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浙江大学学报(工学版)
JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE)
Mechanical and Electrical Engineering     
Proactive scheduling optimization on flow shops with random machine breakdowns
ZHAO Chan yuan1, LU Zhi qiang1, CUI Wei wei2
1. Department of Mechanical and Energy Engineering, Tongji University, Shanghai 201804, China; 2. Department of Industrial Engineering and Logistics Management, Shanghai Jiaotong University, Shanghai 200240, China
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Abstract  

Flow shop scheduling problems with random machine breakdowns were analyzed in order to optimize the bi objective of quality robustness and solution robustness. The impact of breakdowns was analyzed by proactive scheduling theory. A stochastic programming mathematical model was proposed. Then the nested algorithm with two loops was developed to simultaneously determine jobs’ sequence and buffer time. The outer optimization loop combined NEH algorithm and neighborhood search method to determine jobs’ sequence. The inner loop adopted the genetic algorithm to optimize the buffer time with an effective surrogate measure, which was adopted as the evaluation method of solutions. Computational results indicate that the solution performance can be significantly improved with the proposed algorithm comparing with the traditional ways, and decision makers can choose different biased solutions according to their preference. Inserting buffer time improved the solution robustness and increased the stability of quality robustness.

Published: 01 April 2016
CLC:  F 224  
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Cite this article:

ZHAO Chan yuan, LU Zhi qiang, CUI Wei wei. Proactive scheduling optimization on flow shops with random machine breakdowns. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2016, 50(4): 641-649.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2016.04.007     OR     http://www.zjujournals.com/eng/Y2016/V50/I4/641


考虑随机故障的流水线调度问题前摄优化方法

研究带有随机故障的流水线车间调度问题, 以质量鲁棒性和解鲁棒性的综合指标为优化目标, 分析故障这一随机因素的影响, 采用前摄优化理论求解问题. 建立问题的随机规划数学模型,设计内、外两层嵌套式优化算法以联合决策工件调度顺序与缓冲时间大小. 在外层, 以NEH启发式算法为基础,结合邻域搜索决策工件加工顺序；在内层, 采用遗传算法搜索缓冲时间并设计有效的代理指标作为解的评价方式. 数据实验表明, 提出的算法相比2种传统方法所得到的解的综合指标更优异, 且允许决策者根据不同的偏好选择不同的优化解. 加入缓冲时间有利于改善解鲁棒性指标,可以提高质量鲁棒性的稳定度. 

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