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首页> 外文期刊>Proceedings of the Workshop on Principles of Advanced and Distributed Simulation >SIMULATION-BASED OPTIMIZATION FOR SPLIT DELIVERY VEHICLE ROUTING PROBLEM: A REPORT OF ONGOING STUDY
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SIMULATION-BASED OPTIMIZATION FOR SPLIT DELIVERY VEHICLE ROUTING PROBLEM: A REPORT OF ONGOING STUDY

机译:基于仿真的送货车辆路线优化研究:一项正在进行的研究报告

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摘要

Due to the complexity of split delivery vehicle routing problem (SDVRP), a simulation based optimization approach is proposed. A simulation model is used to capture the dynamics and uncertainties of the system and evaluate the system performance. Three split policies, LOS-policy, LDD-policy and LWT-policy are designed to implement the order split/consolidation. To optimize the route of orders in a consolidation, a genetic algorithm is developed and integrated with the simulation model. Experimental results showed that the average order size has significant impact on consolidation and split policies. Split delivery outperforms non-split delivery significantly when the average order size occupies about 60% of a truckload. Large arrival rate of orders also benefits split delivery. Sparse distribution of customers deteriorates the performance of split delivery. In various experimental scenarios, LDD-policy is always better than LOS-policy and LWT-policy.
机译:由于分送车辆路径问题(SDVRP)的复杂性,提出了一种基于仿真的优化方法。仿真模型用于捕获系统的动力学和不确定性并评估系统性能。设计了三个拆分策略,即LOS策略,LDD策略和LWT策略,以实现订单拆分/合并。为了优化合并中的订单路线,开发了一种遗传算法并将其与仿真模型集成在一起。实验结果表明,平均订单大小对合并和拆分策略有重大影响。当平均订单量约占卡车总载货量的60%时,拆分交付的性能要明显优于非拆分交付。较大的订单到达率也有利于分批交货。客户的稀疏分布会降低拆分交付的性能。在各种实验方案中,LDD策略始终优于LOS策略和LWT策略。

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