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Optimization of two-stage location-routing-inventory problem with time-windows in food distribution network

机译:配送网络中带时间窗的两阶段选址库存问题的优化

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摘要

High transportation cost and low service quality are common weaknesses in different logistics networks, especially in food delivery. Due to its perishable features, the quality of the food will deteriorate during the while delivery process. In this paper, a two-stage location-routing-inventory problem with time windows (2S-LRITW) for food products is proposed. The first stage corresponds to a location-routing-inventory problem with time windows and the second stage is the transportation problem with vehicle capacity constraints. The problem is formulated as a mixed integer-programming model. Then a hybrid heuristic is proposed, in which distance-based clustering approach, mutation operation and the relocate exchange method are introduced to improve performance of algorithm. At last, the hybrid heuristic was tested using several cases, including some small instances and a real-life case. The results show that the distance-based clustering approach can efficiently improve the convergence speed. And the IACO and the relocate exchange method can enlarge the search space. As a result, the hybrid heuristic is suitable for solving practical larger scale problem. Furthermore, the results also indicate that customer sequence has great effect on the object due to the energy cost considered.
机译:高运输成本和低服务质量是不同物流网络(尤其是食品配送)中常见的弱点。由于其易腐烂的特性,在交付过程中,食物的质量将下降。本文提出了一种带有时间窗(2S-LRITW)的食品两阶段位置路由库存问题。第一阶段对应于带有时间窗的位置路由库存问题,第二阶段对应于具有车辆容量约束的运输问题。该问题被表述为混合整数编程模型。然后提出了一种混合启发式算法,其中引入了基于距离的聚类方法,变异操作和重定位交换方法,以提高算法的性能。最后,使用几种情况(包括一些小实例和一个实际案例)对混合启发式算法进行了测试。结果表明,基于距离的聚类方法可以有效地提高收敛速度。 IACO和异地交换方法可以扩大搜索空间。结果,混合启发式方法适合于解决实际的大规模问题。此外,结果还表明,由于考虑了能源成本,客户顺序对对象有很大影响。

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