Abstract: Using simple and efficient neighbouring updating as the main selection strategy,MOEA/D focuses more on local replacement.In this case,it ignores the individual’s global fitness and makes algorithm get into local minimum ea-sily.In order to overcome the flaw of MOEA/D in local replacement,an improved MOEA/D which takes the global replacement and local updating into account based on self-adaptive selection strategy(MOEA/D-AS) was proposed.Firstly,a new selection strategy based on perfect matching of bipartite graph(KMS) is applied to select the elite solutions from a global perspective by using matching relationship between sub-problems and indivdual soltuions.Then,using the evolutionary information of the population,a matching disorder judgment mechanism was proposed.At last,on the basis of comprehensive analysis of the advantages of neighbourhood update strategy and KMS,the new algorithm can adaptively choose the most suitable selection strategy by using the disorder judgment mechanism to improve robustness and efficiency.The proposed algorithm was compared with some state-of-the-art versions of MOEA/D on LZ09,DTLZ and CEC09 Benchmarks.The values of Spread and IGD show that MOEA/D-AS has certain advantages than other algorithms in terms of convergence and distribution,and suggest that the self-adaptive selection strategy can effectively guide the selection process of elite solution.

Key words: MOEA/D,Perfect matching of bipartite graph,Disorder judgment,Self-adaptive selection strategy