用QPSO算法求解模糊交货期Flow-shop调度问题  

Quantum particle swarm optimization for flow-shop scheduling problem with fuzzy delivery time

作　　者：宋书强[1] 叶春明[1] 

机构地区：[1]上海理工大学管理学院,上海200093

出　　处：《计算机工程与应用》2009年第6期246-248,共3页Computer Engineering and Applications

摘　　要：针对模糊交货期Flow-shop调度问题的特点,运用一种收敛速度快、全局性能好、不易陷入局部最优的智能迭代算法-量子粒子群算法,对其进行求解。通过仿真实例对该算法进行了验证,结果表明,在求解模糊交货期的Flow-shop问题时,量子粒子群算法要优于遗传算法和基本粒子群算法。According to the characteristics of flow-shop scheduling problem with fuzzy delivery time, quantum particle swarm optimization is used to solve this problem,which has good convergence speed and performance in searching global optimum.A practical analysis is used to confirm the performance of the method.The results show that QPSO is effective in solving the problem.The results of simulation indicate that QPSO is better than the genetic algorithm and the PSO.

关 键 词：量子粒子群算法 Flow—shop调度 模糊交货期 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]