【摘要】 针对以电动汽车作为物流配送车辆的路径优化问题,首先将车辆配送货物的混装类别纳入考虑范围并建立了线性规划数学模型。其次,提出了两种求解该问题的改进型启发式算法MCWS和MHGA。最后,通过多组小规模算例验证了模型和算法结果的准确性。同时采用多组算例来比较两种模型的寻优效果。结果表明,考虑货物类别的模型可以在配送距离略有增加的情况下,避免将不适宜混装在车厢内的货物指派给同一车辆配送,达到降低货物运输损失,提高顾客满意度的目的;将两种算法在较大规模算例进行实验与比较,证明了所提出的模型与算法可以为较大规模的物流企业电动汽车路径策略提供良好借鉴与帮助。更多还原

【Abstract】 Aiming at the path optimization problem of electric vehicles as a distribution vehicle,firstly,this paper takes into account the mixed category of goods delivered by vehicles and establishes a mathematical model of linear programming. Secondly,two heuristics called MCWS and MHGA are proposed to solve the problem. Finally,the accuracy of the model and algorithm results is verified by using multiple sets of small-scale examples,and multiple sets of examples are used to compare the optimization results of the two models. The experimental results show that the model considering the type of goods can avoid assigning the goods which are not suitable to be mixed in the carriage to the same vehicle when the delivery distance increases slightly,so as to reduce the loss of goods transportation and improve the customer satisfaction. Experiments and comparisons of the two algorithms in a large-scale case show that the proposed model and algorithm can provide a good reference and help for the large-scale logistics enterprise’s electric vehicle routing strategy.更多还原