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An improved estimation of distribution algorithm for multi-compartment electric vehicle routing problem

机译:多隔室电动汽车路由问题的分布算法改进估计

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摘要

The multi-compartment electric vehicle routing problem (EVRP) with soft time window and multiple charging types (MCEVRP-STW&MCT) is studied, in which electric multi-compartment vehicles that are environmentally friendly but need to be recharged in course of transport process, are employed. A mathematical model for this optimization problem is established with the objective of minimizing the function composed of vehicle cost, distribution cost, time window penalty cost and charging service cost. To solve the problem, an estimation of the distribution algorithm based on Levy flight (EDA-LF) is proposed to perform a local search at each iteration to prevent the algorithm from falling into local optimum. Experimental results demonstrate that the EDA-LF algorithm can find better solutions and has stronger robustness than the basic EDA algorithm. In addition, when comparing with existing algorithms, the result shows that the EDA-LF can often get better solutions in a relatively short time when solving medium and large-scale instances. Further experiments show that using electric multi-compartment vehicles to deliver incompatible products can produce better results than using traditional fuel vehicles.
机译:研究了具有软时间窗口和多个充电类型(MCEVRP-STW&MCT)的多隔室电动车辆路由问题(EVRP),其中在运输过程中环保的电动多隔室车辆,但需要在运输过程中充电。雇用。建立了该优化问题的数学模型,目的是最小化车辆成本,分配成本,时间窗口惩罚成本和充电服务成本组成的功能。为了解决问题,提出了基于征含飞行(EDA-LF)的分发算法的估计,以在每次迭代中执行本地搜索,以防止算法落入本地最佳状态。实验结果表明,EDA-LF算法可以找到更好的解决方案,并且具有比基本EDA算法更强的鲁棒性。另外,当与现有算法进行比较时,结果表明,在求解介质和大规模实例时,EDA-LF通常可以在相对短的时间内获得更好的解决方案。进一步的实验表明,使用电动多隔室载体输送不相容的产品可以产生比使用传统燃料车辆的更好的结果。

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