Li Ma1, Cai Dai1,*, Xingsi Xue2, Cheng Peng3
CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 997-1026, 2025, DOI:10.32604/cmc.2024.057168
- 03 January 2025
Abstract The multi-objective particle swarm optimization algorithm (MOPSO) is widely used to solve multi-objective optimization problems. In the article, a multi-objective particle swarm optimization algorithm based on decomposition and multi-selection strategy is proposed to improve the search efficiency. First, two update strategies based on decomposition are used to update the evolving population and external archive, respectively. Second, a multi-selection strategy is designed. The first strategy is for the subspace without a non-dominated solution. Among the neighbor particles, the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle… More >
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