Augmenting SPEA2 with K-Random competitive coevolution for enhanced evolutionary multi-objective optimization

Author

Tan, Tse Guan ; Teo, Jason ; Lau, Hui Keng

Author_Institution

Centre for Artificial Intell., Bangalore

Volume

3

fYear

2008

Firstpage

1

Lastpage

6

Abstract

One new algorithm is being proposed, which is the integration between one multiobjective evolutionary algorithm (MOEA): strength Pareto evolutionary algorithm 2 (SPEA2) and competitive coevolution using k-random opponents competitive fitness strategy. The resulting algorithm is referred to as SPEA2-CE-KR. This proposed algorithm was benchmarked against the original SPEA2 using seven DTLZ test problems having 3 to 5 objectives. Overall, reveal that SPEA2-CE-KR performed well for the spacing and coverage metrics.

Keywords

Pareto optimisation; evolutionary computation; random processes; evolutionary multiobjective optimization; k-random competitive coevolution; k-random opponent competitive fitness; multiobjective evolutionary algorithm; strength Pareto evolutionary algorithm 2; Artificial intelligence; Benchmark testing; Constraint optimization; Decision feedback equalizers; Evolutionary computation; Pareto optimization; Performance evaluation; Round robin;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology, 2008. ITSim 2008. International Symposium on

Print_ISBN

978-1-4244-2327-9

Electronic_ISBN

978-1-4244-2328-6

Type

conf

DOI

10.1109/ITSIM.2008.4631990

Filename

4631990