考虑需求紧迫度的海上多事故点应急物资调度优化

doi:10.3969/j.issn.1674-0696.2025.11.08

重庆交通大学学报（自然科学版） ›› 2025, Vol. 44 ›› Issue (11): 61-67.DOI: 10.3969/j.issn.1674-0696.2025.11.08

• 交通运输+人工智能 • 上一篇

考虑需求紧迫度的海上多事故点应急物资调度优化

常征，甄鑫，齐壮，范兴灿

(大连海事大学交通运输工程学院，辽宁大连 116026)

收稿日期:2024-10-25 修回日期:2025-08-04 发布日期:2025-11-27
作者简介:常征(1986—),女,吉林德惠人,副教授,博士,主要从事交通线网优化、运输经济、运输线网规划与设计方面的研究。E-mail:chang_zheng@dlmu.edu.cn
基金资助:
辽宁省社会科学规划基金项目(L24CGL006)

Emergency Material Scheduling Optimization of Maritime Multiple Accident Points Considering Demand Urgency

CHANG Zheng, ZHEN Xin, QI Zhuang, FAN Xingcan

(College of Transportation Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China)

Received:2024-10-25 Revised:2025-08-04 Published:2025-11-27

摘要/Abstract

摘要： 海上事故频发，对应急物资调度的有效性和及时性提出更高要求，尤其在多起事故同时发生、物资供不应求的情况下，合理分配资源变得尤为重要。为解决这一问题，提出了考虑需求紧迫度的海上多事故点应急物资调度模型，并设计自适应权重变异多目标粒子群算法(AW-M-MOPSO)展开求解。首先，引入熵权-TOPSIS法确定各事故点的需求紧迫度；其次，以物资分配公平性最大、应急救援总成本最小且应急救援总时间最短为目标，构建海上多事故点应急物资调度优化模型；最后设计AW-M-MOPSO求解该模型。以东海海域发生的事故为案例进行模型验证，结果表明：该模型可有效依据各事故点紧迫度高低灵活调配资源，在确保公平地满足各事故点需求的同时，优化救援时间和救援成本。

关键词: 交通运输工程；需求紧迫度；应急物资调度；多目标优化；自适应权重变异多目标粒子群算法

Abstract: Maritime accidents occur frequently, which puts forward higher requirements for the effectiveness and timeliness of emergency material scheduling. Especially in situations where multiple accidents occur simultaneously and supplies are in short supply, the rational allocation of resources has become particularly important. In order to solve this problem, an emergency material scheduling model for maritime multiple accident points considering the demand urgency was proposed, and an adaptive weight-mutation-multi-objective particle swarm optimization (AW-M-MOPSO) algorithm was designed to solve it. Firstly, the entropy weight-TOPSIS method was introduced to determine the demand urgency of each accident point. Secondly, with the goal of maximizing the fairness of material distribution, minimizing the total cost of emergency rescue and minimizing the total time of emergency rescue, an optimization model of emergency material scheduling for maritime multiple accident points was constructed. Finally, AW-M-MOPSO was designed to solve the model. The accident that occurred in the East China Sea was taken as a case study for model validation. The results show that the proposed model can effectively allocate resources flexibly according to the urgency of each accident point and optimize the rescue time and rescue cost while ensuring that the needs of each accident point are met fairly.

Key words: traffic and transportation engineering; demand urgency; emergency material scheduling; multi-objective optimization; adaptive weight-mutation-multi-objective particle swarm optimization algorithm

中图分类号:

U692.4

常征，甄鑫，齐壮，范兴灿. 考虑需求紧迫度的海上多事故点应急物资调度优化[J]. 重庆交通大学学报（自然科学版）, 2025, 44(11): 61-67.

CHANG Zheng, ZHEN Xin, QI Zhuang, FAN Xingcan. Emergency Material Scheduling Optimization of Maritime Multiple Accident Points Considering Demand Urgency[J]. Journal of Chongqing Jiaotong University(Natural Science), 2025, 44(11): 61-67.

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考虑需求紧迫度的海上多事故点应急物资调度优化

Emergency Material Scheduling Optimization of Maritime Multiple Accident Points Considering Demand Urgency

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