DocumentCode :
3202997
Title :
Empirical analysis of Competitive Coevolution Multiobjective Evolutionary Algorithm
Author :
Tan, Tse Guan ; Teo, Jason ; Lau, Hui Keng
Author_Institution :
Centre for Artificial Intell., Univ. Malaysia Sabah, Kota Kinabalu
fYear :
2007
fDate :
25-28 Nov. 2007
Firstpage :
501
Lastpage :
504
Abstract :
The integration between strength Pareto Evolutionary algorithm 2 (SPEA2) and competitive coevolution (CE) concept is presented in this paper, a strategy for solving an optimization problem with three scalable objectives. The Hall of Fame (HOF) competitive fitness function is used to implement the CE. This proposed algorithm referred to as SPEA2-CE-HOF. The performance between SPEA2-CE-HOF is compared against original SPEA2 in solving problems in the DTLZ suite having three to five objectives. The results showed that the SPEA2-CE-HOF performed better than SPEA2 in most of the DTLZ test problems for the generational distance. However the proposed algorithm performed average for the coverage metric.
Keywords :
Pareto optimisation; evolutionary computation; competitive coevolution multiobjective evolutionary algorithm; competitive fitness function; optimization; strength Pareto evolutionary algorithm; Algorithm design and analysis; Artificial intelligence; Competitive intelligence; Evolutionary computation; Genetic algorithms; Intelligent systems; Pareto analysis; Pareto optimization; Performance evaluation; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-1355-3
Electronic_ISBN :
978-1-4244-1356-0
Type :
conf
DOI :
10.1109/ICIAS.2007.4658439
Filename :
4658439
Link To Document :
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