Search Results - "Evolutionary algorithms, genetic algorithms (computational aspects)"

Contributors: Doerr, Carola, ITMO University Russia, Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS), Recherche Opérationnelle (RO), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ANR-11-LABX-0056,LMH,LabEx Mathématique Hadamard(2011)

Source: Proceedings of the 2020 Genetic and Evolutionary Computation Conference. :1295-1303

Subject Terms: FOS: Computer and information sciences, Evolutionary algorithms, genetic algorithms (computational aspects), [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], randomized search heuristics, Computer Science - Neural and Evolutionary Computing, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], 68Q17, evolutionary computation, Analysis of algorithms, Neural and Evolutionary Computing (cs.NE), F.2.2, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), runtime analysis

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Access URL: http://arxiv.org/pdf/2004.09613
http://arxiv.org/abs/2004.09613
https://zbmath.org/7535652
https://doi.org/10.1007/s00453-021-00881-0
https://link.springer.com/article/10.1007%2Fs00453-021-00881-0
https://hal.archives-ouvertes.fr/hal-03377095
https://dblp.uni-trier.de/db/journals/corr/corr2004.html#abs-2004-09613
https://arxiv.org/abs/2004.09613
https://arxiv.org/abs/2004.09613
https://ui.adsabs.harvard.edu/abs/2020arXiv200409613B/abstract
http://arxiv.org/pdf/2004.09613.pdf
https://hal.sorbonne-universite.fr/hal-02871956v1

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5

Academic Journal

Self-Adjusting Mutation Rates with Provably Optimal Success Rules: Self-adjusting mutation rates with provably optimal success rules

Authors: Doerr, Benjamin, Doerr, Carola, Lengler, Johannes

Contributors: Doerr, Carola, Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS), Recherche Opérationnelle (RO), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology Zürich (ETH Zürich), ANR-11-LABX-0056,LMH,LabEx Mathématique Hadamard(2011)

Source: Algorithmica. 83:3108-3147

Subject Terms: FOS: Computer and information sciences, Evolutionary algorithms, genetic algorithms (computational aspects), Randomized algorithms, [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], randomized search heuristics, parameter control, Computer Science - Neural and Evolutionary Computing, 0102 computer and information sciences, 02 engineering and technology, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], 01 natural sciences, evolutionary computation, 0202 electrical engineering, electronic engineering, information engineering, Analysis of algorithms, Neural and Evolutionary Computing (cs.NE), runtime analysis

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Access URL: https://hal.sorbonne-universite.fr/hal-02175768/file/bl%20pap162s3-file1%20%281%29.pdf
http://arxiv.org/abs/1902.02588
https://zbmath.org/7421502
https://doi.org/10.1007/s00453-021-00854-3
https://dumas.ccsd.cnrs.fr/LIP6/hal-02175768
http://arxiv.org/pdf/1902.02588.pdf
https://dblp.uni-trier.de/db/conf/gecco/gecco2019.html#DoerrDL19
https://hal.archives-ouvertes.fr/hal-02175768
https://hal.archives-ouvertes.fr/hal-03377092
https://dblp.uni-trier.de/db/journals/algorithmica/algorithmica83.html#DoerrDL21
https://link.springer.com/article/10.1007/s00453-021-00854-3
https://hal-polytechnique.archives-ouvertes.fr/hal-03377092v1
https://hal.sorbonne-universite.fr/hal-03377092v1
https://hal.sorbonne-universite.fr/hal-03377092v1/document
https://doi.org/10.1007/s00453-021-00854-3

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6

Academic Journal

A new taxonomy of global optimization algorithms

Authors: Jörg Stork, A. E. Eiben, Thomas Bartz-Beielstein

Source: Natural Computing. 21:219-242

Subject Terms: ddc:004, FOS: Computer and information sciences, Evolutionary algorithms, genetic algorithms (computational aspects), ddc:000, 0211 other engineering and technologies, 02 engineering and technology, Nonconvex programming, global optimization, Evolutionärer Algorithmus, taxonomy, 0202 electrical engineering, electronic engineering, information engineering, Globale Optimierung, surrogate, Neural and Evolutionary Computing (cs.NE), metaheuristics, Computer Science - Neural and Evolutionary Computing, hybrid optimization, Taxonomie, Approximation methods and heuristics in mathematical programming, 3. Good health, Metaheuristik, evolutionary computation, Fakultät für Informatik und Ingenieurwissenschaften (F10)

