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Research on express delivery vehicle route planning method for stochastic customer demand

机译:满足随机客户需求的快递车辆路线规划方法研究

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Express delivery vehicle route optimization with simultaneous stochastic pick up demands is significantly essential to improve response speed, and to decrease delivery cost. To achieve it, this paper proposes an express delivery vehicle route planning method. The optimization model is build and the methodology is discussed in detail. Ant Colony Algorithm has been exploited to derive the optimal solution. The proposed model is solved in Simulink simulation environment. The results show this method can effectively solve the complex decision problem of selecting the best vehicle from a number of feasible pickup vehicles. According to the dynamic situation, the vehicle routing path can be update and optimize in time. This method can significantly shorten the delivery and pick-up time, greatly improve the customer's dynamic order response speed, improve customer satisfaction, and reduce logistics costs.
机译:具有随机接送需求的快递车辆路线优化对于提高响应速度和降低交货成本至关重要。为此,本文提出了一种快递车辆路线规划方法。建立了优化模型并详细讨论了方法。蚁群算法已被用来推导最优解。该模型在Simulink仿真环境中得到解决。结果表明,该方法可以有效解决从众多可行皮卡中选择最佳车辆的复杂决策问题。根据动态情况,车辆路径可以及时更新和优化。这种方法可以大大缩短交货和取货时间,大大提高了客户的动态订单响应速度,提高了客户满意度,并降低了物流成本。

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