A novel multi-objective PSO algorithm based on completion-checking

作者：Fan, Rui; Wei, Lixin^*; Li, Xin; Hu, Ziyu

来源：Journal of Intelligent and Fuzzy Systems, 2018, 34(1): 321-333.

DOI：10.3233/JIFS-171291

• Multi-objective optimization
• evolutionary algorithms
• decomposition
• particle swarm optimization

Multi-objective particle swarm optimization (MOPSO) algorithms are shown to have enormous potential in solving multi-objective optimization problems (MOPs). However, most MOPSO is difficult to balance the exploration and exploitation, which may cause some problems to find true Pareto fronts when tackling some complex MOPs. A multi-objective decomposition particle swarm optimization based on completion-checking (C-DMOPSO) is improved in this paper. The updating mode of velocity is changed dynamically according to the algorithm's evolutionary process, which balances the exploration and exploitation effectively. In addition, simulated binary crossover and opposition-based learning are adopted to improve the diversity, and the archive set strategy is added to store the optimal solutions. Furthermore, polynomial mutation is performed in archive. The effectiveness of the proposed algorithm is tested by nineteen standard functions, including ZDT, DTLZ and UF, and the experimental results show that C-DMOPSO performs better on most of test problems.

• 出版日期2018
• 单位中国科学院电工研究所; 燕山大学