基于多准则Bat算法的电动卡车限行路径问题求解

J. Yeomans
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引用次数: 3

摘要

随着城市集约化程度的提高,城市规划者将更多的资源投入到更注重可持续性的物流规划中。事实证明,与普遍使用的内燃机汽车相比,电动汽车不仅成本更低,而且更环保。然而,企业和市政当局采用的主要决策方法在计算上不一定有利于涉及电动汽车的城市交通系统的优化和评估。提出了一种创新的建模和规划方法,使城市规划者能够更容易地评估电动汽车在城市物流中的贡献,并支持决策过程。具体而言,本文提出了一种多准则建模-生成备选方案(MGA)决策支持过程,该过程采用蝙蝠算法(BA)元启发式方法,用于城市转运问题中电动汽车规划的备选方案生成集。在涉及电动卡车的城市转运问题上,这种多标准、ba驱动的MGA方法在创建规划替代方案方面的有效性得到了证明。
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A Multicriteria, Bat Algorithm Approach for Computing the Range Limited Routing Problem for Electric Trucks
As a result of increasing urban intensification, civic planners have devoted additional resources to more sustainability-focused logistics planning. Electric vehicles have proved to be both a lower cost alternative and more environmentally friendly than the more ubiquitous internal combustion engine vehicles. However, the predominant decision-making approaches employed by businesses and municipalities are not necessarily computationally conducive for the optimization and evaluation of urban transportation systems involving electric vehicles. An innovative modelling and planning approach is proposed to enable urban planners to more readily evaluate the contribution of electric vehicles in city logistics and to support the decision-making process. Specifically, this paper provides a multicriteria modelling-to-generate-alternatives (MGA) decision-support procedure that employs the Bat Algorithm (BA) metaheuristic for generating sets of alternatives for electric vehicle planning in urban transshipment problems. The efficacy of this multicriteria, BA-driven MGA approach for creating planning alternatives is demonstrated on an urban transshipment problem involving electric trucks.
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