重大突发公共卫生事件下城市应急医疗物资配送

赵建有; 韩万里; 郑文捷; 赵阳

doi:10.19818/j.cnki.1671-1637.2020.03.016

重大突发公共卫生事件下城市应急医疗物资配送

doi: 10.19818/j.cnki.1671-1637.2020.03.016

1.
长安大学汽车学院, 陕西西安 710064
2.
长安大学运输工程学院, 陕西西安 710064

基金项目:

国家自然科学基金项目 71971030

陕西省交通运输厅科研项目 18-27R

中央高校基本科研业务费专项资金项目 300102228114

详细信息

作者简介:
赵建有(1963-), 男, 河南西峡人, 长安大学教授, 工学博士, 从事物流工程与交通运输安全研究

通讯作者:
韩万里(1987-), 男, 河南项城人, 长安大学工学博士研究生

中图分类号: U121
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出版历程
- 收稿日期: 2020-03-08
- 刊出日期: 2020-06-25

Distribution of emergency medical supplies in cities under major public health emergency

1.
School of Automobile, Chang'an University, Xi'an 710064, Shaanxi, China
2.
School of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China

Funds:

National Natural Science Foundation of China 71971030

Scientific Research Project of Department of Transport of Shaanxi Province 18-27R

Special Foundation for Basic Scientific Research of Central Colleges of China 300102228114

More Information

Author Bio:
ZHAO Jian-you(1963-), male, professor, PhD, jyzhao@chd.edu.cn

Corresponding author: HAN Wan-li(1987-), male, doctoral student, 2017022011@chd.edu.cn

摘要

摘要: 为了在发生重大突发公共卫生事件时提高城市医疗物资的应急救援效率, 减少人员伤亡与经济损失, 在分析重大突发公共卫生事件特点与应急物流特征的基础上, 将需求紧迫度作为配送影响因素, 提出以辖区人口、感染确诊及疑似病例、医疗物资需求点规模、医护人员数量和医疗物资缺口率为评价指标的医疗物资需求点需求紧迫度评价指标体系; 针对医疗物资应急物流的特点, 调整医疗物资配送时间窗参数, 建立由车辆行驶成本、配送延误惩罚成本和无配送延误补贴费用组成的总配送费用函数, 并考虑配送车辆载重、配送时间窗、医疗物资需求紧迫度等约束条件, 构建使总配送费用最少与需求紧迫度高的需求点优先配送的双重目标, 优化了医疗物资的配送路径; 依托SPSS、Yaahp和MATLAB软件平台, 结合算例, 利用层次分析法与遗传算法求解考虑与不考虑需求紧迫度的医疗物资应急物流配送路径优化模型。研究结果表明: 重大突发公共卫生事件下, 相对于不考虑需求紧迫度的配送路径, 考虑需求紧迫度的最优配送路径不仅对需求紧迫度较高的医疗物资需求点进行优先配送, 同时还使总配送费用减少了5.8%;需求紧迫度的引入能极大地改善调度的盲目性, 基于配送车辆载重、配送时间窗、医疗物资需求紧迫度等约束条件所构建的双目标优化模型能够有效地提高应急救援效率和减少不必要的调度成本。
- 应急物流 /
- 重大突发公共卫生事件 /
- 医疗物资 /
- 需求紧迫度 /
- 遗传算法 /
- 配送路径
Abstract: To improve the emergency rescue efficiency of medical supplies and reduce the casualties and economic losses in cities under the major public health emergency, based on the characteristics analyses of major public health emergencies and emergency logistics, the demand urgency was taken as the influencing factor of distribution. The evaluation index system for medical supplies demand points was proposed with the evaluation indexes of population within jurisdictions, confirmed and suspected cases of infection, scale of medical supplies demand point, number of medical staff and gap rate of medical supplies. According to the characteristics of emergency logistics of medical supplies, the time window parameters of medical supplies distribution were adjusted. The total distribution cost function composed of driving cost, penalty cost of distribution delay and subsidy without distribution delay was established. Considering the constraints of vehicle load, distribution time window, and demand urgency of medical supplies, a dual objective of priority distribution for demand points with the minimum total distribution cost and high demand urgency was constructed to optimize the distribution path of medical supplies. Relying on the software platforms of SPSS, Yaahp and MATLAB, and combining with examples, the analytic hierarchy process and genetic algorithm were used to solve the optimization models of emergency logistics distribution path of medical supplies with and without the consideration of demand urgency. Research result shows that under the major public health emergency, the optimal distribution path considering the demand urgency not only gives priority to the medical supplies demand points with higher demand urgency, but also reduces the total distribution cost by 5.8%, comparing with the distribution path without the consideration of demand urgency. The introduction of demand urgency can greatly reduce the blindness of scheduling. The dual objective optimization model restrained by the conditions of vehicle load, distribution time window and demand urgency of medical supplies can effectively improve the emergency rescue efficiency and reduce unnecessary scheduling costs.
- emergency logistics /
- major public health emergency /
- medical supply /
- demand urgency /
- genetic algorithm /
- distribution path

