO algorithms combined with a specialized archiver and a postprocessing step based on the Δ𝑝 indicator are introduced which sufficiently approximate the Δ𝑝-optimal archives and generate solutions evenly spread along the Pareto front."}],"department":[{"_id":"34"},{"_id":"819"}],"user_id":"15504","_id":"46371","language":[{"iso":"eng"}]},{"date_updated":"2023-10-16T13:40:43Z","volume":22,"author":[{"first_name":"O","last_name":"Schütze","full_name":"Schütze, O"},{"first_name":"Hernandez VA","last_name":"Sosa","full_name":"Sosa, Hernandez VA"},{"orcid":"0000-0002-9788-8282","last_name":"Trautmann","full_name":"Trautmann, Heike","id":"100740","first_name":"Heike"},{"first_name":"G","full_name":"Rudolph, G","last_name":"Rudolph"}],"date_created":"2023-08-04T15:19:11Z","title":"The Hypervolume based Directed Search Method for Multi-Objective Optimization Problems","doi":"10.1007/s10732-016-9310-0","issue":"3","year":"2016","page":"273–300","intvolume":"        22","citation":{"mla":"Schütze, O., et al. “The Hypervolume Based Directed Search Method for Multi-Objective Optimization Problems.” <i>Journal of Heuristics</i>, vol. 22, no. 3, 2016, pp. 273–300, doi:<a href=\"https://doi.org/10.1007/s10732-016-9310-0\">10.1007/s10732-016-9310-0</a>.","bibtex":"@article{Schütze_Sosa_Trautmann_Rudolph_2016, title={The Hypervolume based Directed Search Method for Multi-Objective Optimization Problems}, volume={22}, DOI={<a href=\"https://doi.org/10.1007/s10732-016-9310-0\">10.1007/s10732-016-9310-0</a>}, number={3}, journal={Journal of Heuristics}, author={Schütze, O and Sosa, Hernandez VA and Trautmann, Heike and Rudolph, G}, year={2016}, pages={273–300} }","short":"O. Schütze, H.V. Sosa, H. Trautmann, G. Rudolph, Journal of Heuristics 22 (2016) 273–300.","apa":"Schütze, O., Sosa, H. V., Trautmann, H., &#38; Rudolph, G. (2016). The Hypervolume based Directed Search Method for Multi-Objective Optimization Problems. <i>Journal of Heuristics</i>, <i>22</i>(3), 273–300. <a href=\"https://doi.org/10.1007/s10732-016-9310-0\">https://doi.org/10.1007/s10732-016-9310-0</a>","chicago":"Schütze, O, Hernandez VA Sosa, Heike Trautmann, and G Rudolph. “The Hypervolume Based Directed Search Method for Multi-Objective Optimization Problems.” <i>Journal of Heuristics</i> 22, no. 3 (2016): 273–300. <a href=\"https://doi.org/10.1007/s10732-016-9310-0\">https://doi.org/10.1007/s10732-016-9310-0</a>.","ieee":"O. Schütze, H. V. Sosa, H. Trautmann, and G. Rudolph, “The Hypervolume based Directed Search Method for Multi-Objective Optimization Problems,” <i>Journal of Heuristics</i>, vol. 22, no. 3, pp. 273–300, 2016, doi: <a href=\"https://doi.org/10.1007/s10732-016-9310-0\">10.1007/s10732-016-9310-0</a>.","ama":"Schütze O, Sosa HV, Trautmann H, Rudolph G. The Hypervolume based Directed Search Method for Multi-Objective Optimization Problems. <i>Journal of Heuristics</i>. 2016;22(3):273–300. doi:<a href=\"https://doi.org/10.1007/s10732-016-9310-0\">10.1007/s10732-016-9310-0</a>"},"_id":"46372","department":[{"_id":"34"},{"_id":"819"}],"user_id":"15504","language":[{"iso":"eng"}],"publication":"Journal of Heuristics","type":"journal_article","abstract":[{"text":"We present a new hybrid evolutionary algorithm for the effective hypervolume approximation of the Pareto front of a given differentiable multi-objective optimization problem. Starting point for the local search (LS) mechanism is a new division of the decision space as we will argue that in each of these regions a different LS strategy seems to be most promising. For the LS in two out of the three regions we will utilize and adapt the Directed Search method which is capable of steering the search into any direction given