Multi-objective particle swarm optimization algorithm based on leader combination of decomposition and dominance

作者：Hu, Ziyu; Yang, Jingming; Cui, Huihui; Sun, Hao^*; Wei, Lixin

来源：Journal of Intelligent and Fuzzy Systems, 2017, 33(3): 1577-1588.

DOI：10.3233/JIFS-17336

• Intelligence algorithm
• multi-objective optimization
• particle swarm optimization
• soft computing

Convergence and well-distribution are two basic issues in multi-objective optimization problems(MOPs). However, it is hard to optimize them simultaneously for the selection of leader particle is not always leading the population to the Pareto front. To make a better performance of multi-objective particle swarm optimization algorithm(MOPSO), decomposition and domination leadership particle selection mechanism have been introduced into MOPSO. Decomposition leader particle selection mechanism is used to keep the swarm with diversity, while domination leader particle selection mechanism make the particles move to the Pareto front. The performance of our proposed method is validated based inverted generation distance(IGD) and compared with five state-of-the-art algorithms on a number of unconstrained benchmark problems. Empirical analysis demonstrates the superiority of our proposed method on both proximity and diversity.

• 出版日期2017
• 单位燕山大学