Multi-objective particle swarm optimization using Pareto-based set and aggregation approach

作者：Huang, Song; Wang, Yan^*; Ji, Zhicheng

来源：Modern Physics Letters B, 2017, 31(19-21): 1740073.

DOI：10.1142/S0217984917400735

• Particle swarm optimization
• multi-objective problem
• Pareto-based set

Multi-objective optimization problems (MOPs) need to be solved in real world recently. In this paper, a multi-objective particle swarm optimization based on Pareto set and aggregation approach was proposed to deal with MOPs. Firstly, velocities and positions were updated similar to PSO. Then, global-best set was defined in particle swarm optimizer to preserve Pareto-based set obtained by the population. Specifically, a hybrid updating strategy based on Pareto set and aggregation approach was introduced to update the global-best set and local search was carried on global-best set. Thirdly, personal-best positions were updated in decomposition way, and global-best position was selected from global-best set. Finally, ZDT instances and DTLZ instances were selected to evaluate the performance of MULPSO and the results show validity of the proposed algorithm for MOPs.

• 出版日期2017-7-30
• 单位江南大学