Emergency Location-routing Model with Uncertain Demands under Path Risks

doi:10.12005/orms.2018.0155

Operations Research and Management Science ›› 2018, Vol. 27 ›› Issue (7): 37-42.DOI: 10.12005/orms.2018.0155

• Theory Analysis and Methodology Study • Previous Articles Next Articles

Emergency Location-routing Model with Uncertain Demands under Path Risks

SUN Hua-li¹, CAO Wen-qian¹, XUE Yao-feng², WANG Xun-qing³

1. Management School, Shanghai University, Shanghai 200444, China;
2. Department of Educational Information technology, Shanghai 200062, China;
3. School of Public Administration, Shandong Technology and Business University,Yantai 264005, China

Received:2016-11-29 Online:2018-07-25

考虑路径风险的需求不确定应急物流定位-路径问题

孙华丽¹, 曹文倩¹, 薛耀锋², 王循庆³

1.上海大学管理学院,上海 200444;
2.华东师范大学教育信息技术学系,上海 200062;
3.山东工商学院公共管理学院,山东烟台 264005

通讯作者: 薛耀锋(1977-),男,山东冠县人,副研究员,博士,研究方向:计算机应用。
作者简介:孙华丽(1977-) ,女,山东威海人,副教授,博士,研究方向:城市安全与应急管理
基金资助:
国家自然科学基金资助项目(71203134,71603109);上海市哲社规划课题(2015XAF002)

Abstract

Abstract: Location-routing problem (LRP) is an important logistics problem in emergency management. Considering the risk of road congestion, the risk of road damage, the risk of the road complexity and the demand uncertainty of relief commodities, a multi-objective optimization model based on robust optimization theory aiming at minimizing the longest distribution routine time and the total logistic system cost is developed. Comparison of several cases is made to indicate that the total system cost, the longest path transportation delivery time and the total system cost all show the tendency of increase with the growth of the controlling parameters. The total cost is higher when the demand disruption is greater, which proves the effectiveness of the robust optimization model. It provides an effective method to solve the emergency material security, timely delivery and the risk in emergency logistics system.

Key words: emergency logistics, location-routing problem (LRP), path risk, robust optimization

摘要： 针对自然灾害对路网造成的破坏性和受灾点物资需求量的不确定性,综合考虑应急物流路径风险和物资分配的时间公平性,将路径风险定量化为路径通行能力风险、路径损毁风险和路径复杂性,基于鲁棒优化理论,以最小化车辆最长配送时间和应急物流系统总成本为目标,建立了双目标多物资定位-路径优化模型,采用遗传算法对其求解,以汶川地震应急救援相关数据为例进行了数据仿真实验。实验结果的对比分析表明:在考虑路径风险下,随着控制系数的增加,系统总成本和最长配送时间目标值均呈现增大的趋势;受灾点的物资需求扰动越大,构建应急物流系统的总成本越高。算例结果也验证了鲁棒优化方法在处理不确定需求方面的有效性,为解决自然灾害后应急设施点的开设和救援物资的安全及时准确配送提供了有效的方法。

关键词: 应急物流, 定位-路径问题, 路径风险, 鲁棒优化

CLC Number:

F252

SUN Hua-li, CAO Wen-qian, XUE Yao-feng, WANG Xun-qing. Emergency Location-routing Model with Uncertain Demands under Path Risks[J]. Operations Research and Management Science, 2018, 27(7): 37-42.

孙华丽, 曹文倩, 薛耀锋, 王循庆. 考虑路径风险的需求不确定应急物流定位-路径问题[J]. 运筹与管理, 2018, 27(7): 37-42.

References

[1] Salhi S, Nagy G. Consistency and robustness in location-routing[J]. Studies in Locational Analysis, 1999, (13): 3-19.
[2] Zarandi M H F, Hemmati A, Davari S. The multi-depot capacitated location-routing problem with fuzzy travel times[J]. Expert Systems with Applications, 2011, 38(8): 10075-10084.
[3] Toro-Díaz H, Mayorga M E, Chanta S, Mclay LA . Joint location and dispatching decisions for emergency medical services[J]. Computers & Industrial Engineering, 2013, 64(4): 917-928.
[4] 代颖,马祖军,郑斌.突发公共事件应急系统中的模糊多目标定位-路径问题研究[J].管理评论,2010,22(1):121-128.
[5] 李双琳,马祖军,郑斌.震后初期应急物资配送的模糊多目标选址-多式联运问题[J].中国管理科学,2013,21(2):144-151.
[6] 孙华丽,王循庆,薛耀锋.随机需求应急物流多阶段定位-路径鲁棒优化研究[J].运筹与管理,2013,22(6):45-51.
[7] Abounacer R, Rekik M, Renaud J. An exact solution approach for multi-objective location-transportation problem for disaster response[J]. Computers & Operations Research, 2014,41: 83-93.
[8] Rath S, Gutjahr W J. A math-heuristic for the warehouse location-routing problem in disaster relief[J]. Computers & Operations Research, 2014, 42(2): 25-39.
[9] 刘长石,彭怡,寇纲.震后应急物资配送的模糊定位—路径问题研究[J].中国管理科学,2016,24(5):111-118.
[10] 马祖军,胡萍.实时/时变路网环境下城市出救点选择与救援车辆路径的集成动态优化[J].管理工程学报,2014.28(4):165-172.
[11] 邹旭东,郑四发 .具有交通限制约束的道路网络最优路径算法[J].公路交通科技,2002,19,(4):82-84.
[12] 张杰,王志勇,许维胜,熊丹.突发事件下应急救援路径选择模型的构建和求解[J].计算机应用研究,2011,28(4):1311-1314.
[13] Bertsimas D, Sim M. Robust discrete optimization and network flows[J]. Mathematical Programming, 2003, 98: 43-71.

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Emergency Location-routing Model with Uncertain Demands under Path Risks

考虑路径风险的需求不确定应急物流定位-路径问题

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