Pascal Kerschke

95 papers A 14B 3C 6Journal 44Unranked 25
YearRankTypeTitle / Venue / Authors
2026 J jnl
BONO-Bench: A Comprehensive Test Suite for Bi-objective Numerical Optimization with Traceable Pareto Sets.
CoRR
Lennart Schäpermeier, Pascal Kerschke
2025 A conf
Clearing the Combinatorial Fog: Tracing the Hidden Paths of TSP Heuristics.
FOGA
Jonathan Heins, Sebastian Dengel, Darrell Whitley, Pascal Kerschke
2025 J jnl
Finding ϵ-Locally Optimal Solutions for Multiobjective Multimodal Optimization.
IEEE Trans. Evol. Comput.
Angel E. Rodriguez-Fernandez, Lennart Schäpermeier, Carlos Hernández, Pascal Kerschke, Heike Trautmann, Oliver Schütze
2025 — conf
Hot off the Press: Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.
GECCO Companion
Angel E. Rodriguez-Fernandez, Lennart Schäpermeier, Carlos Ignacio Hernández Castellanos, Pascal Kerschke, Heike Trautmann, Oliver Schütze
2025 A conf
To Repair or Not to Repair? Investigating the Importance of AB-Cycles for the State-of-the-Art TSP Heuristic EAX.
GECCO
Jonathan Heins, Darrell Whitley, Pascal Kerschke
2025 J jnl
To Repair or Not to Repair? Investigating the Importance of AB-Cycles for the State-of-the-Art TSP Heuristic EAX.
CoRR
Jonathan Heins, Darrell Whitley, Pascal Kerschke
2024 — conf
Dancing to the State of the Art? - How Candidate Lists Influence LKH for Solving the Traveling Salesperson Problem.
PPSN (1)
Jonathan Heins, Lennart Schäpermeier, Pascal Kerschke, Darrell Whitley
2024 J jnl
Dancing to the State of the Art? How Candidate Lists Influence LKH for Solving the Traveling Salesperson Problem.
CoRR
Jonathan Heins, Lennart Schäpermeier, Pascal Kerschke, Darrell Whitley
2024 J jnl
Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems.
CoRR
Moritz Vinzent Seiler, Pascal Kerschke, Heike Trautmann
2024 A conf
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization.
GECCO
Konstantin Dietrich, Diederick Vermetten, Carola Doerr, Pascal Kerschke
2024 J jnl
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization.
CoRR
Konstantin Dietrich, Diederick Vermetten, Carola Doerr, Pascal Kerschke
2024 — conf
Reinvestigating the R2 Indicator: Achieving Pareto Compliance by Integration.
PPSN (4)
Lennart Schäpermeier, Pascal Kerschke
2024 J jnl
Reinvestigating the R2 Indicator: Achieving Pareto Compliance by Integration.
CoRR
Lennart Schäpermeier, Pascal Kerschke
2023 J jnl
A study on the effects of normalized TSP features for automated algorithm selection.
Theor. Comput. Sci.
Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke
2023 J jnl
Challenges in Benchmarking Optimization Heuristics (Dagstuhl Seminar 23251).
Dagstuhl Reports
Anne Auger, Peter A. N. Bosman, Pascal Kerschke, Darrell Whitley, Lennart Schäpermeier
2023 — conf
Evaluation of Algorithms from the Nevergrad Toolbox on the Strictly Box-Constrained SBOX-COST Benchmarking Suite.
GECCO Companion
Konstantin Dietrich, Pascal Kerschke
2023 — conf
Exploratory Landscape Analysis.
GECCO Companion
Pascal Kerschke, Mike Preuss
2023 A conf
Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features.
FOGA
Raphael Patrick Prager, Konstantin Dietrich, Lennart Schneider, Lennart Schäpermeier, Bernd Bischl, Pascal Kerschke, Heike Trautmann, Olaf Mersmann
2023 C conf
Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets.
EMO
Lennart Schäpermeier, Pascal Kerschke, Christian Grimme, Heike Trautmann
2023 J jnl
The objective that freed me: a multi-objective local search approach for continuous single-objective optimization.
Nat. Comput.
