Designing a Bi-Objective Stochastic Model for a Resilient Supply Chain Network taking into Account Support Supplier and Its Financial and Physical Flows

Document Type : Original Article

Authors

1 Ph.D. Student, Department of Industrial Management and Information Technology, Faculty of Management and Accounting, Shahid Beheshti University.

2 Assistant Professor, Department of Industrial Management and Information Technology, Faculty of Management and Accounting, Shahid Beheshti University.

3 Associate Professor, Department of Industrial Management and Information Technology, Faculty of Management and Accounting, Shahid Beheshti University.

Abstract

In the present unstable business environment, supply chains are considerably impacted by disruptions, necessitating the implementation of resilience strategies. These strategies, however, pose significant financial challenges for companies. Therefore, financing is essential in developing resilient supply chain networks. In addition to utilizing existing capital, options such as bank loans and trade credit can be employed to alleviate the financial burden and enhance working capital.  The present scholarship has failed to address the issue of financial strain resulting from the adoption of resilience strategies. Additionally, the significance of trade credit and repayment scheduling in all levels of the supply chain network also left under-researched. To fill this research gap, this paper proposes a three-tiered supply chain network consisting of main/support suppliers, factories, and distribution centers under uncertain demand conditions. The network is developed to effectively handle demand uncertainty and achieve optimal net present value and demand estimation. To solve the bi-objective model of the study, a preemptive fuzzy ideal programming approach accompanied by the implementation of the CPLEX solver is utilized. The findings lend support to the importance of securing financial support for support suppliers and establishing effective trade credit agreements across all levels of the supply chain.

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References

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