Evolutionary computation in stochastic environments

This book develops efficient methods for the application of Evolutionary Algorithms on stochastic problems. To achieve this, procedures for statistical selection are systematically analyzed with respect to different measures and significantly improved. It is shown how to adapt one of the best proced...

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Главный автор: Schmidt, Christian
Формат: Online
Язык:английский
Опубликовано: KIT Scientific Publishing 2021
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Online-ссылка:34679
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author Schmidt, Christian
author_browse Schmidt, Christian
author_facet Schmidt, Christian
author_sort Schmidt, Christian
collection Directory of Open Access Books
description This book develops efficient methods for the application of Evolutionary Algorithms on stochastic problems. To achieve this, procedures for statistical selection are systematically analyzed with respect to different measures and significantly improved. It is shown how to adapt one of the best procedures for the needs of Evolutionary Algorithms and Evolutionary operators for efficient implementation in stochastic environments are identified.
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institution Directory of Open Access Books
language eng
publishDate 2021
publishDateRange 2021
publishDateSort 2021
publisher KIT Scientific Publishing
publisherStr KIT Scientific Publishing
record_format ojs
spelling doab-20.500.12854ir-471482023-12-20T18:40:46Z Evolutionary computation in stochastic environments Schmidt, Christian QA75.5-76.95 Evolutionary Algorithm Uncertainty Simulation based optimization Bayes Ranking & Selection Genetic Algorithms bic Book Industry Communication::U Computing & information technology::UY Computer science This book develops efficient methods for the application of Evolutionary Algorithms on stochastic problems. To achieve this, procedures for statistical selection are systematically analyzed with respect to different measures and significantly improved. It is shown how to adapt one of the best procedures for the needs of Evolutionary Algorithms and Evolutionary operators for efficient implementation in stochastic environments are identified. 2021-02-11T13:12:56Z 2021-02-11T13:12:56Z 2019-07-30 20:01:58 2007 book 34679 9783866441286 https://directory.doabooks.org/handle/20.500.12854/47148 eng image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International https://www.ksp.kit.edu/9783866441286 KIT Scientific Publishing 10.5445/KSP/1000006634 10.5445/KSP/1000006634 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783866441286 VII, 128 p. open access
spellingShingle QA75.5-76.95
Evolutionary Algorithm
Uncertainty
Simulation based optimization
Bayes
Ranking & Selection
Genetic Algorithms
bic Book Industry Communication::U Computing & information technology::UY Computer science
Schmidt, Christian
Evolutionary computation in stochastic environments
title Evolutionary computation in stochastic environments
title_full Evolutionary computation in stochastic environments
title_fullStr Evolutionary computation in stochastic environments
title_full_unstemmed Evolutionary computation in stochastic environments
title_short Evolutionary computation in stochastic environments
title_sort evolutionary computation in stochastic environments
topic QA75.5-76.95
Evolutionary Algorithm
Uncertainty
Simulation based optimization
Bayes
Ranking & Selection
Genetic Algorithms
bic Book Industry Communication::U Computing & information technology::UY Computer science
topic_facet QA75.5-76.95
Evolutionary Algorithm
Uncertainty
Simulation based optimization
Bayes
Ranking & Selection
Genetic Algorithms
bic Book Industry Communication::U Computing & information technology::UY Computer science
url 34679
work_keys_str_mv AT schmidtchristian evolutionarycomputationinstochasticenvironments