DocumentCode
2092009
Title
Multiobjective-based concepts to handle constraints in evolutionary algorithms
Author
Mezura-Montes, Efrén ; Coello, Carlos A Coello
Author_Institution
Departamento de Ingenieria Electrica, Instituto Politecnico Nacional, Mexico City, Mexico
fYear
2003
fDate
8-12 Sept. 2003
Firstpage
192
Lastpage
199
Abstract
This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of some approaches developed under these concepts is provided. Additionally, a comparison of four representative techniques using well-known test functions is shown. Finally, the analysis of the results obtained, based on three main points (quality, consistency and diversity) and some conclusions and future trends are also provided.
Keywords
constraint handling; evolutionary computation; genetic algorithms; constraint handling; evolutionary algorithms; global optimization problems; multiobjective optimization; multiobjective-based concepts; Algorithm design and analysis; Benchmark testing; Computer science; Constraint optimization; Evolutionary computation; Linear programming; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science, 2003. ENC 2003. Proceedings of the Fourth Mexican International Conference on
Print_ISBN
0-7695-1915-6
Type
conf
DOI
10.1109/ENC.2003.1232894
Filename
1232894
Link To Document