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A model for distribution centers location-routing problem on a multimodal transportation network with a meta-heuristic solving approach

机译:基于元启发式求解的多式联运网络配送中心选址问题模型

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Nowadays, organizations have to compete with different competitors in regional, national and international levels, so they have to improve their competition capabilities to survive against competitors. Undertaking activities on a global scale requires a proper distribution system which could take advantages of different transportation modes. Accordingly, the present paper addresses a location-routing problem on multimodal transportation network. The introduced problem follows four objectives simultaneously which form main contribution of the paper; determining multimodal routes between supplier and distribution centers, locating mode changing facilities, locating distribution centers, and determining product delivery tours from the distribution centers to retailers. An integer linear programming is presented for the problem, and a genetic algorithm with a new chromosome structure proposed to solve the problem. Proposed chromosome structure consists of two different parts for multimodal transportation and location-routing parts of the model. Based on published data in the literature, two numerical cases with different sizes generated and solved. Also, different cost scenarios designed to better analyze model and algorithm performance. Results show that algorithm can effectively solve large-size problems within a reasonable time which GAMS software failed to reach an optimal solution even within much longer times.
机译:如今,组织必须在区域,国家和国际层面与不同的竞争者竞争,因此,他们必须提高自身的竞争能力才能与竞争者抗衡。在全球范围内开展活动需要适当的分销系统,该系统可以利用不同的运输方式。因此,本文解决了多式联运网络上的选路问题。引入的问题同时遵循四个目标,这是本文的主要贡献。确定供应商和配送中心之间的多式联运路线,查找模式更改设施,查找配送中心,并确定从配送中心到零售商的产品交付行程。提出了用于该问题的整数线性规划,并提出了一种具有新染色体结构的遗传算法来解决该问题。拟议的染色体结构由两个不同部分组成,用于模型的多式联运和位置路由部分。根据文献中公开的数据,生成并求解了两个大小不同的数值案例。此外,设计了不同的成本方案以更好地分析模型和算法性能。结果表明,该算法可以在合理的时间内有效解决大型问题,即使在更长的时间内,GAMS软件也无法达到最佳解决方案。

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