Comparative Study for Facilities Location Problem in Supply Chain Design

Comparative Study for Facilities Location Problem in Supply Chain Design

Ikram Mankour, Khadidja Yachba
Copyright: © 2022 |Pages: 16
DOI: 10.4018/IJSIR.304718
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Abstract

The interest in supply chains has increased in the last few years. The supply chain optimization aims to reduce the delays and costs generated between suppliers and customers. The researchers focus primarily on the supply chain design to transport products to clients. This paper attempts to find an optimal warehouse location using a metaheuristic method. The goal is to select the optimum warehouse location. FLP-GA (Facility Location Problem - Genetic Algorithms) is the proposed approach based on genetic algorithms that reduce the number of warehouses to be opened, the overall costs, and the distances between them from a set of customers and candidate warehouses. The authors compared the approach with three other methods. This approach can select a reduced number of warehouses with minimal cost.
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Several studies have emphasized the optimization of the logistics system. The researchers are specifically interested in optimizing the facilities' location problems in a supply chain. To more concretely explain the concept of supply chain optimization and facility location problem, the researchers present some recent related works in chronological order:

Amin and Fazle (2017) applied a mathematical model based on fuzzy programming to solve the problem of supply chain network optimization.

In Yachba (2017), the author proposed a critical study to optimize the placement of containers in a seaport. The authors presented two approaches (genetic algorithms, branch and bound) by a decisional model to solve the problem, optimize the storage space available, and manage incoming and outgoing containers.

Ortiz-Astorquiza et al. (2018) presented a comprehensive review of multi-level facility location problems. They first presented the main characteristics of these problems and identified three categories. Then, they discussed some similarities and differences with related areas. The authors presented formulations, algorithms, and applications, tracing the field's historical development.

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