【作者】 韩毅； 唐加福； 郭伟宏； 刘阳；

【Author】 Yi Han Jiafu Tang Ikou Kaku Yang Liu School of Information Science and Engineering, Northeastern University, Shenyang, 110004 Department of Management Science and Engineering, Akita Prefectural University, Japan

【机构】 东北大学信息学院教育部流程工业综合自动化重点实验室； 秋田县立大学系统科学与技术部；

【摘要】 经典的粒子群优化算法是一个在连续的定义域内搜索数值函数极值的很有效的方法。目前,几乎没有人将粒子群优化算法应用于批量问题中。本文提出结合遗传算法思想的混合粒子群优化算法来求解无能力约束的线形结构多层批量问题。通过实验验证了算法的有效性。更多还原

【Abstract】 The classical Particle swarm optimization (PSO) algorithm is a powerful method to find the minimum of a numerical function, on a continuous definition domain. Currently, many literatures have introduced the application of PSO algorithm in different scientific fields. But few people have applied PSO algorithm to multilevel lot-sizing (MLLS) problem. In view of this, a PSO algorithm integrated with operators of Genetic algorithm is come up with. This paper is devoted to investigate the ability of PSO algorithm in solving uncapacitated multilevel lot-sizing problem with series structure. Experiments showed the feasibility of PSO algorithm.更多还原