Designing a Multi-Product Supply Chain Model Despite Disruption in the Supplier With A Stable Mathematical Optimization Approach in Refinery Maintenance Industries
Subject Areas : Industrial Management
Amir Rahimimanesh
1
(PhD Candidate in Industrial Management, Faculty of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht, Iran)
Hamzeh Amin-Tahmasbi
2
(Associate Professor, Department of Industrial Engineering, East Faculty of Technology and Engineering, Gilan University, Rudsar, Iran)
Kambiz Shahroudi
3
(Associate Professor, Faculty of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht, Iran)
Keywords: Supply Chain, Robust Mathematical Optimization, Disturbance, Random Two-Stage Model.,
Abstract :
The supply chain network design problem includes strategic decisions that significantly impact tactical and operational configurations and decisions. The purpose of this research is to provide a multi-product supply chain model that addresses supplier disruptions through a mathematical optimization approach. In line with multi-product supply chain management, there is a need to supply items and raw materials for use in processes, and the supply of these items is subject to uncertainty. Specifically, suppliers may not provide part of the ordered demand to the customer at the required time. To address this uncertainty, two types of suppliers are considered. The first category consists of cheap but unreliable suppliers, while the second category includes reliable suppliers who are more expensive than the first. Items received from suppliers are used in the production or repair process, and a documented model should be provided to manage this process. To integrate these decisions into a cohesive model, previous articles have utilized a random two-stage decision-making model, employing the sampling average approximation method to solve the proposed problem. In this research, due to the dependence of the random two-stage model on non-deterministic parameters (or the worst-case scenario), a robust mathematical model has been developed for the two-stage random model. Finally, the stable model provides the decision-maker with the opportunity to choose the parameters according to the degree of importance of each component.
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