in objective space and which is thus well suited for the problem at hand. We further on integrate the resulting LS mechanism into SMS-EMOA, a state-of-the-art evolutionary algorithm for hypervolume approximations. Finally, we will present some numerical results on several benchmark problems with two and three objectives indicating the strength and competitiveness of the novel hybrid.","lang":"eng"}],"status":"public"},{"department":[{"_id":"34"},{"_id":"819"}],"user_id":"15504","_id":"46368","language":[{"iso":"eng"}],"publication":"Proceedings of the IEEE Congress on Evolutionary Computation (CEC)","type":"conference","status":"public","abstract":[{"text":"Exploratory Landscape Analysis (ELA) aims at understanding characteristics of single-objective continuous (black-box) optimization problems in an automated way. Moreover, the approach provides the basis for constructing algorithm selection models for unseen problem instances. Recently, it has gained increasing attention and numerical features have been designed by various research groups. This paper introduces the R-Package FLACCO which makes all relevant features available in a unified framework together with efficient helper functions. Moreover, a case study which gives perspectives to ELA for multi-objective optimization problems is presented.","lang":"eng"}],"date_created":"2023-08-04T15:14:52Z","author":[{"first_name":"Pascal","last_name":"Kerschke","full_name":"Kerschke, Pascal"},{"first_name":"Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","id":"100740","full_name":"Trautmann, Heike"}],"date_updated":"2023-10-16T13:39:06Z","doi":"10.1109/CEC.2016.7748359","title":"The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems","citation":{"ama":"Kerschke P, Trautmann H. The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems. In: <i>Proceedings of the IEEE Congress on Evolutionary Computation (CEC)</i>. ; 2016. doi:<a href=\"https://doi.org/10.1109/CEC.2016.7748359\">10.1109/CEC.2016.7748359</a>","ieee":"P. Kerschke and H. Trautmann, “The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems,” 2016, doi: <a href=\"https://doi.org/10.1109/CEC.2016.7748359\">10.1109/CEC.2016.7748359</a>.","chicago":"Kerschke, Pascal, and Heike Trautmann. “The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems.” In <i>Proceedings of the IEEE Congress on Evolutionary Computation (CEC)</i>. Vancouver, BC, Kanada, 2016. <a href=\"https://doi.org/10.1109/CEC.2016.7748359\">https://doi.org/10.1109/CEC.2016.7748359</a>.","apa":"Kerschke, P., &#38; Trautmann, H. (2016). The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems. <i>Proceedings of the IEEE Congress on Evolutionary Computation (CEC)</i>. <a href=\"https://doi.org/10.1109/CEC.2016.7748359\">https://doi.org/10.1109/CEC.2016.7748359</a>","short":"P. Kerschke, H. Trautmann, in: Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Vancouver, BC, Kanada, 2016.","mla":"Kerschke, Pascal, and Heike Trautmann. “The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems.” <i>Proceedings of the IEEE Congress on Evolutionary Computation (CEC)</i>, 2016, doi:<a href=\"https://doi.org/10.1109/CEC.2016.7748359\">10.1109/CEC.2016.7748359</a>.","bibtex":"@inproceedings{Kerschke_Trautmann_2016, place={Vancouver, BC, Kanada}, title={The R-Package FLACCO for Exploratory Landscape Analysis with Applications to Multi-Objective Optimization Problems}, DOI={<a href=\"https://doi.org/10.1109/CEC.2016.7748359\">10.1109/CEC.2016.7748359</a>}, booktitle={Proceedings of the IEEE Congress on Evolutionary Computation (CEC)}, author={Kerschke, Pascal and Trautmann, Heike}, year={2016} }"},"year":"2016","place":"Vancouver, BC, Kanada"},{"status":"public","abstract":[{"text":"This