在多仓库网络优化牛奶收集路线的供应链分析方法

Mattia Neroni , Marta Rinaldi
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引用次数: 0

摘要

本研究提出了一个供应链模型,用于优化多仓库网络中的牛奶收集路线。这个问题包括一个车队,这些车队离开他们的仓库(即通常是司机的家),访问指定的农场收集生牛奶,并将其运送到加工厂。这个问题在文献中还没有明确的表述,它可以被分类在团队定向问题(TOP)和多仓库车辆路径问题(MDVRP)之间。然而,在引入对数学公式的轻微修改和附加约束之前,它不能简化为前面提到的任何问题。我们介绍了一个新的公式,并提出了六种启发式算法,以尽量减少牛奶收集在乳制品部门覆盖的距离。通过使用新的基准测试和在一组实际案例应用程序中进行测试,验证了所提出的解决方案。在实际数据上进行了计算实验,以研究启发式方法改变牛奶需求的性能。结果证明了所提出的方法在现实世界中的适用性,并在求解质量和计算时间方面确定了最佳算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A supply chain analytics approach for optimizing milk collection routing in multi-depot networks
This study presents a supply chain model for optimizing milk collection routing in multi-depot networks. The problem consists of a fleet of vehicles that leaves their depots (i.e., typically the driver’s houses), visits an assigned set of farms to collect the raw milk, and delivers it to the processing plant. This problem has not yet been formulated explicitly in the literature, and it can be classified in the middle between the Team Orienteering Problem (TOP) and the Multi-Depot Vehicle Routing Problem (MDVRP) with heterogeneous vehicles. However, it cannot be reduced to any previously mentioned problems before introducing slight modifications and additional constraints to the mathematical formulation. We introduce a new formulation and propose six heuristic algorithms to minimize the distance covered in milk collection in the dairy sector. The proposed solutions are validated by using new benchmarks and tested in a set of real case applications. Computational experiments on real-life data are performed to investigate the performance of the heuristics varying the milk demand. The results demonstrate the applicability of the proposed approach to the real world and identify the best algorithm in terms of solution quality and computational time.
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