摘要
提出了一种混合微粒群算法,通过引入禁忌搜索算法和动态设置惯性权重等方法,提高了算法搜索全局最优解的能力并且能够有效避免早熟收敛问题。并将这种算法应用于求解实际的提前/滞后F lowShop调度问题,仿真实验结果表明了混合微粒群算法的可靠性与实用性。
This paper presents the hybrid particle swarm optimi;＋ation （PSO） algorithm which using taboo searching algorithm, alterable setting of weight inertia, etc. The improved algorithm has high ability of searching the global optimum solution and avoiding the premature convergence problem effectively. The hybrid PSO can be applied to solve flow shop scheduling problem with earliness and tardiness, and experiment results demonstrate that the proposed algorithm have reliability, practicability and efficient value in the engineering application.
出处
《系统工程理论方法应用》
北大核心
2006年第4期294-298,304,共6页
Systems Engineering Theory·Methodology·Applications
基金
上海市教委发展基金项目(02GK13)
上海市重点学科建设资助项目(T0502)
关键词
提前/滞后
FLOW
SHOP
调度问题
微粒群算法
禁忌搜索算法
flow shop scheduling problem with earliness/tardiness
particle swarm optimization （PSO）
taboo searching algorithm
