2026-07-26T19:54:17Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:22728 2026-04-20T12:49:34Z ddc:004 open_access

Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 24271) Auger, Anne Glasmachers, Tobias Krejca, Martin S. Lengler, Johannes Jungeilges, Alexander Black-Box Optimization Heuristics Evolution Strategies Genetic and Evolutionary Algorithms Runtime and Convergence Analysis Stochastic Processes This report documents the program and the outcomes of Dagstuhl Seminar 24271 "Theory of Randomized Optimization Heuristics", which marks the twelfth installment of our biennial seminar series. This iteration saw a lot of discussion on important, yet rarely analyzed topics in the domain of heuristic optimization, such as mixed-integer problems, permutation spaces, and coevolution. Moreover, it aimed at unifying existing results by discussing mathematical tools (such as drift analysis), the structure of discrete problems, and a common framework for theoretical analysis and practical implementation. Last, more recent and important topics, such as constrained and multi-objective optimization, were a major part of the seminar. We had a vivid exchange in various breakout sessions and different talks, with a great mix of junior and senior participants, which was very positively received. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Anne Auger and Tobias Glasmachers and Martin S. Krejca and Johannes Lengler and Alexander Jungeilges 2024 Is Part Of Dagstuhl Reports, Volume 14, Issue 6 (2024) Article Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagRep.14.6.215 urn:nbn:de:0030-drops-227286 https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.6.215 eng https://creativecommons.org/licenses/by/4.0/legalcode