Pelin Aspar, Vera Steinhoff, Lennart Schäpermeier, Pascal Kerschke, Heike Trautmann, Christian Grimme
2023 J jnl
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games.
Appl. Soft Comput.
Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar
2023 J jnl
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games.
CoRR
Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar
2022 J jnl
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes.
CoRR
Moritz Vinzent Seiler, Raphael Patrick Prager, Pascal Kerschke, Heike Trautmann
2022 A conf
A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapes.
GECCO
Moritz Vinzent Seiler, Raphael Patrick Prager, Pascal Kerschke, Heike Trautmann
2022 — conf
Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods.
PPSN (1)
Raphael Patrick Prager, Moritz Vinzent Seiler, Heike Trautmann, Pascal Kerschke
2022 — conf
BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems.
PPSN (1)
Jonathan Heins, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, Heike Trautmann
2022 J jnl
Correction to: Estimation of component reliability from superposed renewal processes by means of latent variables.
Comput. Stat.
Agatha S. Rodrigues, Pascal Kerschke, Carlos Alberto De Bragança Pereira, Heike Trautmann, Carolin Wagner, Bernd Hellingrath, Adriano Polpo
2022 J jnl
Estimation of component reliability from superposed renewal processes by means of latent variables.
Comput. Stat.
Agatha S. Rodrigues, Pascal Kerschke, Carlos Alberto De Bragança Pereira, Heike Trautmann, Carolin Wagner, Bernd Hellingrath, Adriano Polpo
2022 J jnl
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.
CoRR
Lennart Schneider, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, Pascal Kerschke
2022 — conf
HPO ˟ ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.
PPSN (1)
Lennart Schneider, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, Pascal Kerschke
2022 J jnl
MOLE: Digging Tunnels Through Multimodal Multi-Objective Landscapes.
CoRR
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
2022 A conf
MOLE: digging tunnels through multimodal multi-objective landscapes.
GECCO
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
2022 C conf
Mixture of Decision Trees for Interpretable Machine Learning.
ICMLA
Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke, Marco F. Huber
2022 J jnl
Mixture of Decision Trees for Interpretable Machine Learning.
CoRR
Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke, Marco F. Huber
2022 — ed.
Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Dortmund, Germany, September 10-14, 2022, Proceedings, Part I
PPSN (1)
Günter Rudolph, Anna V. Kononova, Hernán E. Aguirre, Pascal Kerschke, Gabriela Ochoa, Tea Tusar
2022 — ed.
Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Dortmund, Germany, September 10-14, 2022, Proceedings, Part II
PPSN (2)
Günter Rudolph, Anna V. Kononova, Hernán E. Aguirre, Pascal Kerschke, Gabriela Ochoa, Tea Tusar
2022 J jnl
Plotting Impossible? Surveying Visualization Methods for Continuous Multi-Objective Benchmark Problems.
IEEE Trans. Evol. Comput.
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
2021 — ch.
Lifting the Multimodality-Fog in Continuous Multi-objective Optimization.
Metaheuristics for Finding Multiple Solutions
Pascal Kerschke, Christian Grimme
2021 C conf
Multi
EMO
Pelin Aspar, Pascal Kerschke, Vera Steinhoff, Heike Trautmann, Christian Grimme
2021 A conf
On the potential of normalized TSP features for automated algorithm selection.
FOGA
Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke
2021 J jnl
Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization.
Comput. Oper. Res.
Christian Grimme, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, Michael Emmerich
2021 C conf
To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes.
EMO
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
2021 — conf
Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box Optimization.
SSCI
Raphael Patrick Prager, Moritz Vinzent Seiler, Heike Trautmann, Pascal Kerschke
2020 J jnl
A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms.
Appl. Soft Comput.
Jakob Bossek, Pascal Kerschke, Heike Trautmann
2020 B conf
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection.
CEC
Jakob Bossek, Pascal Kerschke, Heike Trautmann
2020 J jnl
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection.
CoRR
Jakob Bossek, Pascal Kerschke, Heike Trautmann
2020 J jnl
Benchmarking in Optimization: Best Practice and Open Issues.
