Augmenting SPEA2 with K-Random Competitive Coevolution for Enhanced Evolutionary Multi-objective Optimization

被引：0
|
作者：
Tan, Tse Guan
Teo, Jason
Lau, Hui Keng
机构：
来源：
INTERNATIONAL SYMPOSIUM OF INFORMATION TECHNOLOGY 2008, VOLS 1-4, PROCEEDINGS: COGNITIVE INFORMATICS: BRIDGING NATURAL AND ARTIFICIAL KNOWLEDGE | 2008年
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D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
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页码：1579 / 1584
页数：6
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