基于旋转基技术的多目标粒子群优化算法

his paper proposed a multi-objective particle swarm algorithm based on rotation basis (rtMOPSO) in order to solve problems about multi-objective optimization. Firstly, Pareto front maps to the improved sectorial plane of rotation basis so that evolutionary status of the population were detected by the entropy and its difference entropy of the population. Then, angle dominance and strength of angle dominance were proposed to design an archive maintaining strategy which can balance diversity and convergence. Finally, selecting the global best solution was proposed based on rotation angle and distance of the rotation basis. The improved algorithm is compared with 5 multi-objective optimization algorithms on two kinds of test suites. The Simulation results show that improved algorithm in this paper has big advantages over the other competitors in terms of diversity and convergence.