吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (4): 1078-1084.doi: 10.13229/j.cnki.jdxbgxb.20211416

• 交通运输工程·土木工程 • 上一篇    

基于鲁棒优化的不确定需求下应急物资配送多目标决策模型

龙海波1(),杨家其1(),尹靓1,赵学彧2,向子权1   

  1. 1.武汉理工大学 交通与物流工程学院，武汉 430063
    2.湖北第二师范学院 经济与管理学院 武汉 430205
  • 收稿日期:2021-12-22 出版日期:2023-04-01 发布日期:2023-04-20
  • 通讯作者: 杨家其 E-mail:longhaibo2012@163.com;styjq@whut.edu.cn
  • 作者简介:龙海波（1966-），男，正高级经济师，博士研究生.研究方向：运输与物流管理.E-mail：longhaibo2012@163.com
  • 基金资助:
    国家自然科学基金项目(51979214);吉林省交通科技项目(103-46160101)

Multi-objective decision-making on emergency material distribution under uncertain demand based on robust optimization

Hai-bo LONG1(),Jia-qi YANG1(),Liang YIN1,Xue-yu ZHAO2,Zi-quan XIANG1   

  1. 1.School of Transportation and Logistics Engineering，Wuhan University of Technology，Wuhan 430063，China
    2.School of Economics and Management，Hubei University of Education，Wuhan 430205，China
  • Received:2021-12-22 Online:2023-04-01 Published:2023-04-20
  • Contact: Jia-qi YANG E-mail:longhaibo2012@163.com;styjq@whut.edu.cn

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摘要：

针对应急物资配送决策具有不确定性和突然性等特点，提出了一种基于多目标鲁棒优化不确定需求下的应急物资配送决策模型。在分析应急需求的随机性、应急物流设施点的需求不确定风险和路网中断风险的因素上，确定了以物资需求点的救援时间满意度之和最大、系统总成本最小以及物资到达需求点的救援时间之和最小为目标，构建了多目标鲁棒优化模型，并运用Matlab软件求解。以一个山区发生自然灾害作为突发事件为例，验证了多目标鲁棒优化模型的有效性和正确性。研究结果表明：不确定需求下应急物资配送中，决策者可以依据本文多目标鲁棒优化模型权衡利弊，制定出既具有应对风险能力，又能快速反应的救援方案。

关键词: 应急物资配送路径, 鲁棒优化, 需求不确定性, 多目标优化

Abstract:

Aiming at the uncertainty and suddenness of emergency material distribution decision-making， a multi-objective robust optimization-based emergency material distribution decision model under uncertain demand is proposed. Based on the analysis of the randomness of emergency demand， the demand uncertainty risk of emergency logistics facilities and the risk on road network interruption， it is determined that maximum sum of satisfaction with the rescue time of the material demand point， minimum the total system cost， and sum of rescue time of the material reaches the demand point as the goal， a multi-objective robust optimization model is constructed and solved by Matlab software. Taking a natural disaster in a mountainous area as an example， the validity and correctness of the multi-objective robust optimization model are verified. The results show that in the distribution of emergency supplies under uncertain demand， decision maker can weigh the pros and cons based on the multi-objective robust optimization model in this paper， and formulate a rescue plan that not only has the ability to deal with risks， but also can respond quickly.

Key words: emergency supplies distribution route, robust optimization, demand uncertainty, multi-objective optimization

中图分类号: 

  • U15

表1

一级候选应急物流设施点"

一级应急点坐标/km建设费用/元容量/t
a1（17，0）53 28475
a2（0，35）70 64575
a3（26，38）56 91275
a4（50，74）57 34075

表2

二级候选应急物流设施点"

二级应急点坐标/km建设费用/元容量/t二级应急点坐标/km建设费用/元容量/t
k1（16，90）35 26315k5（23，16）26 31415
k2（25，68）27 88415k6（15，12）21 85315
k3（37，55）26 11215k7（10，25）31 67415
k4（26，25）23 64515k8（16，48）34 75815

表3

应急配送需求点"

需求点坐标/km容量/t需求点坐标/km容量/t需求点坐标/km容量/t
t1（31，63）2.172 322t8（25，34）2.090 059t15（6，15）2.076 513
t2（21，21）1.660 612t9（25，26）1.703 085t16（20，39）1.703 709
t3（20，15）2.102 983t10（17，12）2.081 522t17（39，60）2.304 982
t4（13，26）1.965 038t11（16，32）2.724 638t18（35，44）1.520 833
t5（13，14）2.783 066t12（24，51）2.941 742t19（17，6）1.909 298
t6（22，34）2.452 009t13（19，65）2.122 999t20（39，31）2.995 854
t7（33，36）2.606 505t14（16，23）2.868 852

