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197 Publications
2020 | Conference Paper | LibreCat-ID: 46330
M. Seiler, J. Pohl, J. Bossek, P. Kerschke, and H. Trautmann, “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem,” in Proceedings of the 16$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XVI), 2020, pp. 48–64, doi: 10.1007/978-3-030-58112-1_4.
LibreCat
| DOI
2020 | Journal Article | LibreCat-ID: 46334
J. Bossek, P. Kerschke, and H. Trautmann, “A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms,” Applied Soft Computing, vol. 88, p. 105901, 2020, doi: https://doi.org/10.1016/j.asoc.2019.105901.
LibreCat
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2020 | Conference Paper | LibreCat-ID: 46322
J. Bossek, C. Grimme, G. Rudolph, and H. Trautmann, “Towards Decision Support in Dynamic Bi-Objective Vehicle Routing,” in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2020, pp. 1–8, doi: 10.1109/CEC48606.2020.9185778.
LibreCat
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2020 | Conference Paper | LibreCat-ID: 46324
J. Bossek, P. Kerschke, and H. Trautmann, “Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection,” in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2020, pp. 1–8.
LibreCat
2020 | Conference Paper | LibreCat-ID: 46323
J. Bossek, C. Grimme, and H. Trautmann, “Dynamic Bi-Objective Routing of Multiple Vehicles,” in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’20), 2020, pp. 166–174.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46343
C. Grimme, P. Kerschke, and H. Trautmann, “Multimodality in Multi-Objective Optimization — More Boon than Bane?,” in Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization (EMO), 2019, vol. 11411, pp. 126–138, doi: 10.1007/978-3-030-12598-1_11.
LibreCat
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2019 | Journal Article | LibreCat-ID: 46345
P. Kerschke, H. H. Hoos, F. Neumann, and H. Trautmann, “Automated Algorithm Selection: Survey and Perspectives,” Evolutionary Computation (ECJ), vol. 27, no. 1, pp. 3–45, 2019, doi: 10.1162/evco_a_00242.
LibreCat
| DOI
2019 | Journal Article | LibreCat-ID: 46344
M. Carnein and H. Trautmann, “Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms,” Business and Information Systems Engineering (BISE), vol. 61, no. 3, pp. 277–297, 2019.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46340
M. Carnein, L. Homann, H. Trautmann, and G. Vossen, “A Recommender System Based on Omni-Channel Customer Data,” in Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19), 2019, pp. 65–74.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46341
M. Carnein and H. Trautmann, “Customer Segmentation Based on Transactional Data Using Stream Clustering,” in Proceedings of the 23$^rd$ Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’19), 2019, pp. 280–292.
LibreCat
2019 | Conference Paper | LibreCat-ID: 46342
C. Grimme, P. Kerschke, M. T. M. Emmerich, M. Preuss, A. H. Deutz, and H. Trautmann, “Sliding to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal Multi-Objective Optimization,” in AIP Conference Proceedings, 2019, pp. 020052-1-020052–4, doi: 10.1063/1.5090019.
LibreCat
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2019 | Book Chapter | LibreCat-ID: 46336
P. Kerschke and H. Trautmann, “Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-package flacco,” in Applications in Statistical Computing, N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, and M. Vichi, Eds. Springer, 2019, pp. 93–123.
LibreCat
| DOI
2019 | Book | LibreCat-ID: 46335
H. Trautmann, Applications in Statistical Computing — From Music Data Analysis to Industrial Quality Improvement. Springer International Publishing, 2019.
LibreCat
2019 | Journal Article | LibreCat-ID: 46346
P. Kerschke and H. Trautmann, “Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning,” Evolutionary Computation (ECJ), vol. 27, no. 1, pp. 99–127, 2019, doi: 10.1162/evco_a_00236.
LibreCat
| DOI
2019 | Journal Article | LibreCat-ID: 46347
P. Kerschke et al., “Search Dynamics on Multimodal Multi-Objective Problems,” Evolutionary Computation (ECJ), vol. 27, no. 4, pp. 577–609, 2019, doi: 10.1162/evco_a_00234.
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 48841
J. Bossek, C. Grimme, S. Meisel, G. Rudolph, and H. Trautmann, “Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm,” in Evolutionary Multi-Criterion Optimization (EMO), 2019, pp. 516–528, doi: 10.1007/978-3-030-12598-1_41.
LibreCat
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2019 | Conference Paper | LibreCat-ID: 48842
J. Bossek, P. Kerschke, A. Neumann, M. Wagner, F. Neumann, and H. Trautmann, “Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators,” in Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2019, pp. 58–71, doi: 10.1145/3299904.3340307.
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 48843
J. Bossek, F. Neumann, P. Peng, and D. Sudholt, “Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2019, pp. 1443–1451, doi: 10.1145/3321707.3321792.
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 48840
J. Bossek, C. Grimme, and F. Neumann, “On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2019, pp. 516–523, doi: 10.1145/3321707.3321818.
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 48858
J. Bossek and C. Grimme, “Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems,” in Learning and Intelligent Optimization, 2019, pp. 184–198, doi: 10.1007/978-3-030-05348-2_17.
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