A tabu search based algorithm for the optimal design of multi-objective multi-product supply chain networks

•Large scale multi-objectives supply networks poses computational challenges.•An effective tabu search algorithm is developed, designed, coded and tested.•The developed algorithm outperformed an exact algorithm in commercial software.•The tabu search algorithm offer researchers and partitions a viab...

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Bibliographic Details
Published in:Expert systems with applications Vol. 140; p. 112808
Main Authors: Mohammed, Awsan M., Duffuaa, Salih O.
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.02.2020
Elsevier BV
Subjects:
Algorithms
Design optimization
Embedded systems
Heuristic methods
Meta-heuristic
Mixed integer
Multi-objective
Multiple objective analysis
Network
Production scheduling
Search algorithms
Supply chain
Supply chains
Tabu search
Supply chain
Multi-objective
Meta-heuristic
Tabu search
Network
ISSN:0957-4174, 1873-6793
Online Access:Get full text
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Summary:•Large scale multi-objectives supply networks poses computational challenges.•An effective tabu search algorithm is developed, designed, coded and tested.•The developed algorithm outperformed an exact algorithm in commercial software.•The tabu search algorithm offer researchers and partitions a viable alternative. The optimal design of a supply chain network is a challenging problem, especially for large networks where there are multiple objectives. Such problems are usually formulated as mixed integer programs. Solving this type of network design problem takes a long time using exact algorithms and for large-scale problems it is not even possible. This has given rise to the use of meta-heuristic techniques. In this paper, an effective tabu search algorithm for solving multi-product, multi-objective, multi-stage supply chain design problems is proposed. The desirable characteristics of the algorithm are developed, coded and tested. The results of the developed algorithm are compared with the results obtained by an improved augmented ε-constraint algorithm embedded in the General Algebraic Modeling System (GAMS) software for small-scale, medium-scale, and large-scale instances of multi-objective supply chain problems. Experimental results have shown that the developed algorithm is capable of obtaining high quality solutions within a short computation time, in addition to performing well in other measures such as solution diversity.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2019.07.025