欢迎访问《兵工学报》官方网站,今天是 分享到:

兵工学报 ›› 2019, Vol. 40 ›› Issue (8): 1708-1715.doi: 10.3969/j.issn.1000-1093.2019.08.021

• 论文 • 上一篇    下一篇

考虑中断风险的备件供应选址-分配优化模型

王亚东, 石全, 陈材, 尤志锋   

  1. (陆军工程大学石家庄校区 装备指挥与管理系, 河北 石家庄 050003)
  • 收稿日期:2018-11-12 修回日期:2018-11-12 上线日期:2019-10-15
  • 通讯作者: 石全(1966—),男,教授,博士生导师 E-mail:junshiyc@163.com
  • 作者简介:王亚东(1992—),男,博士研究生。E-mail: xwzj0003@163.com
  • 基金资助:
    武器装备“十三五”预先研究共用技术项目(41404050501);军内科研重点项目(KYSZJWJK1742)

Location-allocation Joint Optimization Model of Spare Parts Supply under Supply Disruption Risk

WANG Yadong, SHI Quan, CHEN Cai, YOU Zhifeng   

  1. (Department of Equipment Command and Management, Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, Hebei, China)
  • Received:2018-11-12 Revised:2018-11-12 Online:2019-10-15

摘要: 战时条件下,仓库或运输载体受到敌方蓄意攻击而丧失全部或部分储存和运输能力,造成备件供应中断。而供应网络的中断风险很难预测且动态变化,为不确定性参数。为解决不确定中断风险下的备件供应问题,以备件供应成本最低、供应延迟时间最短为目标,构建了战时备件供应的多目标选址-分配联合优化模型。通过对多面体不确定集合的鲁棒等价变化,建立相应的鲁棒优化模型。采用元启发式算法对模型进行求解,得到了模型的非支配解集及其对应的供应方案。研究结果表明:通过对关键设施的加固防护,可以提高备件供应网络的效率和可靠性;鲁棒优化模型的最优解可以保证战时备件供应“最差情况下”解的可行性,即模型具有很好的鲁棒性。

关键词: 备件供应, 中断风险, 选址-分配问题, 多目标优化, 鲁棒优化

Abstract: In wartime, the spare parts warehouse or transport carrier may be attacked deliberately, and some storage and transportation capacity may be completely or partially lost, which leads to the interruption of spare parts supply system. The interruption risk of supply network is an uncertain parameter and difficult to be predicted and change dynamically. In view of the depth uncertainty of interruption risk, the diversification of wartime spare parts supply optimization objectives is considered. A joint optimization model of multi-objective location-allocation for wartime spare parts supply is constructed for the minimum cost of spare parts supply and the shortest lead time of supply. A corresponding robust optimization model is established based on the robust equivalent change of polyhedron uncertainty set. The meta-heuristic algorithms are used to obtain the non-dominate solution sets and the corresponding supply plans. The results show that the efficiency and reliability of spare parts supply network can be greatly improved by strengthening some key nodes. On the other hand, the optimal solution of the robust optimization model can guarantee the feasibility of the worst-case solution of spare parts supply, that is, the model has good robustness. Key

Key words: sparepartssupply, disruptionrisk, location-allocationproblem, multi-objectiveoptimization, robustoptimization

中图分类号: