Accepted Papers

Below is the list of papers accepted for presentation at FOGA 2025.

• Optimal Restart Strategies for Parameter-dependent Optimization Algorithms
  Lisa Schönenberger (Ulm University, Vorarlberg University of Applied Sciences), Hans-Georg Beyer (Vorarlberg University of Applied Sciences)
• Additive Drift as an Optimization Problem for the (1+1)-ES
  Alexander Jungeilges (Ruhr-University Bochum), Tobias Glasmachers (Ruhr-University Bochum)
• Runtime Analysis of a Compact Genetic Algorithm with High Selection Pressure
  Sumit Adak (Technical University of Denmark), Carsten Witt (Technical University of Denmark)
• Diversity-Preserving Exploitation of Crossover
  Johannes Lengler (ETH Zurich), Tom Offermann (ETH Zurich)
• Population Dynamics and Improved Runtime Guarantees for the $(\mu+1)$ EA on BinVal
  Martin S. Krejca (Ecole Polytechnique, Institut Polytechnique de Paris), Frank Neumann (University of Adelaide), Carsten Witt (Technical University of Denmark)
• Availability of Perfect Decomposition in Statistical Linkage Learning for Unitation-Based Function Concatenations
  Michal Prusik (Wroclaw University of Science and Technology), Bartosz Frej (Wroclaw University of Science And Technology), Michal Przewozniczek (Wroclaw University of Science and Technology)
• Foundations of Correlated Mutations for Integer Programming
  Ofer Shir (Tel-Hai College, Migal Institute), Michael Emmerich (University of Jyvaskyla)
• A Standardized Benchmark Set of Clustering Problem Instances for Comparing Black-Box Optimizers
  Diederick Vermetten (LIP6, Sorbonne University; CNRS), Catalin-Viorel Dinu (LIP6, Sorbonne University; CNRS), Marcus Gallagher (Queensland University)
• Efficient Online Automated Algorithm Selection in the Face of Data-Drift in Optimisation Problem Instances
  Jeroen Rook (Paderborn University, University of Twente), Quentin Renau (Edinburgh Napier University), Heike Trautmann (Paderborn University, University of Twente), Emma Hart (Edinburgh Napier University)
• Runtime Bounds for a Coevolutionary Algorithm on Classes of Potential Games
  Mario Alejandro Hevia Fajardo (University of Birmingham), Jamal Toutouh (University of Malage), Erik Hemberg (Massachusetts Institute of Technology), Una-May O'Reilly (Massachusetts Institute of Technology), Per Kristian Lehre (University of Birmingham)
• Hyper-GRASP: A Hypervolume-Based Constructive Heuristic
  Gonçalo Lopes (University of Coimbra, CISUC/LASI, DEI), Luís Paquete (University of Coimbra, CISUC/LASI, DEI), Carlos Fonseca (University of Coimbra, CISUC/LASI, DEI)
• On the Problem Characteristics of Multi-objective Pseudo Boolean Functions in Runtime Analysis
  Zimin Liang (University of Birmingham), Miqing Li (University of Birmingham)
• A First Runtime Analysis of the PAES-25: An Enhanced Variant of the Pareto Archived Evolution Strategy
  Andre Opris (University of Passau)
• Scalable Multi-Modal Multi-Objective Test Problems with Respect to Decision Space Dimensionality and Pareto Set Dimensionality: High-Dimensional Manhattan Distance Minimization Problems
  Hisao Ishibuchi (Southern University of Science and Technology), Tianye Shu (Southern University of Science and Technology), Lie Meng Pang (Southern University of Science and Technology)
• Surrogate Model Assisted Evolutionary Algorithms: Performance Bound and Incremental Gaussian Process Model Updates
  Hong Huang (Dalhousie University), Dirk V. Arnold (Dalhousie University)
• Generating Realistic Benchmarks for Dynamic Truck and Trailer Scheduling using Gaussian Copulas
  Joan Alza (Robert Gordon University, National Subsea Centre), Mark Bartlett (Robert Gordon University), Josu Ceberio (University of the Basque Country), John McCall (Robert Gordon University)
• Optimal Distributions of Solutions for Maximizing the Minimum Crowding Distance for Two-Objective and Three-Objective Linear Pareto Fronts: Search Behavior Analysis of NSGA-II
  Hisao Ishibuchi (Southern University of Science and Technology), Yang Nan (Southern University of Science and Technology), Lie Meng Pang (Southern University of Science and Technology)
• Multi-parameter Control for the (1+($\lambda$,$\lambda$))-GA on OneMax via Deep Reinforcement Learning
  Tai Nguyen (University of St Andrews, Sorbonne University), Phong Le (University of St Andrews), Carola Doerr (CNRS, Sorbonne University), Nguyen Dang (University of St Andrews)
• A Fixed-Parameter Tractable GA for Data Clustering
  Liam Gaeuman (University of Minnesota Duluth), Andrew M. Sutton (University of Minnesota Duluth)
• Analyzing Competitive Coevolution across Families of N-Player Games through Tree Search
  Sean N. Harris (Auburn University, BONSAI Lab), Daniel R. Tauritz (Auburn University, BONSAI Lab), Samuel Mulder (Auburn University, BONSAI Lab)
• Distributed Evolutionary Algorithms with Adversarial Corruption
  Brahim Aboutaib (University of Minnesota Duluth), Andrew M. Sutton (University of Minnesota Duluth)
• Trust Region-Based Bayesian Optimisation to Discover Diverse Solutions
  Kokila Kasuni Perera (Optimisation and Logistics, School of Computer and Mathematical Sciences, The University of Adelaide), Frank Neumann (Optimisation and Logistics, School of Computer and Mathematical Sciences, The University of Adelaide), Aneta Neumann (Optimisation and Logistics, School of Computer and Mathematical Sciences, The University of Adelaide)
• Clearing the Combinatorial Fog: Tracing the Hidden Paths of TSP Heuristics
  Jonathan Heins (TU Dresden), Sebastian Dengel (TU Dresden), Darrell Whitley (Colorado State University), Pascal Kerschke (TU Dresden, ScaDS.AI Dresden/Leipzig)
• Conditional Direct Empirical Linkage Discovery for Solving Multi-Structured Problems
  Michal Witold Przewozniczek (Wroclaw University of Science and Technology), Peter Alexander Nicolaas Bosman (Centrum Wiskunde & Informatica), Anton Bouter (Centrum Wiskunde & Informatica), Arthur Guijt (Centrum Wiskunde & Informatica), Marcin Michal Komarnicki (Wroclaw University of Science and Technology), Dirk Thierens (Utrecht University)
• Enhancing Parameter Control Policies with State Information
  Denis Antipov (Sorbonne Université, CNRS, LIP6), Gianluca Covini (University of Pavia), Carola Doerr (Sorbonne Université, CNRS, LIP6)
• Empirical Linkage Discovery in Bi-Objective Optimization
  Michal Witold Przewozniczek (Wroclaw University of Science and Technology), Marcin Michal Komarnicki (Wroclaw University of Science and Technology), Renato Tinós (University of São Paulo)