report documents the talks and discussions at the Dagstuhl Seminar 15211 \"Theory of Evolutionary Algorithms\". This seminar, now in its 8th edition, is the main meeting point of the highly active theory of randomized search heuristics subcommunities in Australia, Asia, North America, and Europe. Topics intensively discussed include rigorous runtime analysis and computational complexity theory for randomised search heuristics, information geometry of randomised search, and synergies between the theory of evolutionary algorithms and theories of natural evolution.","lang":"eng"}],"type":"journal_article","publication":"Dagstuhl Reports","language":[{"iso":"eng"}],"user_id":"15504","department":[{"_id":"34"},{"_id":"819"}],"_id":"46370","citation":{"ama":"Neumann F, Trautmann H. Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211). <i>Dagstuhl Reports</i>. 2016;5(5):78–79. doi:<a href=\"https://doi.org/10.4230/DagRep.5.5.57\">10.4230/DagRep.5.5.57</a>","ieee":"F. Neumann and H. Trautmann, “Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211),” <i>Dagstuhl Reports</i>, vol. 5, no. 5, pp. 78–79, 2016, doi: <a href=\"https://doi.org/10.4230/DagRep.5.5.57\">10.4230/DagRep.5.5.57</a>.","chicago":"Neumann, F, and Heike Trautmann. “Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211).” <i>Dagstuhl Reports</i> 5, no. 5 (2016): 78–79. <a href=\"https://doi.org/10.4230/DagRep.5.5.57\">https://doi.org/10.4230/DagRep.5.5.57</a>.","short":"F. Neumann, H. Trautmann, Dagstuhl Reports 5 (2016) 78–79.","mla":"Neumann, F., and Heike Trautmann. “Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211).” <i>Dagstuhl Reports</i>, vol. 5, no. 5, 2016, pp. 78–79, doi:<a href=\"https://doi.org/10.4230/DagRep.5.5.57\">10.4230/DagRep.5.5.57</a>.","bibtex":"@article{Neumann_Trautmann_2016, title={Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211)}, volume={5}, DOI={<a href=\"https://doi.org/10.4230/DagRep.5.5.57\">10.4230/DagRep.5.5.57</a>}, number={5}, journal={Dagstuhl Reports}, author={Neumann, F and Trautmann, Heike}, year={2016}, pages={78–79} }","apa":"Neumann, F., &#38; Trautmann, H. (2016). Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211). <i>Dagstuhl Reports</i>, <i>5</i>(5), 78–79. <a href=\"https://doi.org/10.4230/DagRep.5.5.57\">https://doi.org/10.4230/DagRep.5.5.57</a>"},"page":"78–79","intvolume":"         5","year":"2016","issue":"5","doi":"10.4230/DagRep.5.5.57","title":"Working Group Report: Bridging the Gap Between Experiments and Theory Using Feature-Based Run-Time Analysis; Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211)","author":[{"last_name":"Neumann","full_name":"Neumann, F","first_name":"F"},{"id":"100740","full_name":"Trautmann, Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","first_name":"Heike"}],"date_created":"2023-08-04T15:17:00Z","volume":5,"date_updated":"2023-10-16T13:40:00Z"},{"doi":"10.1007/978-3-319-50349-3_4","date_updated":"2023-12-13T10:47:05Z","author":[{"first_name":"Jakob","full_name":"Bossek, Jakob","id":"102979","orcid":"0000-0002-4121-4668","last_name":"Bossek"},{"full_name":"Trautmann, Heike","last_name":"Trautmann","first_name":"Heike"}],"place":"Cham","citation":{"ama":"Bossek J, Trautmann H. Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers. In: Festa P, Sellmann M, Vanschoren J, eds. <i>Learning and Intelligent Optimization</i>. Lecture Notes in Computer Science. Springer International Publishing; 2016:48–59. doi:<a href=\"https://doi.org/10.1007/978-3-319-50349-3_4\">10.1007/978-3-319-50349-3_4</a>","chicago":"Bossek, Jakob, and Heike Trautmann. “Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers.” In <i>Learning and Intelligent Optimization</i>, edited by Paola Festa, Meinolf Sellmann, and Joaquin Vanschoren, 48–59. