多模态载具动态协同的山区森林火灾应急物资配送路径优化

doi:10.16265/j.cnki.issn1003-3033.2026.05.0356

中国安全科学学报 ›› 2026, Vol. 36 ›› Issue (5): 270-278.doi: 10.16265/j.cnki.issn1003-3033.2026.05.0356

多模态载具动态协同的山区森林火灾应急物资配送路径优化

周愉峰¹(), 程佳豪²^,^**(), 潘紫玫¹, 刘长石³

¹ 重庆工商大学管理科学与工程学院, 重庆 400067
² 西南交通大学交通运输与物流学院, 四川成都 611756
³ 湖南工商大学工商管理学院, 湖南长沙 410205

收稿日期:2025-12-12 修回日期:2026-03-01 出版日期:2026-05-28
通信作者:
^** 程佳豪(1999—),男,四川成都人,博士研究生,主要研究方向为物流与供应链管理。E-mail: chengjiahao@my.swjtu.edu.cn。
作者简介:
周愉峰 (1984—),男,湖南双峰人,博士,教授,博士生导师,主要从事物流与供应链管理研究。E-mail:xtuzyf@qq.com。
刘长石教授。
基金资助:
国家社会科学基金资助(23XGL039)

Dynamically coordinated routing optimization for mountainous forest fire emergency supply delivery using multi-modal vehicles

Zhou Yufeng¹(), Cheng Jiahao²^,^**(), Pan Zimei¹, Liu Changshi³

¹ School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing 400067, China
² School of Transportation and Logistics, Southwest Jiaotong University, Chengdu Sichuan 611756, China
³ School of Management, Hunan University of Technology and Business, Changsha Hunan 410205, China

Received:2025-12-12 Revised:2026-03-01 Published:2026-05-28

摘要/Abstract

摘要：

针对山区森林火灾应急物资保障中存在的多模态载具协同配送与动态调度难题,提出一种应急物资配送路径优化方法。考虑山区路网结构,需求紧迫性,摩托车与无人机参与,空-地协同配送等因素,以应急物资配送时间最短为目标,构建卡车-无人机-摩托车动态协同的山区森林火灾应急物资配送路径优化模型;设计一种带修复算子的整数多向量编码改进自适应大邻域搜索算法(IALNS)求解模型,并与传统自适应大领域搜索算法(ALNS)和禁忌搜索算法比较。研究结果表明: 提出的模型和算法可应用于山区环境森林火灾应急物资配送中; IALNS优于ALNS和禁忌搜索算法;动态协同策略优于静态协同策略,总配送时间下降2.49%~25.75%;应发挥摩托车与无人机的优势,构建多载具协同的优化配送模式。

关键词: 山区森林火灾, 应急物资配送, 动态协同, 车辆路径问题(VRP), 自适应大邻域搜索算法(ALNS)

Abstract:

To address the challenges of multi-modal vehicle coordination and dynamic scheduling in emergency supply delivery for mountain forest fires, this study proposes an optimized route planning method for emergency supply distribution. Considering factors such as mountainous road network structures, demand urgency, motorcycle and drone participation, and air-ground collaborative delivery, a dynamic collaborative truck-drone-motorcycle route optimization model for mountain forest fire emergency supply delivery is constructed, aiming to minimize delivery time. An improved adaptive large neighborhood search (IALNS) algorithm with a repair operator is designed to solve the model, and it is compared with traditional ALNS and tabu search algorithms(TSA). Research findings indicate: The proposed model and algorithm are applicable to emergency supply delivery in mountainous forest fire scenarios. The IALNS outperforms both ALNS and TSA. Dynamic coordination strategies yield superior results compared to static coordination, reducing the total delivery time by 2.49% to 25.75%. Leveraging the advantages of motorcycles and drones is essential for establishing an optimized multi-vehicle collaborative delivery model.

Key words: forest fire, emergency deliveries, dynamically coordinated, vehicle routing problem(VRP), adaptive large neighborhood search(ALNS)

中图分类号:

X928.7火灾与爆炸事故

周愉峰, 程佳豪, 潘紫玫, 刘长石. 多模态载具动态协同的山区森林火灾应急物资配送路径优化[J]. 中国安全科学学报, 2026, 36(5): 270-278.

