Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (6): 246-248.DOI: 10.3778/j.issn.1002-8331.2009.06.071

• 工程与应用 • Previous Articles    

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

SONG Shu-qiang,YE Chun-ming   

  1. School of Management,University of Shanghai for Science and Technology,Shanghai 200093,China
  • Received:2008-01-14 Revised:2008-04-14 Online:2009-02-21 Published:2009-02-21
  • Contact: SONG Shu-qiang

用QPSO算法求解模糊交货期Flow-shop调度问题

宋书强,叶春明   

  1. 上海理工大学 管理学院 上海 200093
  • 通讯作者: 宋书强

Abstract: 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.

Key words: quantum particle swarm optimization, flow-shop, fuzzy due date

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。

关键词: 量子粒子群算法, Flow-shop调度, 模糊交货期