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2016. <a href=\"https://doi.org/10.1007/978-3-319-50349-3_4\">https://doi.org/10.1007/978-3-319-50349-3_4</a>.","ieee":"J. Bossek and H. Trautmann, “Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers,” in <i>Learning and Intelligent Optimization</i>, 2016, pp. 48–59, doi: <a href=\"https://doi.org/10.1007/978-3-319-50349-3_4\">10.1007/978-3-319-50349-3_4</a>.","apa":"Bossek, J., &#38; Trautmann, H. (2016). Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers. In P. Festa, M. Sellmann, &#38; J. Vanschoren (Eds.), <i>Learning and Intelligent Optimization</i> (pp. 48–59). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-319-50349-3_4\">https://doi.org/10.1007/978-3-319-50349-3_4</a>","short":"J. Bossek, H. Trautmann, in: P. Festa, M. Sellmann, J. Vanschoren (Eds.), Learning and Intelligent Optimization, Springer International Publishing, Cham, 2016, pp. 48–59.","mla":"Bossek, Jakob, and Heike Trautmann. “Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers.” <i>Learning and Intelligent Optimization</i>, edited by Paola Festa et al., Springer International Publishing, 2016, pp. 48–59, doi:<a href=\"https://doi.org/10.1007/978-3-319-50349-3_4\">10.1007/978-3-319-50349-3_4</a>.","bibtex":"@inproceedings{Bossek_Trautmann_2016, place={Cham}, series={Lecture Notes in Computer Science}, title={Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers}, DOI={<a href=\"https://doi.org/10.1007/978-3-319-50349-3_4\">10.1007/978-3-319-50349-3_4</a>}, booktitle={Learning and Intelligent Optimization}, publisher={Springer International Publishing}, author={Bossek, Jakob and Trautmann, Heike}, editor={Festa, Paola and Sellmann, Meinolf and Vanschoren, Joaquin}, year={2016}, pages={48–59}, collection={Lecture Notes in Computer Science} }"},"page":"48–59","publication_status":"published","publication_identifier":{"isbn":["978-3-319-50349-3"]},"extern":"1","_id":"48873","user_id":"102979","series_title":"Lecture Notes in Computer Science","department":[{"_id":"819"}],"editor":[{"first_name":"Paola","full_name":"Festa, Paola","last_name":"Festa"},{"first_name":"Meinolf","last_name":"Sellmann","full_name":"Sellmann, Meinolf"},{"first_name":"Joaquin","full_name":"Vanschoren, Joaquin","last_name":"Vanschoren"}],"status":"public","type":"conference","title":"Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers","publisher":"Springer International Publishing","date_created":"2023-11-14T15:58:57Z","year":"2016","keyword":["Algorithm selection","Feature selection","Instance hardness","TSP"],"language":[{"iso":"eng"}],"abstract":[{"text":"Despite the intrinsic hardness of the Traveling Salesperson Problem (TSP) heuristic solvers, e.g., LKH+restart and EAX+restart, are remarkably successful in generating satisfactory or even optimal solutions. However, the reasons for their success are not yet fully understood. Recent approaches take an analytical viewpoint and try to identify instance features, which make an instance hard or easy to solve. We contribute to this area by generating instance sets for couples of TSP algorithms A and B by maximizing/minimizing their performance difference in order to generate instances which are easier to solve for one solver and much harder to solve for the other. This instance set offers the potential to identify key features which allow to distinguish between the problem hardness classes of both algorithms.","lang":"eng"}],"publication":"Learning and Intelligent Optimization"},{"publication":"Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037","type":"conference","abstract":[{"lang":"eng","text":"State