运筹与管理 ›› 2015, Vol. 24 ›› Issue (3): 6-13.DOI: 10.12005/orms.2015.0077

• 理论分析与方法探讨 • 上一篇    下一篇

有容量限制的可靠性固定费用选址问题

周愉峰1, 马祖军2, 王恪铭3   

  1. 1.重庆工商大学 商务策划学校,重庆 400067;
    2.西南交通大学 经济管理学院 物流与应急管理研究所,四川 成都 610031;
    3.西南交通大学 峨眉校区,四川 峨眉山 614202
  • 收稿日期:2012-12-16 出版日期:2015-06-12
  • 作者简介:周愉峰(1984-),男,湖南双峰人,讲师,博士,研究方向:应急物流、物流系统优化;马祖军(1974-),男,浙江开化人,教授,博士生导师,研究方向:物流与供应链管理、应急管理、产品回收管理。
  • 基金资助:
    国家自然科学基金项目(90924012,71090402,71271227);教育部新世纪优秀人才支持计划资助项目(NCET-10-0706);四川省哲学社会科学研究规划项目(SC11B049);四川省学术和技术带头人培养资金项目(川人社办发[2011]441号);中央高校基本科研业务费专项资金资助项目(SWJTU11CX152,2682013CX073)

Reliability Capacitated Fixed-charge Location Problem

ZHOU Yu-feng1, MA Zu-jun2, WANG Ke-ming3   

  1. 1.School of Business Planning, Chongqing Technology and Business University, Chongqing 400067, China;
    2.Institute for Logistics and Emergency Management, School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China;
    3.Emei Campus, Southwest Jiaotong University, Emeishan 614202, China
  • Received:2012-12-16 Online:2015-06-12

摘要: 设施网络可能面临各种失灵风险,而设施选址属于战略决策问题,短期内难以改变,因而在选址设计时需要充分考虑设施的非完全可靠性。本文针对无容量限制的可靠性固定费用选址问题进行扩展,进一步考虑设施的容量约束,基于非线性混合整数规划方法建立了一个有容量限制的可靠性固定费用选址问题优化模型。针对该模型的特点,应用线性化技术进行模型转化,并设计了一种拉格朗日松弛算法予以求解。通过多组算例分析,验证了算法的性能。算例分析结果表明设施失灵风险和设施容量对于选址决策有显著影响,因而在实际的选址决策过程中有必要充分考虑设施的失灵风险及容量约束。

关键词: 设施选址, 设施失灵, 可靠性, 容量限制, 拉格朗日松弛

Abstract: Infrastructure networks have the risk of disruptions. Because facility location is a strategic decision that can not be changed in a short time, it is critical to account for the non-complete reliability of facility in designing the network. The classical reliability uncapacitated fixed-charge location problem is extended by considering the capacity constraint. And the reliability capacitated fixed-charge location problem under the risk of disruptions is formulated as a mixed integer nonlinear programming model. Considering the characteristics of the model, a linearization technique is applied to convert the model and a lagrangian relaxation algorithm is developed to solve the problem. A numerical example is given to verify the model and algorithm performance. The results show that facility capacity has a notable impact on location decision, and the unexpected failures of facility and capacity constraint of facility should be fully considered in real-life location decision process.

Key words: facility location, facility disruptions, reliability, capacitated, Lagrangian relaxation

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