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Article | Open Access

Facilities Location in the Supply Chain Network Using an Iterated Local Search Algorithm

Ali Abdi Seyedkolaei1,2( ), Seyed Hadi Nasseri1,2
Department of Applied Mathematics, University of Mazandaran, Babolsar 48175, Iran
Research Center of Optimization and Logistics, University of Mazandaran, Babolsar 48175, Iran
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Abstract

The supply chain design problem is one of the important problems in supply chain management. In this problem, the goal is to locate several facilities for distribution centers in different geographical areas to cover customer demands. In the model presented in this paper, customer demand is met through distribution centers, while these distribution centers supply products from manufacturing plants. In this paper, a mathematical model of integer linear programming is presented that, in addition to the optimal supply chain network design, considers the facility's location. This model aims to minimize the costs of sending products from the factory to distribution centers, from distribution centers to customers, and establishing distribution centers. To evaluate the proposed model, different network samples were created randomly on small, medium and large scales for experiments. In order to perform the experiments, a linear programming solver (LP Solver) and an iterated local search algorithm were used to compare the performance of each of these methods to find the optimal solution. These experiments show the superiority of the iterated local search algorithm compared to LP Solver in achieving the optimal solution in the shortest runtime for all instances.

Keywords

supply chaindistribution centerslocationiterated local search algorithm

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Fuzzy Information and Engineering
Volume 15 Issue 1,
March 2023
Pages 14-25
DOI: 10.26599/FIE.2023.9270002
Cite this article:
Seyedkolaei AA, Nasseri SH. Facilities Location in the Supply Chain Network Using an Iterated Local Search Algorithm. Fuzzy Information and Engineering, 2023, 15(1): 14-25. https://doi.org/10.26599/FIE.2023.9270002

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Received: 02 October 2022
Revised: 24 November 2022
Accepted: 29 December 2022
Published: 07 March 2023
© The Author(s) 2023. Published by Tsinghua University Press.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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