of the Art inexact solvers of the NP-hard Traveling Salesperson Problem TSP are known to mostly yield high-quality solutions in reasonable computation times. With the purpose of understanding different levels of instance difficulties, instances for the current State of the Art heuristic TSP solvers LKH+restart and EAX+restart are presented which are evolved using a sophisticated evolutionary algorithm. More specifically, the performance differences of the respective solvers are maximized resulting in instances which are easier to solve for one solver and much more difficult for the other. Focusing on both optimization directions, instance features are identified which characterize both types of instances and increase the understanding of solver performance differences."}],"status":"public","_id":"48874","series_title":"AI*IA 2016","user_id":"102979","keyword":["Combinatorial optimization","Instance hardness","Metaheuristics","Transportation","TSP"],"language":[{"iso":"eng"}],"extern":"1","publication_identifier":{"isbn":["978-3-319-49129-5"]},"publication_status":"published","year":"2016","place":"Berlin, Heidelberg","page":"3–12","citation":{"mla":"Bossek, Jakob, and Heike Trautmann. “Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference.” <i>Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037</i>, Springer-Verlag, 2016, pp. 3–12, doi:<a href=\"https://doi.org/10.1007/978-3-319-49130-1_1\">10.1007/978-3-319-49130-1_1</a>.","bibtex":"@inproceedings{Bossek_Trautmann_2016, place={Berlin, Heidelberg}, series={AI*IA 2016}, title={Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference}, DOI={<a href=\"https://doi.org/10.1007/978-3-319-49130-1_1\">10.1007/978-3-319-49130-1_1</a>}, booktitle={Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037}, publisher={Springer-Verlag}, author={Bossek, Jakob and Trautmann, Heike}, year={2016}, pages={3–12}, collection={AI*IA 2016} }","short":"J. Bossek, H. Trautmann, in: Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037, Springer-Verlag, Berlin, Heidelberg, 2016, pp. 3–12.","apa":"Bossek, J., &#38; Trautmann, H. (2016). Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. <i>Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037</i>, 3–12. <a href=\"https://doi.org/10.1007/978-3-319-49130-1_1\">https://doi.org/10.1007/978-3-319-49130-1_1</a>","ama":"Bossek J, Trautmann H. Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. In: <i>Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037</i>. AI*IA 2016. Springer-Verlag; 2016:3–12. doi:<a href=\"https://doi.org/10.1007/978-3-319-49130-1_1\">10.1007/978-3-319-49130-1_1</a>","chicago":"Bossek, Jakob, and Heike Trautmann. “Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference.” In <i>Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037</i>, 3–12. AI*IA 2016. Berlin, Heidelberg: Springer-Verlag, 2016. <a href=\"https://doi.org/10.1007/978-3-319-49130-1_1\">https://doi.org/10.1007/978-3-319-49130-1_1</a>.","ieee":"J. Bossek and H. Trautmann, “Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference,” in <i>Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037</i>, 2016, pp. 3–12, doi: <a href=\"https://doi.org/10.1007/978-3-319-49130-1_1\">10.1007/978-3-319-49130-1_1</a>."},"date_updated":"2023-12-13T10:47:11Z","publisher":"Springer-Verlag","date_created":"2023-11-14T15:58:57Z","author":[{"first_name":"Jakob","orcid":"0000-0002-4121-4668","last_name":"Bossek","id":"102979","full_name":"Bossek, Jakob"},{"full_name":"Trautmann, Heike","last_name":"Trautmann","first_name":"Heike"}],"title":"Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference","doi":"10.1007/978-3-319-49130-1_1"}]