HTML全文

图 1 应急医疗物资需求点需求紧迫度评价指标体系

Figure 1. Evaluation index system of demand urgency for emergency medical supplies demand point

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图 2 应急医疗物资配送路径

Figure 2. Distribution paths of emergency medical supplies

下载: 全尺寸图片幻灯片

图 3 遗传算法运算过程

Figure 3. Operation process of genetic algorithm

下载: 全尺寸图片幻灯片

表 1 各医疗物资需求点信息

Table 1. Information of each medical supplies demand point

需求紧迫度评价指标	辖区人口/万人	感染确诊及疑似病例/人	医疗物资需求点规模/m²	医护人员数量/人	医疗物资缺口率/%
需求点1	1	5 417	10 611	67	40
需求点2	64	268	63 739	90	80
需求点3	144	3 417	35 375	77	70
需求点4	155	3 525	88 078	60	60
需求点5	31	5 801	61 251	90	10
需求点6	13	4 275	20 956	76	30

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表 2 各医疗物资需求点标准化信息

Table 2. Standardized information of each medical supplies demand point

需求紧迫度评价指标	辖区人口标准化值	感染确诊及疑似病例标准化值	医疗物资需求点规模标准化值	医护人员数量标准化值	医疗物资缺口率标准化值
需求点1	0.00	0.93	0.00	0.21	0.43
需求点2	0.41	0.00	0.69	0.99	1.00
需求点3	0.93	0.57	0.32	0.57	0.86
需求点4	1.00	0.59	1.00	0.00	0.71
需求点5	0.19	1.00	0.65	0.96	0.00
需求点6	0.08	0.72	0.13	0.55	0.29

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表 3 指标得分

Table 3. Scores of indexes

评价指标	辖区人口	确诊及疑似病例	医疗物资需求点规模	医护人员数量	医疗物资缺口率
辖区人口	1	1	4	3	1
确诊及疑似病例	1	1	4	3	1
医疗物资需求点规模	1/4	1/4	1	1	1/5
医护人员数量	1/3	1/3	1	1	1/4
医疗物资缺口率	1	1	5	4	1

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表 4 医疗物资需求点参数

Table 4. Medical supplies demand points parameters

参数	物资配送中心0	需求点1	需求点2	需求点3	需求点4	需求点5	需求点6
医疗物资需求/单位质量	0.0	4.0	3.0	1.5	4.5	1.5	2.0
最晚配送时间/h	10 000.0	2.3	0.8	2.5	2.0	2.3	2.3
各需求点相对需求紧迫度	1.00	1.10	1.50	2.06	2.00	1.25	1.00

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表 5 其他参数设置

Table 5. Other parameter settings

参数	取值
车辆额定载质量/单位质量	8
延误时单位时间惩罚成本/单位费用	60
无配送延误时单位补贴费用/单位费用	120
车辆单位时间的行驶成本/单位费用	200

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表 6 各医疗物资需求点最短距离

Table 6. Minimum distances of each medical supplies demand point h

需求点	0	1	2	3	4	5	6
0	0.00	2.00	1.80	2.00	1.50	1.20	0.80
1	2.00	0.00	1.50	1.40	1.80	1.50	1.50
2	1.80	1.50	0.00	2.00	2.00	2.00	2.00
3	2.00	1.40	2.00	0.00	1.00	2.00	1.00
4	1.50	1.80	2.00	1.00	0.00	1.50	0.80
5	1.20	1.50	2.00	2.00	1.50	0.00	1.30
6	0.80	1.50	2.00	1.00	0.80	1.30	0.00

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表 7 考虑与不考虑需求紧迫度的配送路线

Table 7. Distribution routes considering demand urgency or not

求解结果	考虑需求紧迫度	不考虑需求紧迫度
配送路线1	0-2-1-0	0-1-2-0
配送路线2	0-4-3-6-0	0-6-3-4-0
配送路线3	0-5-0	0-5-0
总配送费用/单位费用	1 732.8	1 840.8

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