改进的多目标粒子群算法

改进的多目标粒子群算法 Improved Multi-Objective Particle Swarm Algorithm 熊盛武 XIONG Sheng-wu 1 2 first-author 刘麟 LIU Lin 1 2 王琼 WANG Qiong 1 2 史旻 SHI Min 1 2 武汉理工大学计算机科学与技术学院 武汉理工大学计算机科学与技术学院 School of Computer Science and Technology, Wuhan University of Technology School of Computer Science and Technology, Wuhan University of Technology 武汉理工大学计算机科学与技术学院,湖北,武汉,430070 武汉理工大学计算机科学与技术学院,湖北,武汉,430070 提出了一个改进的粒子群算法并将其用于解决多目标优化问题.该算法利用粒子群算法的信息传递机制,引入多目标演化算法常用的归档技术,采用SPEA2算法的环境选择和配对选择策略,使得整个群体在保持适当的选择压力的情况下收敛于Pareto最优解集.标准测试函数的数值实验结果表明,所提出的算法能够使找到的解集快速收敛到Pareto非劣最优目标域,并且解集沿着Pareto非劣最优目标域有很好的扩展性. An improved particle swarm algorithm to solve multi-objective problems is proposed. The algorithm uses both the information transfer strategy of particle swarm algorithm and the archiving technique which is commonly used in multi-objective evolutionary algorithms. Environmental selection and matching selection strategy of SPEA2 algorithm are also adopted to assure the population converge to the true Pareto front while keeping proper selection pressure. The benchmark problems numerical experiment results demonstrate that the proposed method can rapidly converge to the Pareto optimal front and spread widely along the front. 多目标优化 粒子群算法 Pareto最优解 multi-objective optimization particle swarm algorithm Pareto solutions TP301.6 国家863计划（2002AA1Z1490）;湖北省自然科学基金项目（2002AB040）资助 2005-03-01 2021-04-01 3