关键词: 领地行为, 粒子群算法, 板翅式换热器, 逼近理想解法

Abstract: Aiming at the problem that Multi-Objective Particle Swarm Optimization (MOPSO) was easy fell into partial optimal solution,a Territorial Behavior-based Multi-Objective Particle Swarm Optimization (TBMOPSO) was proposed.Through imitating the three subbehaviors of occupying territory,self-improvement and finding new territory in animal territorial behavior,the dynamic update of territory radius was presented to widen search scope of the population|the crossover operation and Gauss mutation were applied to increase  the population diversity and improve the search ability|the one-total probability and the expectation-variance probability were proposed to enhance the efficiency of particle search,which achieved the optimization of MOPSO.An improved TOPSIS was applied to assess and select the Pareto optimal solutions.The proposed algorithm was applied to the optimum design of plate-fin heat exchanger,and the resonable parameters were obtained.

Key words: territorial behavior, particle swarm optimization, plate-fin heat exchanger, technique for order preference by similarity to ideal solution