Zobrazeno 1 - 10
of 126
pro vyhledávání: '"Dirk Sudholt"'
Publikováno v:
ACM Transactions on Evolutionary Learning and Optimization. 2:1-39
The self-adjusting (1 + (λ, λ)) GA is the best known genetic algorithm for problems with a good fitness-distance correlation as in OneMax . It uses a parameter control mechanism for the parameter λ that governs the mutation strength and the number
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03dfcb83b96917d9b956c383a50112a1
https://doi.org/10.1145/3564755
https://doi.org/10.1145/3564755
Autor:
Carlo Kneissl, Dirk Sudholt
Publikováno v:
Evolutionary Computation in Combinatorial Optimization ISBN: 9783031300349
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c40ad558567f19c03ae7f3c7cbaf48ec
https://doi.org/10.1007/978-3-031-30035-6_12
https://doi.org/10.1007/978-3-031-30035-6_12
Publikováno v:
Algorithmica. 84:1603-1658
Recent progress in the runtime analysis of evolutionary algorithms (EAs) has allowed the derivation of upper bounds on the expected runtime of standard steady-state genetic algorithms (GAs). These upper bounds have shown speed-ups of the GAs using cr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::131d70ce67ef7da357e3f6affbf79f67
https://doi.org/10.1007/s00453-021-00893-w
https://doi.org/10.1007/s00453-021-00893-w
Publikováno v:
Proceedings of the Genetic and Evolutionary Computation Conference.
The compact genetic algorithm (cGA) is an non-elitist estimation of distribution algorithm which has shown to be able to deal with difficult multimodal fitness landscapes that are hard to solve by elitist algorithms. In this paper, we investigate the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad88c35aa1f1a98f976c21822e18ea52
https://doi.org/10.1145/3512290.3528776
https://doi.org/10.1145/3512290.3528776
Autor:
Jakob Bossek, Dirk Sudholt
Publikováno v:
Theoretical Computer Science. 950:113757
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::307426c66955bfaa4713fdfbf4a50373
https://doi.org/10.1016/j.tcs.2023.113757
https://doi.org/10.1016/j.tcs.2023.113757
Publikováno v:
Theoretical Computer Science. 832:123-142
Parent selection in evolutionary algorithms for multi-objective optimisation is usually performed by dominance mechanisms or indicator functions that prefer non-dominated points. We propose to refine the parent selection on evolutionary multi-objecti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c7ebbac05b0d5d1876ebfc432823b20
https://doi.org/10.1016/j.tcs.2018.06.009
https://doi.org/10.1016/j.tcs.2018.06.009
Autor:
Edgar Covantes Osuna, Dirk Sudholt
Publikováno v:
IEEE Transactions on Evolutionary Computation. 24:581-592
Many real-world optimization problems lead to multimodal domains and require the identification of multiple optima. Crowding methods have been developed to maintain population diversity, to investigate many peaks in parallel and to reduce genetic dri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bfe6d42833b1b7f85d4c82361f1b9725
https://doi.org/10.1109/tevc.2019.2914606
https://doi.org/10.1109/tevc.2019.2914606
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031147203
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43fb108347a873069b8129806662c822
https://doi.org/10.1007/978-3-031-14721-0_32
https://doi.org/10.1007/978-3-031-14721-0_32
We contribute to the theoretical understanding of randomized search heuristics for dynamic problems. We consider the classical vertex coloring problem on graphs and investigate the dynamic setting where edges are added to the current graph. We then a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f018b481e6cc2da096b429ae9415af9c
https://eprints.whiterose.ac.uk/178846/1/Bossek2021_Article_TimeComplexityAnalysisOfRandom.pdf
https://eprints.whiterose.ac.uk/178846/1/Bossek2021_Article_TimeComplexityAnalysisOfRandom.pdf
Autor:
Dirk Sudholt, Jakob Bossek
Publikováno v:
FOGA
Most runtime analyses of randomised search heuristics focus on the expected number of function evaluations to find a unique global optimum. We ask a fundamental question: if additional search points are declared optimal, or declared as desirable targ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd8bb8627905d4660c73739165b079a7
https://doi.org/10.1145/3450218.3477309
https://doi.org/10.1145/3450218.3477309