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16 Publications
2022 | Conference Paper | LibreCat-ID: 31066
Schön O, Götte R-S, Timmermann J. Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. In: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022). Vol 55. ; 2022:19-24. doi:https://doi.org/10.1016/j.ifacol.2022.07.282
LibreCat
| DOI
2022 | Conference Paper | LibreCat-ID: 48882
Heins J, Rook J, Schäpermeier L, Kerschke P, Bossek J, Trautmann H. BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tusar T, eds. Parallel Problem Solving from Nature (PPSN XVII). Lecture Notes in Computer Science. Springer International Publishing; 2022:192–206. doi:10.1007/978-3-031-14714-2_14
LibreCat
| DOI
2022 | Conference Paper | LibreCat-ID: 48896
Rook J, Trautmann H, Bossek J, Grimme C. On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO’22. Association for Computing Machinery; 2022:356–359. doi:10.1145/3520304.3528998
LibreCat
| DOI
2021 | Journal Article | LibreCat-ID: 21808 | 
Schneider SB, Khalili R, Manzoor A, et al. Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning. Transactions on Network and Service Management. 2021. doi:10.1109/TNSM.2021.3076503
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| DOI
2021 | Journal Article | LibreCat-ID: 46318
Grimme C, Kerschke P, Aspar P, et al. Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Computers & Operations Research. 2021;136:105489. doi:https://doi.org/10.1016/j.cor.2021.105489
LibreCat
| DOI
2020 | Journal Article | LibreCat-ID: 46334
Bossek J, Kerschke P, Trautmann H. A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. Applied Soft Computing. 2020;88:105901. doi:https://doi.org/10.1016/j.asoc.2019.105901
LibreCat
| DOI
2020 | Conference Paper | LibreCat-ID: 48845
Bossek J, Grimme C, Trautmann H. Dynamic Bi-Objective Routing of Multiple Vehicles. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’20. Association for Computing Machinery; 2020:166–174. doi:10.1145/3377930.3390146
LibreCat
| DOI
2020 | Journal Article | LibreCat-ID: 48848
Bossek J, Kerschke P, Trautmann H. A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms. Applied Soft Computing. 2020;88(C). doi:10.1016/j.asoc.2019.105901
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 48841
Bossek J, Grimme C, Meisel S, Rudolph G, Trautmann H. Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm. In: Deb K, Goodman E, Coello Coello CA, et al., eds. Evolutionary Multi-Criterion Optimization (EMO). Lecture Notes in Computer Science. Springer International Publishing; 2019:516–528. doi:10.1007/978-3-030-12598-1_41
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 48840
Bossek J, Grimme C, Neumann F. On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’19. Association for Computing Machinery; 2019:516–523. doi:10.1145/3321707.3321818
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