Performance Scalability of a Cooperative Coevolution Multiobjective Evolutionary Algorithm

摘要

Recently,numerous Multiobjective Evolutionary Algorithms (MOEAs) have been presented to solve real life problems.However,a number of issues still remain with regards to MOEAs such as convergence to the true Pareto front as well as scalability to many objective problems rather than just bi-objective problems.The performance of these algorithms may be augmented by incorporating the coevolutionary concept.Hence,in this paper,a new algorithm for multiobjective optimization called SPEA2-CC is illustrated SPEA2-CC combines an MOEA,Strength Pareto Evolutionary Algorithm 2 (SPEA2) with Cooperative Coevolution (CC).Scalability tests have been conducted to evaluate and compare the SPEA2-CC against the original SPEA2 for seven DTLZ test problems with a set of objectives (3 to 5 objectives).The results show clearly that the performance scalability of SPEA2-CC was significantly better compared to the original SPEA2 as the number of objectives becomes higher.