考虑救援效用的洪灾医疗物资多方式配送路径规划

doi:10.16265/j.cnki.issn1003-3033.2026.01.0753

中国安全科学学报 ›› 2026, Vol. 36 ›› Issue (1): 216-226.doi: 10.16265/j.cnki.issn1003-3033.2026.01.0753

考虑救援效用的洪灾医疗物资多方式配送路径规划

刘长石¹(), 刘涛², 祝勇军³^,^**(), 岳俊羽⁴, 万城², 李君宇⁵

¹ 湖南工商大学工商管理学院,湖南长沙 410205
² 湖南工商大学智能工程与智能制造学院,湖南长沙 410205
³ 湖南工商大学会计学院,湖南长沙 410205
⁴ 湖南工商大学人工智能与先进计算学院,湖南长沙 410205
⁵ 西南财经大学工商管理学院,四川成都 611130

收稿日期:2025-08-12 修回日期:2025-11-21 出版日期:2026-01-28
通信作者:
** 祝勇军(1978—),男,湖南永州人,博士,副教授,主要从事物流与供应链研究。E-mail:hnzyj@qq.com。
作者简介:
刘长石 (1975—),男,湖南邵阳人,博士,教授,主要从事物流与供应链管理、数字经济等方面的研究。E-mail: liuchangshi964@126.com。
基金资助:
国家社会科学基金(23BGL011); 湖南省社会科学基金(23JD037); 教育厅一般项目(25C0404)

Multi-modal delivery routing planning of medical supplies for flood disasters considering rescue utility

LIU Changshi¹(), LIU Tao², ZHU Yongjun³^,^**(), YUE Junyu⁴, WAN Cheng², LI Junyu⁵

¹ School of Business Administration, Hunan University of Technology and Business, Changsha Hunan 410205, China
² School of Intelligent Engineering and Intelligent Manufacturing, Hunan University of Technology and Business, Changsha Hunan 410205, China
³ School of Accounting, Hunan University of Technology and Business, Changsha Hunan 410205, China
⁴ School of Artificial Intelligence and Advanced Computing, Hunan University of Technology and Business, Changsha Hunan 410205, China
⁵ School of Business Administration, Southwest University of Finance and Economics, Chengdu Sichuan 611130, China

Received:2025-08-12 Revised:2025-11-21 Published:2026-01-28

摘要/Abstract

摘要：

为量化医疗物资在不同时间送达需求点产生的救援效果,引入救援效用概念,根据医疗物资运达需求点的时间差异构建救援效用量化函数;在此基础上,以总救援效用最大、总配送时间最短为目标,构建洪灾医疗物资多方式配送的路径规划模型,并根据模型特性,设计一种混合非支配排序遗传算法-II(HNSGA-II)求解;采用多类型算例开展试验。结果表明:HNSGA-II的总救援效用比传统非支配排序遗传算法-II(NSGA-II)和多目标蜂群算法(MOABCA)分别提升62%和29%,物资送达时间的平均满意度分别提升13%和6.1%。HNSGA-II能够提升应急救援效果,体现出更强的多目标优化能力,确保灾民在紧急情况下能得到及时有效的治疗。

关键词: 救援效用, 洪灾, 医疗物资, 多方式配送, 路径规划, 混合非支配排序遗传算法-II(HNSGA-II)

Abstract:

To quantify the rescue effect of medical supplies delivered to demand points at different times, the concept of rescue utility is introduced, and a rescue utility quantification function was constructed based on the time difference of medical supplies arriving at demand points. On this basis, a path planning model for multi-modal distribution of medical supplies in flood disasters was established with the objective of maximizing total rescue utility and minimizing total distribution time. According to the characteristics of the model, a HNSGA-II was designed for solution. Experiments were conducted using multiple types of examples. The results demonstrate that HNSGA-II achieves a 62% and 29% improvement in total rescue utility compared to the traditional Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and the Multi-Objective Artificial Bee Colony Algorithm (MOABCA), respectively. Additionally, the average satisfaction level of material delivery time is enhanced by 13% and 6.1%, respectively. These findings indicate that HNSGA-II significantly improves emergency rescue outcomes, exhibits superior multi-objective optimization capability, and ensures that disaster victims receive timely and effective treatment under emergency conditions.

Key words: rescue utility, flood disaster, medical supplies, multi-mode delivery, routing planning, hybrid non-dominated sorting genetic algorithm-II (HNSGA-II)

中图分类号:

X915.5

刘长石, 刘涛, 祝勇军, 岳俊羽, 万城, 李君宇. 考虑救援效用的洪灾医疗物资多方式配送路径规划[J]. 中国安全科学学报, 2026, 36(1): 216-226.

LIU Changshi, LIU Tao, ZHU Yongjun, YUE Junyu, WAN Cheng, LI Junyu. Multi-modal delivery routing planning of medical supplies for flood disasters considering rescue utility[J]. China Safety Science Journal, 2026, 36(1): 216-226.

图/表 9

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算例	OT/min	ORU	DT/min	NT/min	AS/%	RT/s
R103	1 317.96	1 598.13	589.72	728.25	83.38	376.66
RC103	1 634.30	1 795.59	795.33	838.98	86.99	380.11
R203	1 289.87	2 124.55	547.56	742.31	97.98	371.90
RC203	1 710.98	1 468.91	902.88	808.10	98.79	348.38
C103	1 529.10	2 242.71	583.21	945.89	99.00	326.01
C203	1 889.16	1 534.41	811.52	1 077.64	98.81	313.49

灾区	路径序号	冲锋艇配送路径及各需求点送达时间	BT	FT	TR
重灾区1	1	101 →11 →12 →9 →101 (8:10)(8:20) (8:34) (9:11)(9:50)	8:10	9:50	101.67
	2	101 →8 →7 →10 →6 →101 (8:10)(8:55)(9:14) (9:25)(9:35)(9:47)	8:10	9:47	8.50
	3	101 →4 →3 →101 (9:47)(11:30)(11:59)(12:28)	9:47	12:28	0.000 7
	4	101 →1 →5 →2 →101 (9:50)(10:18)(10:56)(11:46)(12:18)	9:50	12:18	0.000 4

算法	OT/min	ORU	AS/%	RT/s
NSGA-Ⅱ	1 865.57	1 106.58	76	432.88
MOABCA	1 755.39	1 383.89	81	442.76
HNSGA-Ⅱ	1 634.30	1 795.59	86	380.11

策略	OT/min	ORU	AS/%	TU	AU
目标A₁	3 206.31	1 810.87	55	10	2.1
目标A₂	1 521.97	742.07	91	9	1.8
目标A₃	1 634.30	1 795.59	86	9	2

载货量	NT/min	ORU	AS/%	LT/min	AU	Z
500	917.30	1 356.83	79	312.54	2.3	14
600	838.98	1 795.59	86	268.12	2	12
700	777.22	1 843.98	88	225.28	1.8	11
800	652.84	1 948.38	91	180.20	1.5	9

考虑救援效用的洪灾医疗物资多方式配送路径规划

Multi-modal delivery routing planning of medical supplies for flood disasters considering rescue utility

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参考文献 23

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BN	MI/min	AU	Z₁	Z₂	Z₃	ORU	AS/%
1	310	4.3	5	5	3	1 603.45	69
2	146	2	5	4	3	1 795.59	86
3	64	1.2	4	4	3	1 842.59	87
4	58	1.08	5	5	3	1 906.87	89
5	0	0.8	5	4	3	1 987.96	91
6	0	0.6	4	5	3	1 993.89	91

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