CoRR
Thomas Bartz-Beielstein, Carola Doerr, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, Manuel López-Ibáñez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise
2020 — conf
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.
PPSN (1)
Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann
2020 J jnl
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.
CoRR
Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann
2020 J jnl
Empirical Study on the Benefits of Multiobjectivization for Solving Single-Objective Problems.
CoRR
Vera Steinhoff, Pascal Kerschke, Christian Grimme
2020 B conf
Enhancing Resilience of Deep Learning Networks By Means of Transferable Adversaries.
IJCNN
Moritz Seiler, Heike Trautmann, Pascal Kerschke
2020 J jnl
Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries.
CoRR
Moritz Seiler, Heike Trautmann, Pascal Kerschke
2020 — conf
Evolving Sampling Strategies for One-Shot Optimization Tasks.
PPSN (1)
Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, Frank Neumann
2020 J jnl
Initial Design Strategies and their Effects on Sequential Model-Based Optimization.
CoRR
Jakob Bossek, Carola Doerr, Pascal Kerschke
2020 A conf
Initial design strategies and their effects on sequential model-based optimization: an exploratory case study based on BBOB.
GECCO
Jakob Bossek, Carola Doerr, Pascal Kerschke
2020 — conf
Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent.
SSCI
Vera Steinhoff, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Christian Grimme
2020 J jnl
Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent.
CoRR
Vera Steinhoff, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Christian Grimme
2020 J jnl
One PLOT to Show Them All: Visualization of Efficient Sets in Multi-Objective Landscapes.
CoRR
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
2020 — conf
One PLOT to Show Them All: Visualization of Efficient Sets in Multi-objective Landscapes.
PPSN (2)
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
2020 — conf
Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis.
SSCI
Raphael Patrick Prager, Heike Trautmann, Hao Wang, Thomas Bäck, Pascal Kerschke
2020 J jnl
The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics.
CoRR
Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann
2020 A conf
The node weight dependent traveling salesperson problem: approximation algorithms and randomized search heuristics.
GECCO
Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann
2020 J jnl
To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes.
CoRR
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
2019 J jnl
Automated Algorithm Selection on Continuous Black-Box Problems by Combining Exploratory Landscape Analysis and Machine Learning.
Evol. Comput.
Pascal Kerschke, Heike Trautmann
2019 J jnl
Automated Algorithm Selection: Survey and Perspectives.
Evol. Comput.
Pascal Kerschke, Holger H. Hoos, Frank Neumann, Heike Trautmann
2019 A conf
Evolving diverse TSP instances by means of novel and creative mutation operators.
FOGA
Jakob Bossek, Pascal Kerschke, Aneta Neumann, Markus Wagner, Frank Neumann, Heike Trautmann
2019 — conf
Exploratory landscape analysis.
GECCO (Companion)
Pascal Kerschke, Mike Preuss
2019 — conf
Exploring the MLDA benchmark on the nevergrad platform.
GECCO (Companion)
Jérémy Rapin, Marcus Gallagher, Pascal Kerschke, Mike Preuss, Olivier Teytaud
2019 — conf
Making a case for (Hyper-)parameter tuning as benchmark problems.
GECCO (Companion)
Carola Doerr, Johann Dréo, Pascal Kerschke
2019 C conf
Multimodality in Multi-objective Optimization - More Boon than Bane?
EMO
Christian Grimme, Pascal Kerschke, Heike Trautmann
2019 J jnl
One-Shot Decision-Making with and without Surrogates.
CoRR
Jakob Bossek, Pascal Kerschke, Aneta Neumann, Frank Neumann, Carola Doerr
2019 J jnl
OpenML: An R package to connect to the machine learning platform OpenML.
Comput. Stat.
Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl
2019 J jnl
Search Dynamics on Multimodal Multiobjective Problems.
Evol. Comput.
Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael T. M. Emmerich
2019 A conf
Single- and multi-objective game-benchmark for evolutionary algorithms.
GECCO
Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar
2018 J jnl
Automated Algorithm Selection: Survey and Perspectives.
CoRR
Pascal Kerschke, Holger H. Hoos, Frank Neumann, Heike Trautmann
2018 J jnl
Leveraging TSP Solver Complementarity through Machine Learning.
