Parallel multi-agent real-coded genetic algorithm for large-scale black-box single-objective optimisation

There is an ongoing evolution involving a new approach to large-scale optimisations based on co-evolutionary searches using interacting heterogeneous agent-processes via the implementation of synchronised genetic algorithms with local populations. The individualisation of heuristic operators at the...

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Vydané v:	Knowledge-based systems Ročník 174; s. 103 - 122
Hlavní autori:	Akopov, Andranik S., Beklaryan, Levon A., Thakur, Manoj, Verma, Bhisham Dev
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 15.06.2019 Elsevier Science Ltd
Predmet:	Agents Algorithms Biological evolution Black-box single-objective optimisation Computer simulation Crossovers Economic models Genetic algorithms Genetics Heuristic Multi-agent genetic algorithms Multiagent systems Objectives Operators Optimization Process parameters Real-coded genetic algorithms Searching Simulation Simulation modelling World problems Multi-agent genetic algorithms Real-coded genetic algorithms Black-box single-objective optimisation Simulation modelling
ISSN:	0950-7051, 1872-7409
On-line prístup:	Získať plný text
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