Fuzzy flow-shop scheduling problem based on Quantum Particle Swarm Optimization

Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (2): 238-240.

• 工程与应用 • Previous Articles Next Articles

Fuzzy flow-shop scheduling problem based on Quantum Particle Swarm Optimization

JIN Chao, YE Chunming

School of Management, University of Shanghai for Science and Technology, Shanghai 200090, China

Received:1900-01-01 Revised:1900-01-01 Online:2012-01-11 Published:2012-01-11

基于QPSO算法的模糊流水车间调度问题

金超，叶春明

上海理工大学管理学院，上海 200090

Abstract

Abstract: The problem of fuzzy flow shop scheduling has uncertainty in actual production process owing to various objective factors. This scheduling problem is discussed in this paper, and Quantum Particle Swarm Optimization（QPSO） is proposed to solve the 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.

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

摘要： 实际生产过程中由于各种客观因素的影响，流水车间调度问题往往具有模糊不确定性。介绍了模糊流水车间调度问题，在此基础上提出了一种收敛速度快、全局性能好的量子微粒群算法来解决该问题。通过仿真实例对该算法进行了验证。结果表明，在求解模糊流水车间调度问题时，量子微粒群算法有很好的效果。

关键词: 量子微粒群算法, 模糊流水车间调度, 模糊交货期, 优化

JIN Chao, YE Chunming. Fuzzy flow-shop scheduling problem based on Quantum Particle Swarm Optimization[J]. Computer Engineering and Applications, 2012, 48(2): 238-240.

金超，叶春明. 基于QPSO算法的模糊流水车间调度问题[J]. 计算机工程与应用, 2012, 48(2): 238-240.

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Fuzzy flow-shop scheduling problem based on Quantum Particle Swarm Optimization

基于QPSO算法的模糊流水车间调度问题

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