Prof. Dr. rer. pol. Pascal Kerschke
Person

Affiliations

Chair of Big Data Analytics in Transportation (TT)
- Full Professor
- pascal.kerschke@tu-dresden.de

Identification Numbers

ORCID	0000-0003-2862-1418
Scopus author ID	56336853600
Researcher ID	B-8845-2017

Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization

Rodriguez-Fernandez, A. E., Schäpermeier, L., Hernández, C., Kerschke, P., Trautmann, H. & Schütze, O., Oct 2025, In: IEEE transactions on evolutionary computation : a publication of the IEEE Neural Networks Council. 29, 5, p. 2019-2031 13 p.

Research output: Contribution to journal › Research article › Contributed › peer-review

Clearing the Combinatorial Fog: Tracing the Hidden Paths of TSP Heuristics

Heins, J., Dengel, S., Whitley, D. & Kerschke, P., 27 Aug 2025, (E-pub ahead of print) FOGA 2025 - Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. p. 73-84 12 p.

Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review

Hot off the Press: Finding e-locally Optimal Solutions for Multi-objective Multimodal Optimization

Rodriguez-Fernandez, A. E., Schütze, O., Schäpermeier, L., Kerschke, P., Castellanos, C. H. & Trautmann, H., 11 Aug 2025, GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion. Ochoa, G. (ed.). Association for Computing Machinery, Inc, p. 61-62 2 p.

Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review

To Repair or Not to Repair? Investigating the Importance of AB-Cycles for the State-of-the-Art TSP Heuristic EAX

Heins, J., Whitley, D. & Kerschke, P., Jul 2025, GECCO '25: Proceedings of the Genetic and Evolutionary Computation Conference. Ochoa, G. (ed.). p. 231-239 9 p.

Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review

Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems

Seiler, M. V., Kerschke, P. & Trautmann, H., 2025, In: Evolutionary Computation. p. 1-27 27 p.

Research output: Contribution to journal › Research article › Contributed › peer-review

View all research output (70)

Interpretable Spatiotemporal Feature Selection for Solar Power Forecasts

Leyser, M. (Speaker), Kerschke, P. (Involved person), Schäpermeier, L. (Involved person)

22 May 2024

Activity: Talk or presentation at external institutions/events › Talk/Presentation › Contributed

Research Portal of the TU Dresden

Prof. Dr. rer. pol. Pascal Kerschke
Person

Affiliations

Identification Numbers

Related content

Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization

Clearing the Combinatorial Fog: Tracing the Hidden Paths of TSP Heuristics

Hot off the Press: Finding e-locally Optimal Solutions for Multi-objective Multimodal Optimization

To Repair or Not to Repair? Investigating the Importance of AB-Cycles for the State-of-the-Art TSP Heuristic EAX

Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems

Interpretable Spatiotemporal Feature Selection for Solar Power Forecasts

Best Paper Award auf der PPSN XVIII