Location and routing of dangerous goods' storage and transportation under continuous time-varying risks

doi:10.16265/j.cnki.issn1003-3033.2022.04.027

Abstract

Abstract:

In order to improve safety of dangerous goods' storage and transportation, considering the location and routing problems under continuous time-varying risks, warehouse location, transportation routes and flow allocation were optimized simultaneously. Firstly, a nonlinear assessment model for continuous time-varying risks was formulated considering continuous influence of emergency rescues. Then, with minimization of total risks and cost as optimized goals, a multi-objective nonlinear 0-1 mixed integer programming model was developed based on locally connected urban network. Finally, TOPSIS-based Dijkstra phased solution algorithm was designed according to the model's complexity, and several examples were used to verify the effectiveness of the model and algorithm. The results show that compared with current management schemes, the proposed method, which considers continuous time-varying risks, can reduce 48.79% of risks, and therefore provides a better plan for dangerous goods' storage and transportation.

Key words: continuous time-varying risk, dangerous goods' storage and transportation, location and routing, emergency rescue, technique for order preference by similarity to an ideal solution (TOPSIS)

KUANG Yujie, ZHAO Jiahong. Location and routing of dangerous goods' storage and transportation under continuous time-varying risks[J]. China Safety Science Journal, 2022, 32(4): 185-191.

Figures/Tables 7

Fig.1

Fig.2

Tab.1

Tab.2

Tab.3

Comparison between optimal & current plan

决策	优化目标	现有方案	新方案	变化率/%
选址	风险	8.90×1 $022$	3.09×10²³	+247.19
选址	成本/元	1.68×10⁷	3.12×10⁷	+85.71
选线	风险	6.16×10²³	5.22×1 $022$	-91.52
选线	成本/元	8.06×10⁶	7.41×10⁵	-90.81
选址- 选线	风险	7.05×10²³	3.61×10²³	-48.79
选址- 选线	成本/元	2.49×10⁷	3.13×10⁷	+25.70

Tab.3

Tab.4

Tab.5

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节点	建设成本/元	运营成本/元	存储能力/ (t·a^-1)	人口密度/ (百人·km^-2)
6	4 291 951	600 326	6 000	2.31
7	3 748 137	764 508	6 000	0.76
8	3 746 256	782 949	6 000	0. 59
9	3 489 505	733 797	6 000	2.11
10	3 631 024	828 488	6 000	1.57
11	2 424 362	708 616	6 000	0.40
12	4 008 556	657 516	6 000	0.49
13	3 099 541	534 283	6 000	0.90
14	4 132 514	881 849	6 000	2.40
15	3 680 144	740 102	6 000	0.13
16	3 537 588	709 566	6 000	1.41

规模(节点, 线路,变量, 约束)	风险	成本/ 元	目标值与最优值相差占比/%	时间/ s
小(57,2 220, 227,67)	1.61×10²³	1.40×10⁷	0	15
中(115,7 079, 912,133)	2.12×10²³	3.16×10⁷	18	22
大(230,22 977, 3 622,263)	7.63×10²³	6.55×10⁷	43	99

情景	风险		成本/元		目标值与最优值相差占比/%		时间/s
情景	优化结果	变化率/%	优化结果	变化率/%	优化结果	变化率/%	优化结果	变化率/%
基础测试算例	2.12×10²³	—	3.16×10⁷	—	18	—	22	—
情景1	2.68×10²²	-91.51	3.11×10⁷	-1.58	41	+127.78	17	-22.73
情景2	1.76×10²³	-16.98	3.16×10⁷	0	74	+311.11	22	0
情景3	2.35×10²³	+10.85	3.14×10⁷	0.63	61	+238.89	25	+13.64
情景4	2.71×10²⁴	+1178.30	4.03×10⁷	27.53	—	—	217	+886.37