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Performance evaluation of meta-heuristic algorithms for designing multi-objective multi-product multi-echelon supply chain network

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Abstract

The purpose of this paper is to develop and test three meta-heuristic algorithms to solve large size multi-objective supply chain network design problems. The algorithms are based on tabu search, genetic algorithm, and simulated annealing to find near-optimal global solutions. The three algorithms are designed, coded, and tested, and their parameters are fine tuned. The exact ε-constraint algorithm embedded in the General Algebraic Modeling System is used to validate the results of the three algorithms. The algorithms are compared using a typical multi-objective supply chain model utilizing several performance measures. The measures include the mean ideal distance, diversification metric, and percent of domination, inverted generational distance, and computation time. The results show that the tabu search algorithm outperformed the other two algorithms in terms of the percent of domination and computation time. On the other hand, the simulated annealing solutions are the best in terms of their diversity. The work in this paper is expected to help managers to solve large-scale supply chain problems that arise in oil and gas, petrochemical, and food supply chains.

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Acknowledgements

The authors wish to thank the anonymous reviewers for their supportive suggestions and comments. They also acknowledge the support provided by King Fahd University of Petroleum and Minerals.

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  1. Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    Salih O. Duffuaa

  2. Construction Engineering and Management Department, King Fahd University of Petroleum and Minerals, Dhahran, 31262, Saudi Arabia

    Awsan Mohammed

  3. Interdisciplinary Research Center for Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    Salih O. Duffuaa & Awsan Mohammed

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Duffuaa, S.O., Mohammed, A. Performance evaluation of meta-heuristic algorithms for designing multi-objective multi-product multi-echelon supply chain network. Soft Comput 27, 12223–12248 (2023). https://doi.org/10.1007/s00500-023-08446-9

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