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Bi-objective vehicle routing problem for hazardous materials transportation

机译:危险品运输的双目标车辆路径问题

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摘要

In hazardous materials distribution and recollection, economic, social and environmental aspects need to be considered simultaneously. The stakeholders involved in these activities have different and sometimes conflicting objectives, shippers and carriers are interested in a cost efficient distribution while government and population are interested in a safe transportation. A method for providing trade-off solutions is proposed through the determination of a set of routes that simultaneously minimizes two conflicting objectives, the total routing risk and the total transportation cost. This hazardous materials transportation problem is modeled by vehicle routing problem using a heterogeneous fleet of trucks. The multi-objective version of vehicle routing problem has not been as studied as its mono-objective version. Two solutions methods are proposed, a multi-objective neighborhood dominance-based algorithm and an e-constraint meta-heuristic algorithm, both of them based on neighborhood search. A comprehensive comparison among the proposed solution methods is carried out using multi-objective metrics. The algorithms are tested on 20 modified benchmark instances (including the risk assessment associated parameters) with up to 100 customers. The results show that the use of the dominance-based algorithm presents a better performance, in terms of the quality of the Pareto front approximation, than the utilization of the e-constraint method. (C) 2018 Elsevier Ltd. All rights reserved.
机译:在危险物质的分配和回收中,需要同时考虑经济,社会和环境方面。参与这些活动的利益相关者具有不同的目标,有时甚至是相互矛盾的目标,托运人和承运人对具有成本效益的分配感兴趣,而政府和民众对安全运输感兴趣。通过确定一组路线同时提出了一种权衡解决方案的方法,该路线可以同时最小化两个相互冲突的目标,即总路线风险和总运输成本。该危险物料运输问题是通过使用异构卡车车队的车辆路线问题来建模的。车辆路径问题的多目标版本尚未像其单目标版本那样得到研究。提出了两种求解方法,一种是基于邻域优势的多目标算法,另一种是基于邻域搜索的电子约束元启发式算法。所提出的解决方法之间的全面比较是使用多目标指标进行的。在最多100个客户的20个修改后的基准实例(包括与风险评估相关的参数)上对算法进行了测试。结果表明,与基于电子约束方法的利用相比,基于帕拉托前沿近似的质量,基于优势的算法的使用表现出更好的性能。 (C)2018 Elsevier Ltd.保留所有权利。

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