Multi-objective optimization decomposition algorithm based on differentiated selection strategy

Yan Xiaofan

Volume : VIII, Issue : IX, September - 2019

Multi-objective optimization decomposition algorithm based on differentiated selection strategy

Yan Xiaofan

Abstract :

Decomposition-based multi-objective evolutionary algorithm can obtain effective solution sets for solving multi-objective optimization problems. However, the random way of selecting individuals is not conducive to the preservation of good solutions and reduces the convergence speed of the algorithm. In order to solve this problem, a multi-objective optimization decomposition algorithm based on differentiated selection strategy (MOEA/D-DFS) is proposed. The differentiated selection strategy adopted by the algorithm is to select the non-dominant solution from population, using the method of individual selection in NSGA-II. Meanwhile, the strategy of first substitution and stopping is adopted when the offspring replace parent. It is conducive to enhancing the diversity of the population. The experimental results of ZDT test function shows that the algorithm is superior to other algorithm in convergence and diversity, and has certain advantages in solving performance.