Zhou Yufeng, Cheng Jiahao, Pan Zimei, Liu Changshi. Dynamically coordinated routing optimization for mountainous forest fire emergency supply delivery using multi-modal vehicles[J]. China Safety Science Journal, 2026, 36(5): 270-278.

图/表 7

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算例	TT/min	TDT/min	DDT/min	MDT/min	TDCT/min	TDN	DDN	MDN	RT/s
C101	827.24	279.11	410.45	266.33	281.80	20	12	18	5.98
C201	1 034.76	383.94	505.79	285.21	365.61	25	11	14	5.56
R101	1 340.21	441.86	524.62	533.29	365.06	21	10	19	5.74
R201	1 379.44	698.29	484.40	392.68	288.47	26	9	15	5.50
RC101	2 019.04	470.34	263.04	1 312.15	236.55	18	6	26	5.45
RC201	2 053.39	486.05	865.77	752.06	815.27	19	14	17	5.19
平均值	1 442.35	459.93	509.01	590.29	392.13	21.50	10.33	18.17	5.57

算例	策略	TT/min	TDT/min	DDT/min	MDT/min	TDCT/min	TDN	DDN	MDN
C102	动态	872.61	285.14	286.83	416.14	171.32	20	10	20
C102	静态	894.91	331.40	329.34	234.17	329.34	22	12	16
R202	动态	1 264.06	579.34	436.49	437.88	246.84	24	9	17
R202	静态	1 320.56	590.03	369.88	360.64	369.88	25	10	15
RC102	动态	1 186.60	464.71	427.01	448.67	273.22	22	9	20
RC102	静态	1 598.05	394.33	566.56	637.17	566.56	19	9	22

算例	节点数量	算法	最优目标/min	最差目标/min	平均值/min	Gap/%	标准差	平均时间/s
C205	25	IALNS	485.75	598.18	543.30	—	34.95	4.81
		ALNS	514.21	619.64	558.62	2.82	34.12	4.79
		TSA	575.40	665.54	610.45	12.36	27.98	10.01
C206	50	IALNS	1 282.38	1 516.38	1 434.86	—	83.97	5.99
		ALNS	1 380.82	1 664.81	1 550.42	8.05	88.02	6.13
		TSA	1 631.08	2 192.95	1 875.30	30.70	219.42	12.32
RC206	100	IALNS	3 390.10	3 788.68	3 667.33	—	123.85	13.53
		ALNS	3 486.18	4 610.39	3 959.89	7.98	393.04	14.92
		TSA	3 717.92	4 704.93	4 272.89	16.51	357.77	28.72
G-C102	200	IALNS	5 088.95	6 362.82	5 703.07	—	381.23	19.81
		ALNS	5 722.08	6 786.82	6 217.66	9.02	386.73	13.77
		TSA	7 303.94	9 073.83	8 244.30	44.56	601.28	35.65

算例	w_f/ kg	TT/min	TDT/min	DDT/min	MDT/min	TDCT/min	TDN	DDN	MDN
RC202	4	1 990.90	539.30	221.77	1 266.00	185.60	20	6	24
	6	1 888.79	665.60	368.04	896.03	327.15	22	9	19
	8	1 835.75	676.30	371.68	838.56	320.89	22	10	18
	10	1 696.70	642.58	448.02	655.20	398.93	22	13	15
	12	1 680.03	758.03	408.67	580.46	341.54	24	13	13
	14	1 645.52	550.76	393.91	764.29	330.47	20	14	16

算例	摩托车数量	TT/min	TDT/min	DDT/min	MDT/min	TDCT/min	TDN	DDN	MDN
RC202	2	1 990.02	775.49	408.60	844.38	370.15	22	14	14
	3	1 729.92	715.48	315.31	758.05	256.39	22	13	15
	4	1 696.70	642.58	448.02	655.2	398.93	22	13	15
	5	1 593.93	546.11	459.16	655.82	392.00	20	13	17
	6	1 458.52	602.19	271.19	648.89	207.44	22	10	18

多模态载具动态协同的山区森林火灾应急物资配送路径优化

Dynamically coordinated routing optimization for mountainous forest fire emergency supply delivery using multi-modal vehicles

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