公共卫生事件下交叉感染风险的车辆路径优化研究

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

摘要/Abstract

摘要：

针对公共卫生事件中物流配送路径优化所面临的安全风险挑战，研究了考虑交叉感染风险的车辆路径问题。将疫区中物流活动可能引发的交叉传染风险融入物流配送模型中，建立以交叉感染风险和成本为目标的物流车辆配送模型。设计了一种改进的遗传算法用于模型优化求解，并在融合了混沌初始化种群与自适应交叉、变异操作的基础上，进一步提出了一种邻居互斥算子，提升了算法的全局搜索能力，防止过早收敛，保障了染色体种群的多样性。仿真结果验证了模型和优化算法在解决公共卫生事件下物流配送问题的有效性和可行性。

关键词: 应急物资配送, 交叉感染风险, 双目标物流路径优化, 混沌自适应遗传算法, 权重加权

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

中图分类号:

TP391.9

史晓东,郭永城,马铭杞等 . 公共卫生事件下交叉感染风险的车辆路径优化研究[J]. 系统仿真学报, 2025, 37(4): 910-921.

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

图/表 12

图1

表1

区域感染风险评估模型指标内容

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

表1

表2

图2

图3

图4

图5

表3

图6

图7

图8

表4

运行结果对比

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

表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)，－，－