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带时间窗的危险货物车辆路径问题2阶段优化

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为有效降低危险货物道路运输的风险和成本,针对带时间窗的危险货物车辆路径问题(HMVRPTW),设计2阶段优化方法.首先,根据特征将该问题分解为双目标最短路径问题和带时间窗双目标车辆路径问题(VRP),分别建立数学模型并设计2阶段方法求解,第1阶段采用脉冲算法初筛路径,第2阶段设计针对带时间窗双目标VRP蚁群算法;然后,以9个节点和17条边的测试为例,说明求解过程;最后,以兰州市主城区16个加油站油品配送为例,采用该方法分配运输车辆,计算平均用时为24.38 s,可获得Pareto最优解,而采用多目标遗传算法平均用时为41.05 s.结果表明:所提方法通过初筛路径能够简化问题规模,充分考虑危险货物运输风险变化及时间窗因素,引导蚂蚁在指定搜索空间中寻优,在效率方面较多目标遗传算法具有明显优势.
Two-stage optimization of vehicle routing problem for hazardous materials with time windows
In order to effectively reduce the risks and costs of road transportation of hazardous materials,aiming at vehicle routing problem(VRP)for hazardous materials with time windows(HMVRPTW),a two-stage optimization was studied.First of all,according to its characteristics,it was divided into bi-objective shortest path problem and bi-objective VRP with time window.Secondly,the mathematical models were established and two-stage methods were designed to solve them.In the first stage,the pulse algorithm was used to filter the path to obtain the Pareto-optimal path between the distribution center and each demand node.In the second stage,an ant colony algorithm was designed for the bi-objective VRP with time window.Then,taking the test of 9 nodes and 17 edges as an example,the solution process was explained.Finally,taking the oil delivery of 16 gas stations in the main urban area of Lanzhou city as an example,this method calculated an average time of 24.38 seconds to obtain the Pareto-optimal solution for the vehicle scheduling,while using multi-objective genetic algorithm,the average time was 41.05 seconds.The results show that the proposed method simplifies the problem scale through the filtering paths,fully consider the changes in risk and the constraint of time window of hazardous materials transportation,and guides the ants to search for optimization in the specified search space.The proposed method has obvious advantages in efficiency compared to the multi-objective genetic algorithm.

time windowhazardous material vehicle routing problem(VRP)two-stage optimizationant colonyPareto-optimal

柴获、何瑞春、韩伟、贾晓燕、代存杰

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兰州交通大学电子与信息工程学院,甘肃兰州 730070

兰州交通大学交通运输学院,甘肃兰州 730070

时间窗 危险货物 车辆路径问题(VRP) 2阶段优化 蚁群算法 Pareto最优

国家自然科学基金资助国家自然科学基金资助天津大学-兰州交通大学自主创新基金合作项目资助甘肃省教育厅"双一流"科研重点项目甘肃省高等学校青年博士基金资助

71961015521620412020054GSSYLXM-042022QB-065

2023

10.16265/j.cnki.issn1003-3033.2023.12.2080

中国安全科学学报
中国职业安全健康协会

中国安全科学学报

CSTPCDCSCD北大核心
影响因子：1.548
ISSN：1003-3033
年,卷(期)：2023.33(12)
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