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Access URL: https://link.springer.com/content/pdf/10.1007/s11047-020-09820-4.pdf
http://arxiv.org/abs/1808.08818
https://zbmath.org/7733308
https://doi.org/10.1007/s11047-020-09820-4
https://research.vu.nl/en/publications/f4ff540b-8c20-4af3-95ca-f47e3e6b2075
https://doi.org/10.1007/s11047-020-09820-4
https://hdl.handle.net/1871.1/f4ff540b-8c20-4af3-95ca-f47e3e6b2075
https://link.springer.com/article/10.1007/s11047-020-09820-4
https://link.springer.com/content/pdf/10.1007/s11047-020-09820-4.pdf
https://research.vu.nl/en/publications/a-new-taxonomy-of-global-optimization-algorithms
https://arxiv.org/pdf/1808.08818
https://dblp.uni-trier.de/db/journals/corr/corr1808.html#abs-1808-08818
https://arxiv.org/abs/1808.08818
https://cos.bibl.th-koeln.de/files/753/Stor16acos-submitted.pdf
https://cos.bibl.th-koeln.de/frontdoor/index/index/searchtype/all/start/0/rows/20/languagefq/eng/subjectfq/Globale+Optimierung/docId/753
http://ui.adsabs.harvard.edu/abs/2018arXiv180808818S/abstract
https://cos.bibl.th-koeln.de/files/753/Stor16acos-submitted.pdf
https://epb.bibl.th-koeln.de/files/2246/s11047-020-09820-4.pdf

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7

Academic Journal

Tail bounds on hitting times of randomized search heuristics using variable drift analysis

Authors: Lehre, P. K., Witt, C.

Source: Lehre, P K & Witt, C 2021, ' Tail bounds on hitting times of randomized search heuristics using variable drift analysis ', Combinatorics Probability and Computing, vol. 30, no. 4, pp. 550–569 . https://doi.org/10.1017/S0963548320000565

Subject Terms: Evolutionary algorithms, genetic algorithms (computational aspects), 4. Education, Randomized algorithms, 0202 electrical engineering, electronic engineering, information engineering, 0102 computer and information sciences, 02 engineering and technology, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), 01 natural sciences

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Access URL: https://backend.orbit.dtu.dk/ws/files/234770969/tail_bounds_on_hitting_times_of_randomized_search_heuristics_using_variable_drift_analysis.pdf
https://orbit.dtu.dk/en/publications/tail-bounds-on-hitting-times-of-randomized-search-heuristics-usin
https://backend.orbit.dtu.dk/ws/files/234770969/tail_bounds_on_hitting_times_of_randomized_search_heuristics_using_variable_drift_analysis.pdf
https://www.cambridge.org/core/journals/combinatorics-probability-and-computing/article/tail-bounds-on-hitting-times-of-randomized-search-heuristics-using-variable-drift-analysis/F30499B93D4498D404E00206005A999A
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/F30499B93D4498D404E00206005A999A/S0963548320000565a.pdf/div-class-title-tail-bounds-on-hitting-times-of-randomized-search-heuristics-using-variable-drift-analysis-div.pdf
https://orbit.dtu.dk/en/publications/bfdcc357-ac66-4d8d-bb15-c5701c9ed438

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8

Academic Journal

Novel biogeography-based optimization algorithm with hybrid migration and global-best Gaussian mutation

Authors: Zihao Fu, Xinming Zhang, Shangwang Liu, Guoqi Liu, Shuangqian Li, Yun Jiang, Doudou Wang, Wentao Mao

Source: Applied Mathematical Modelling. 86:74-91

Subject Terms: evolutionary algorithm, biogeography-based optimization algorithm, Evolutionary algorithms, genetic algorithms (computational aspects), $K$-menas clustering, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Gaussian mutation, 02 engineering and technology, minimum spanning tree, migration, Approximation methods and heuristics in mathematical programming

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Access URL: https://www.sciencedirect.com/science/article/pii/S0307904X20302420

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9

Academic Journal

Self-adjusting evolutionary algorithms for multimodal optimization

Authors: Amirhossein Rajabi, Carsten Witt

Source: Rajabi, A & Witt, C 2020, Self-adjusting evolutionary algorithms for multimodal optimization . in Proceedings of the 2020 Genetic and Evolutionary Computation Conference . Association for Computing Machinery, pp. 1314-1322, 2020 Genetic and Evolutionary Computation Conference, Cancun, Mexico, 08/07/2020 . https://doi.org/10.1145/3377930.3389833

Subject Terms: multimodal functions, FOS: Computer and information sciences, Evolutionary algorithms, genetic algorithms (computational aspects), Multimodal functions, randomized search heuristics, self-adjusting algorithms, Computer Science - Neural and Evolutionary Computing, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Self-adjusting algorithms, Randomised search heuristics, 0202 electrical engineering, electronic engineering, information engineering, Analysis of algorithms, Runtime analysis, Neural and Evolutionary Computing (cs.NE), Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), runtime analysis

