Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (4): 1078-1084.doi: 10.13229/j.cnki.jdxbgxb.20211416

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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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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

CLC Number: 

  • U15

Table1

Emergency response facility points for level 1"

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

Table 2

Emergency response facility points for level 2"

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

Table 3

Disaster demand point"

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

Fig.1

Distribution of objective function values in different contexts"

Table 4

Mean value of objective function with different control coefficients"

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
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