Multiobjective Optimization at Evolutionary Search with Binary Choice Relations

A multiobjective optimization problem is considered, in which binary choice relations are used instead of optimized functions. To solve this problem, it is proposed to use an evolutionary random search algorithm, in which the function of choice in the form of a lock is used instead of the choice fun...

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Vydané v:Cybernetics and systems analysis Ročník 56; číslo 3; s. 449 - 454
Hlavní autori: Irodov, V. F., Barsuk, R. V., Chornomorets, H. Ya
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.05.2020
Springer
Springer Nature B.V
Predmet:
Algorithms
Analysis
Artificial Intelligence
Control
Convergence
Evolutionary algorithms
Genetic algorithms
Mathematics
Mathematics and Statistics
Multiple objective analysis
Optimization
Processor Architectures
Search algorithms
Searches and seizures
Software Engineering/Programming and Operating Systems
Systems Theory
multiobjective optimization
evolutionary search
binary choice relations
ISSN:1060-0396, 1573-8337
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Popis
Shrnutí:A multiobjective optimization problem is considered, in which binary choice relations are used instead of optimized functions. To solve this problem, it is proposed to use an evolutionary random search algorithm, in which the function of choice in the form of a lock is used instead of the choice function in the form of a preference,. The convergence of the proposed evolutionary algorithms is analyzed, and sufficient conditions for convergence are formulated. The results of the proposed evolutionary search are compared with the results of well-known evolutionary algorithms for one test problem.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1060-0396
1573-8337
DOI:10.1007/s10559-020-00260-7