Using multi-objective evolutionary algorithms for single-objective optimization

In recent decades, several multi-objective evolutionary algorithms have been successfully applied to a wide variety of multi-objective optimization problems. Along the way, several new concepts, paradigms and methods have emerged. Additionally, some authors have claimed that the application of multi...

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Vydáno v:4OR Ročník 11; číslo 3; s. 201 - 228
Hlavní autoři: Segura, Carlos, Coello Coello, Carlos A., Miranda, Gara, León, Coromoto
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2013
Springer Nature B.V
Témata:
Business and Management
Evolutionary algorithms
Genetic algorithms
Heuristic
Industrial and Production Engineering
Invited Survey
Mathematical functions
Mathematical programming
Multiple objective analysis
Objectives
Operations research
Operations Research/Decision Theory
Optimization
90C59 Approximation methods and heuristics
90 Operations Research and Mathematical Programming
Diversity preservation
Multi-objective optimization
Multiobjectivization
Single-objective optimization
90C29 Multi-objective and goal programming
Constrained optimization
ISSN:1619-4500, 1614-2411
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Popis
Shrnutí:In recent decades, several multi-objective evolutionary algorithms have been successfully applied to a wide variety of multi-objective optimization problems. Along the way, several new concepts, paradigms and methods have emerged. Additionally, some authors have claimed that the application of multi-objective approaches might be useful even in single-objective optimization. Thus, several guidelines for solving single-objective optimization problems using multi-objective methods have been proposed. This paper offers a survey of the main methods that allow the use of multi-objective schemes for single-objective optimization. In addition, several open topics and some possible paths of future work in this area are identified.
Bibliografie:ObjectType-Article-1
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ISSN:1619-4500
1614-2411
DOI:10.1007/s10288-013-0248-x