Bi-objective mathematical modeling for the design of closed-loop resilient supply chain networks

Subject Areas :

Maryam Bahadoran ¹ , Mehdi Fadaei Eshkiki ^{2 *} , Mohamad Taleghani ³ , Mahdi Homayounfar ⁴

1 - Doctoral student of Industrial Management Department, Rasht Branch, Islamic Azad University, Rasht, Iran
2 - Assistant Professor, Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran.
3 - Associate Professor, Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran.
4 - Assistant Professor, Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran.

Received: 2024-10-02 Accepted : 2024-12-19 Published : 2024-12-29

Keywords: Supply chain, closed loop, resilience, multi-objective optimization,

Abstract :

Purpose : In highly disrupted and risk-prone operational environments, proper design of the supply chain network can enhance factors such as sustainability, disruption mitigation, and reliability to ensure the continuity of operations. To prevent inefficiencies caused by separate designs, it is essential to integrate the design of forward and reverse networks. In a closed-loop supply chain, in addition to the normal flow of goods from suppliers to end customers, attention is also paid to the reverse flow of products for recycling, remanufacturing, or disposal.

Research Methodology : In this study, a resilient closed-loop supply chain network is designed under probabilistic risk and disruption conditions at the levels of manufacturers, distributors, and customers. The proposed model simultaneously maximizes the number of nodes and minimizes the total cost. The bi-objective optimization problem is solved using the weighted comprehensive criterion method for P = 1 and P = 2.

Findings: According to the results, the proposed model can determine the quantity of produced goods, high-capacity production volumes, product transportation routes, flow volumes along each path, and the values of the objective functions. Finally, a sensitivity analysis was conducted on the probability of node and path failures. The results show that reducing the failure probability in each path leads to the greatest improvement in the second objective function.

Originality / Value  : The value of this research lies in the development of a resilient closed-loop supply chain model that simultaneously incorporates multi-objective optimization and sensitivity analysis to address disruptions across different supply chain levels. This model provides more comprehensive and accurate decision-making capabilities for supply chain managers in high-risk environments.

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