Optimization of Vehicle Routing for Cross-infection Risk in the Epidemic

doi:10.16182/j.issn1004731x.joss.23-1476

Abstract

Abstract:

In view of the safety risks associated with logistics distribution route optimization during public health emergencies, this paper investigates the vehicle routing problem by incorporating the risk of cross-infection, integrates the cross-infection risk caused by logistics activities in the epidemic area into the logistics distribution model, and establishes a logistics vehicle distribution model with the goal of cross-infection risk and cost. An improved genetic algorithm is designed for model optimization and solution. Based on the integration of chaos initialization population and adaptive crossover and mutation operations, a neighbor exclusion operator is further proposed to enhance the global search ability of the algorithm, prevent premature convergence, and ensure the diversity of chromosome population. Through numerical simulation and experimental comparative analysis, it is verified that the model and optimization algorithm established in this paper are effective and feasible in solving logistics distribution problems under public health events.

Key words: emergency supplies distribution, risk of cross infection, dual-objective logistics routing optimization, chaotic adaptive genetic algorithm, weight weighting

CLC Number:

TP391.9

Shi Xiaodong, Guo Yongcheng, Ma Mingqi, Pan Jiarui. Optimization of Vehicle Routing for Cross-infection Risk in the Epidemic[J]. Journal of System Simulation, 2025, 37(4): 910-921.

Figures/Tables 12

Fig. 1

Table 1

Content of indicators for regional epidemic risk assessment model

一级指标	二级指标	定义描述
感染可能性P	区域常住人口数 $a 1$	基于区域常住人口数
	现存确诊人数 $a 2$	现存确诊的人口数：累计确诊人数-累计治愈人数-累计死亡人数
	发病总人数 $a 3$	疫情统计以来累计确诊患病总人数
感染严重度Q	近14天新增病例数 $a 4$	近14天新增患病人数总和
	发病率 $a 5$	区域常住人口中，累计确诊人数所占比例
	死亡率 $a 6$	在区域患病总人数中，累计死亡人数所占的比例

Table 1

Table 2

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Table 3

Fig. 6

Fig. 7

Fig. 8

Table 4

Comparison of running results

指标	$φ 1 = 0.4$				$φ 1 = 0.6$				$φ 1 = 0.8$
指标	1车	2车	3车	汇总	1车	2车	3车	汇总	1车	2车	3车	汇总
车辆里程/km	360	403	233	996	651	564	299	1 514	798	527	326	1651
车辆载重量/kg	933	945	546	2 424	927	989	508	2 424	951	944	529	2424
固定成本/元	230	230	230	690	230	230	230	690	230	230	230	690
消毒成本/元	120	120	80	320	0	20	0	20	20	40	0	60
运输成本/元	4 325	4 846	2 798	11 969	7 815	6 778	3 592	18 185	9 585	6 333	3 923	19 841
配送总成本/元	4 675	5 196	3 108	12 979	8 045	7 028	3 822	18 895	9 835	6 603	4 153	20 591
交叉感染风险成本/元	4 550	4 550	1 050	10 150	3 900	4 550	1 400	9 850	3 900	3 900	1 800	9 600

Table 4

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指标分区	等级L	指标值分布
高风险区	3	前20%
中风险区	2	20%~70%
低风险区	1	后30%

编号	坐标，物资需求量，感染风险等级	编号	坐标，物资需求量，感染风险等级
1	(45，68)，77，1	19	(42，15)，63，2
2	(42，68)，89，1	20	(38，05)，68，2
3	(40，66)，67，1	21	(50，30)，77，2
4	(35，66)，50，1	22	(48，30)，75，2
5	(22，75)，53，1	23	(47，40)，56，2
6	(20，85)，62，1	24	(95，30)，51，2
7	(15，80)，50，1	25	(92，30)，87，3
8	(28，52)，78，1	26	(90，35)，73，3
9	(25，52)，90，1	27	(87，30)，80，3
10	(23，55)，75，1	28	(75，55)，65，3
11	(10，35)，75，1	29	(68，60)，72，3
12	(8，45)，76，1	30	(65，60)，52，3
13	(2，40)，71，2	31	(60，60)，59，3
14	(35，30)，79，2	32	(65，82)，69，3
15	(33，35)，82，2	33	(60，85)，84，3
16	(30，32)，72，2	34	(55，85)，53，3
17	(28，35)，64，2	35	(5，35)，79，3
18	(25，35)，51，2	0	(40，50)，－，－

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