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Access URL: https://backend.orbit.dtu.dk/ws/files/247787189/Rajabi_Witt2020_GECCO.pdf
http://arxiv.org/abs/2004.03266
https://arxiv.org/abs/2004.03266
https://ui.adsabs.harvard.edu/abs/2020arXiv200403266R/abstract
https://arxiv.org/pdf/2004.03266.pdf
https://dblp.uni-trier.de/db/journals/corr/corr2004.html#abs-2004-03266
https://dl.acm.org/doi/pdf/10.1145/3377930.3389833
https://orbit.dtu.dk/en/publications/2f0d9a20-b131-4308-9724-13ebf8c68d76

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10

Academic Journal

Does comma selection help to cope with local optima?

Authors: Benjamin Doerr

Contributors: École polytechnique (X), Institut Polytechnique de Paris (IP Paris), Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS), ANR-11-LABX-0056,LMH,LabEx Mathématique Hadamard(2011)

Source: Proceedings of the 2020 Genetic and Evolutionary Computation Conference. :1304-1313

Subject Terms: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Evolutionary algorithms, genetic algorithms (computational aspects), Computer Science - Artificial Intelligence, Computer Science - Data Structures and Algorithms, Computer Science - Neural and Evolutionary Computing, [INFO]Computer Science [cs], Analysis of algorithms, Data Structures and Algorithms (cs.DS), Neural and Evolutionary Computing (cs.NE), Approximation methods and heuristics in mathematical programming

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Access URL: https://dl.acm.org/doi/pdf/10.1145/3377930.3389823
http://arxiv.org/pdf/2004.01274
http://arxiv.org/abs/2004.01274
https://zbmath.org/7535649
https://doi.org/10.1007/s00453-021-00896-7
https://dl.acm.org/doi/pdf/10.1145/3377930.3389823
https://hal.archives-ouvertes.fr/hal-03278163/document
https://dblp.uni-trier.de/db/journals/corr/corr2004.html#abs-2004-01274
https://archivesic.ccsd.cnrs.fr/LIX/hal-03278163v1
https://ui.adsabs.harvard.edu/abs/2020arXiv200401274D/abstract
http://arxiv.org/pdf/2004.01274.pdf
https://arxiv.org/abs/2004.01274

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11

Academic Journal

A Tight Runtime Analysis for the $${(\mu + \lambda )}$$ EA: A tight runtime analysis for the $(\mu + \lambda)$ EA

Authors: Denis Antipov, Benjamin Doerr

Contributors: National Research University of Information Technologies, Mechanics and Optics St. Petersburg (ITMO), Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS)

Source: Algorithmica. 83:1054-1095

Subject Terms: Evolutionary algorithms, genetic algorithms (computational aspects), [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], 0202 electrical engineering, electronic engineering, information engineering, Computer Science - Neural and Evolutionary Computing, Analysis of algorithms, 0102 computer and information sciences, 02 engineering and technology, evolutionary algorithms, 01 natural sciences, runtime analysis

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Access URL: http://arxiv.org/pdf/1812.11061
http://arxiv.org/abs/1812.11061
https://hal.ip-paris.fr/hal-03353025v1
https://link.springer.com/article/10.1007/s00453-020-00731-5
https://hal.archives-ouvertes.fr/hal-03353025
https://hal.archives-ouvertes.fr/hal-03353025/document
https://dblp.uni-trier.de/db/journals/algorithmica/algorithmica83.html#AntipovD21

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12

Academic Journal

On the benefits of populations for the exploitation speed of standard steady-state genetic algorithms

Authors: Dogan Corus, Pietro S. Oliveto

Source: Proceedings of the Genetic and Evolutionary Computation Conference. :1452-1460

Subject Terms: FOS: Computer and information sciences, crossover, Evolutionary algorithms, genetic algorithms (computational aspects), 13. Climate action, population-based algorithms, Computer Science - Neural and Evolutionary Computing, Analysis of algorithms, Neural and Evolutionary Computing (cs.NE), recombination, genetic algorithms, runtime analysis

