Designing a Resilient Multi-Objective Meat Supply Chain: A Robust Possibilistic Approach

Document Type : Research Paper

Authors

Department of Industrial Engineering, Faculty of Engineering, College of Farabi, University of Tehran, Iran

Abstract

Population growth has led to more food demand, especially meat. Designing a supply chain, especially a meat one, is complicated due to the uncertainty of food demand and the perishability of meat. To this aim, we develop a multi-objective mixed-integer linear programming model. The developed model contains four echelons, i.e., farms, slaughterhouses, retailers, and customers. The first objective function minimizes the total costs, the second objective minimizes the distribution time, and the third objective minimizes the network's non-resiliency simultaneously. An enhanced version of the augmented ε-constraint method is employed to solve the suggested model, and a set of Pareto–optimal solutions is found. This study also explores the impact of using the robust possibilistic approach in modeling a supply chain network under uncertainty. Numerical experiments demonstrate that the robust optimization approach brings significantly superior outcomes in comparison to the conventional deterministic approach, and the model provides a practical and valuable tool for real-world supply chain challenges.

Keywords

References

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International Journal of Supply and Operations Management
Volume 11, Issue 3
August 2024
Pages 367-389

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