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DOI: 10.4230/DagRep.9.10.61
URN: urn:nbn:de:0030-drops-118567
URL: https://drops.dagstuhl.de/opus/volltexte/2020/11856/
Doerr, Carola ; Fonseca, Carlos M. ; Friedrich, Tobias ; Yao, Xin
Weitere Beteiligte (Hrsg. etc.): Carola Doerr and Carlos M. Fonseca and Tobias Friedrich and Xin Yao
Theory of Randomized Optimization Heuristics (Dagstuhl Reports 19431)
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Abstract
This report documents the activities of Dagstuhl Seminar 19431 on Theory of Randomized Optimization Heuristics. 46 researchers from Europe, Australia, Asia, and North America have come together to discuss ongoing research. This tenth edition of the seminar series had three focus topics: (1) relation between optimal control and heuristic optimization, (2) benchmarking optimization heuristics, and (3) the interfaces between continuous and discrete optimization. Several breakout sessions have provided ample opportunity to brainstorm on recent developments in the research landscape, to discuss and solve open problems, and to kick-start new research initiatives.
BibTeX - Entry
@Article{doerr_et_al:DR:2020:11856,
author = {Carola Doerr and Carlos M. Fonseca and Tobias Friedrich and Xin Yao},
title = {{Theory of Randomized Optimization Heuristics (Dagstuhl Reports 19431)}},
pages = {61--94},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2020},
volume = {9},
number = {10},
editor = {Carola Doerr and Carlos M. Fonseca and Tobias Friedrich and Xin Yao},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2020/11856},
URN = {urn:nbn:de:0030-drops-118567},
doi = {10.4230/DagRep.9.10.61},
annote = {Keywords: algorithms and complexity, evolutionary algorithms, machine learning, optimization, soft computing}
}
| Keywords: | algorithms and complexity, evolutionary algorithms, machine learning, optimization, soft computing | |
| Seminar: | Dagstuhl Reports, Volume 9, Issue 10 | |
| Issue date: | 2020 | |
| Date of publication: | 26.02.2020 |