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Access URL: http://eprints.whiterose.ac.uk/144388/1/1903.10976v1.pdf
https://link.springer.com/content/pdf/10.1007/s00453-020-00743-1.pdf
http://arxiv.org/abs/1903.10976
https://zbmath.org/7272777
https://doi.org/10.1007/s00453-020-00743-1
http://arxiv.org/pdf/1903.10976.pdf
https://arxiv.org/abs/1903.10976
https://dblp.uni-trier.de/db/conf/gecco/gecco2019.html#CorusO19
https://eprints.whiterose.ac.uk/164018/
http://dblp.uni-trier.de/db/journals/corr/corr1903.html#abs-1903-10976
https://dl.acm.org/doi/pdf/10.1145/3321707.3321783
https://dblp.uni-trier.de/db/journals/algorithmica/algorithmica82.html#CorusO20
https://link.springer.com/article/10.1007/s00453-020-00743-1
https://link.springer.com/content/pdf/10.1007/s00453-020-00743-1.pdf

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13

Academic Journal

Analyzing randomized search heuristics via stochastic domination

Authors: Benjamin Doerr

Contributors: École polytechnique (X), Institut Polytechnique de Paris (IP Paris), Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS)

Source: Theoretical Computer Science. 773:115-137

Subject Terms: Evolutionary algorithms, genetic algorithms (computational aspects), Randomized algorithms, 0211 other engineering and technologies, [INFO]Computer Science [cs], Analysis of algorithms, 0102 computer and information sciences, 02 engineering and technology, evolutionary algorithms, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), 01 natural sciences, runtime analysis

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Access URL: https://www.sciencedirect.com/science/article/am/pii/S0304397518305954
https://arxiv.org/abs/1801.04487
https://dblp.uni-trier.de/db/journals/tcs/tcs773.html#Doerr19
https://ru.arxiv.org/abs/1801.04487
https://core.ac.uk/display/146481142
https://www.sciencedirect.com/science/article/pii/S0304397518305954
https://arxiv.org/pdf/1801.04487

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14

Academic Journal

Runtime Analysis for Self-adaptive Mutation Rates: Runtime analysis for self-adaptive mutation rates

Authors: Benjamin Doerr, Carsten Witt, Jing Yang

Contributors: École polytechnique (X), Institut Polytechnique de Paris (IP Paris), Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS), Department of Applied Mathematics and Computer Science Lyngby (DTU Compute), Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Eberhard Karls Universität Tübingen = University of Tübingen, ANR-11-LABX-0056,LMH,LabEx Mathématique Hadamard(2011)

Source: Algorithmica. 83:1012-1053

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Evolutionary algorithms, genetic algorithms (computational aspects), Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing, Machine Learning (cs.LG), self-adaptive, Artificial Intelligence (cs.AI), Computer Science - Data Structures and Algorithms, [INFO]Computer Science [cs], Analysis of algorithms, Data Structures and Algorithms (cs.DS), Neural and Evolutionary Computing (cs.NE), evolutionary algorithms, runtime analysis

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Access URL: https://backend.orbit.dtu.dk/ws/files/151866568/p1475_doerr.pdf
http://arxiv.org/abs/1811.12824
https://zbmath.org/7331693
https://doi.org/10.1007/s00453-020-00726-2
https://link.springer.com/10.1007/s00453-020-00726-2
https://link.springer.com/article/10.1007/s00453-020-00726-2
https://dblp.uni-trier.de/db/journals/algorithmica/algorithmica83.html#DoerrWY21
https://orbit.dtu.dk/en/publications/runtime-analysis-for-self-adaptive-mutation-rates-2
https://doi.org/10.1007/s00453-020-00726-2
https://dblp.uni-trier.de/db/journals/corr/corr1811.html#abs-1811-12824
http://ui.adsabs.harvard.edu/abs/2018arXiv181112824D/abstract
https://doi.acm.org/10.1145/3205455.3205569
http://dblp.uni-trier.de/db/conf/gecco/gecco2018.html#DoerrW018

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15

Academic Journal

Optimal Parameter Choices via Precise Black-Box Analysis: Optimal parameter choices via precise black-box analysis

Authors: Doerr, Benjamin, Doerr, Carola, Yang, Jing

Contributors: Doerr, Carola, Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS), Recherche Opérationnelle (RO), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU), ANR-11-LABX-0056,LMH,LabEx Mathématique Hadamard(2011)

Source: Proceedings of the Genetic and Evolutionary Computation Conference 2016. :1123-1130

Subject Terms: FOS: Computer and information sciences, theory of evolutionary computation, Evolutionary algorithms, genetic algorithms (computational aspects), [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], parameter control, Computer Science - Neural and Evolutionary Computing, 0102 computer and information sciences, 02 engineering and technology, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], 01 natural sciences, black-box complexity, 0202 electrical engineering, electronic engineering, information engineering, Analysis of algorithms, Neural and Evolutionary Computing (cs.NE), runtime analysis