Evol. Comput.
Pascal Kerschke, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, Heike Trautmann
2018 — conf
Parameterization of state-of-the-art performance indicators: a robustness study based on inexact TSP solvers.
GECCO (Companion)
Pascal Kerschke, Jakob Bossek, Heike Trautmann
2018 — conf
Tutorials at PPSN 2018.
PPSN (2)
Gisele Lobo Pappa, Michael T. M. Emmerich, Ana L. C. Bazzan, Will N. Browne, Kalyanmoy Deb, Carola Doerr, Marko Durasevic, Michael G. Epitropakis, Saemundur O. Haraldsson, Domagoj Jakobovic, Pascal Kerschke, Krzysztof Krawiec, Per Kristian Lehre, Xiaodong Li, Andrei Lissovoi, Pekka Malo, Luis Martí, Yi Mei, Juan Julián Merelo Guervós, Julian F. Miller, Alberto Moraglio, Antonio J. Nebro, Su Nguyen, Gabriela Ochoa, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Marc Schoenauer, Roman Senkerik, Ankur Sinha, Ofer M. Shir, Dirk Sudholt, L. Darrell Whitley, Mark Wineberg, John R. Woodward, Mengjie Zhang
2018 — conf
Workshops at PPSN 2018.
PPSN (2)
Robin C. Purshouse, Christine Zarges, Sylvain Cussat-Blanc, Michael G. Epitropakis, Marcus Gallagher, Thomas Jansen, Pascal Kerschke, Xiaodong Li, Fernando G. Lobo, Julian F. Miller, Pietro S. Oliveto, Mike Preuss, Giovanni Squillero, Alberto Paolo Tonda, Markus Wagner, Thomas Weise, Dennis Wilson, Borys Wróbel, Ales Zamuda
2017 C conf
An Expedition to Multimodal Multi-objective Optimization Landscapes.
EMO
Pascal Kerschke, Christian Grimme
2017 J jnl
Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning.
CoRR
Pascal Kerschke, Heike Trautmann
2017 — conf
Exploratory landscape analysis: advanced tutorial at GECCO 2017.
GECCO (Companion)
Pascal Kerschke, Mike Preuss
2017 J jnl
OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML.
CoRR
Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl
2017 — conf
flaccogui: exploratory landscape analysis for everyone.
GECCO (Companion)
Christian Hanster, Pascal Kerschke
2016 J jnl
ASlib: A benchmark library for algorithm selection.
Artif. Intell.
Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren
2016 A conf
Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models.
GECCO
Pascal Kerschke, Mike Preuss, Simon Wessing, Heike Trautmann
2016 J jnl
Modelling interventions in INGARCH processes.
Int. J. Comput. Math.
Tobias Liboschik, Pascal Kerschke, Konstantinos Fokianos, Roland Fried
2016 B conf
The R-Package FLACCO for exploratory landscape analysis with applications to multi-objective optimization problems.
CEC
Pascal Kerschke, Heike Trautmann
2016 A conf
Towards Analyzing Multimodality of Continuous Multiobjective Landscapes.
PPSN
Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael Emmerich
2015 J jnl
ASlib: A Benchmark Library for Algorithm Selection.
CoRR
Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren
2015 — conf
An Overview of Topic Discovery in Twitter Communication through Social Media Analytics.
AMCIS
Andrey Chinnov, Pascal Kerschke, Christian Meske, Stefan Stieglitz, Heike Trautmann
2015 — conf
Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms.
GECCO (Companion)
Luis Martí, Christian Grimme, Pascal Kerschke, Heike Trautmann, Günter Rudolph
2015 J jnl
Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms.
CoRR
Luis Martí, Christian Grimme, Pascal Kerschke, Heike Trautmann, Günter Rudolph
2015 A conf
Detecting Funnel Structures by Means of Exploratory Landscape Analysis.
GECCO
Pascal Kerschke, Mike Preuss, Simon Wessing, Heike Trautmann
2015 — conf
Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection.
LION
Lars Kotthoff, Pascal Kerschke, Holger H. Hoos, Heike Trautmann