图1

不同情境下目标函数值分布"

表4

不同控制系数取值下各目标函数均值"

目标函数值控制系数
012345
115.78415.78415.78415.78415.78415.784
2265 456.500279 197.500287 962.100295 639.800287 662.300289 924.800
326.87629.11527.95627.57430.30730.324
Z24.45925.73226.02626.41026.47826.617
目标函数值控制系数
67891~9均值10
115.78415.78415.78415.78415.78415.784
2294 972.100298 899.500301 319.200299 932.400292 834.411329 269.200
329.42029.70030.02930.53129.44028.543
Z26.73927.03127.24227.25926.61528.622
1 范琪, 王炜, 华雪东, 等. 基于广义出行费用的城市综合交通方式优势出行距离研究[J]. 交通运输系统工程与信息, 2018, 18(4): 25-31.
Fan Qi, Wang Wei, Hua Xue-dong, et al. Dominant transportation distance for multi transportation modes in urban integrated transportation[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(4): 25-31.
2 李彦瑾, 罗霞, 车国鹏, 等. 基于GERT网络的应急救援关键路段识别[J]. 交通运输系统工程与信息, 2017, 17(04): 166-172.
Li Yan-jin, Luo Xia, Che Guo-peng, et al. Critical road links identification in emergency rescue based on GERT network[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(4): 166-172.
3 李健, 周漪, 刘威. 上海市历史城区震后应急救援路网评价与优化[J]. 交通运输系统工程与信息, 2017, 17(4): 166-172.
Li Jian, Zhou Yi, Liu Wei. The evaluation and optimization of post-earthquake emergency rescue road network in Shanghai historic area[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(4): 166-172.
4 项昀, 王炜, 郑敦勇, 等. 区域综合网络货运交通方式的优势运距研究[J].交通运输系统工程与信息, 2016, 16(6): 33-39.
Xiang Yun, Wang Wei, Zheng Dun-yong, et al. Dominant transportation distance for multi transportation modes in regional integrated freight network[J]. Journal of Transportation Systems Engineering and Information Technology, 2016, 16(6): 33-39.
5 代颖, 马祖军.应急物流系统中的随机定位‒路径问题[J].系统管理学报,2012, 21(2): 212-217.
Dai Ying, Ma Zu-jun. Stochastic location-path problem in emergency logistics system[J]. Journal of Systems Management, 2012, 21(2): 212-217.
6 Ozdamar L, Ekinci E, Kucukyzici B. Emergency logistics planning in natural disasters[J]. Annals of Operations Research, 2004, 129: 217-245.
7 Chang K L, Zhou H, Chen G J, et al. Multiobjectivelocation routing problem considering uncertain dataafter disasters[J].Discrete Dynamics in Nature and Society, 2017, 2017(3): 1-7.
8 Juan Carlos Martín, Román Concepción, Juan Carlos García-Palomares, et al. Spatial analysis of the competitiveness of the high-speed train and air transport: the role of access to terminals in the Madrid–Barcelona corridor[J]. Transportation Research Part A, 2014, 69(12): 1099-1114.
9 Ipek N S, Ram M P, Chandra R B. Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior[J]. Journal of Transport Geography,2010,19(2): 298-313.
10 Filipe Rodrigues, Agostinho Agra. An exact robust approach for the integrated berth allocation and quay crane scheduling problem under uncertain arrival times[J]. European Journal of Operational Research, 2021, 295(2): 499-516.
11 Xiang Zi-quan, Yang Jia-qi, et al. A solution to resource allocation problem based on discrete grey wolf optimizer[J]. Journal of Huazhong University of Science & Technology (Natural Science Edition), 2021, 49(8): 81-85.
12 Gumte K M, Devi P P, Miriyala S S, et al. Data driven robust optimization for handling uncertainty in supply chain planning models[J]. Chemical Engineering Science, 2021, 246: No.116889.
13 Abdalla O H, Abu A M A, Ahmed A S. Generation expansion planning considering unit commitment constraints and data-driven robust optimization under uncertainties[J]. International Transactions on Electrical Energy Systems, 2021, 31(6): 1-19.
14 Xiang Zi-quan, Yang Jia-qi, Naseem M H, et al. Solving the multi-objective transportation decision-making problem based on improved S-type membership function[J]. Journal of Mathematics,2021: No.4169352.
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