Document Type : Research Paper
Authors
1 Ph.D. Candidate, Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran.
2 Prof. Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran.
3 Professor, Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabatabaei University, Tehran, Iran.
Abstract
In the context of developing a robust multi-objective optimization framework for designing sustainable supply chain networks for perishable items under uncertainty, this paper provides an overview of a possibilistic framework. Using the three pillars of sustainability (i.e., economic, environmental, and social), the proposed framework seeks to minimize overall supply chain costs, minimize CO₂ emissions, and maximize regional employment opportunities. The proposed framework addresses the uncertainties associated with product demand (sales), shelf life, and shipping/transportation conditions. To accomplish this, the proposed framework employs fuzzy trapezoidal numbers (which can model how much variation a number might have) in combination with a robust possibilistic programming structure. The objective of the proposed framework is twofold: 1) to solve for and balance each of the objectives and 2) to use GAMS to implement the LP-Metric method. Validation of the model has been conducted through extensive utilization of numerical experiments to create a variety of examples (small, medium, and large-sized), which support the proposed approach's ability to produce stable (balanced) solutions, regardless of the size of the example. Additionally, results indicate that the cost of the system (i.e., total supply chain cost) increases with the size of the network, while the number of employment opportunities created is directly related to network size; the amount of environmental impact is not increased by network size. Finally, results from the model establish that the proposed robust possibilistic approach exhibits superior performance to traditional models based solely upon determinism by producing consistently higher levels of reliability and resiliency within supply chain configurations, thereby providing an invaluable source of potential inputs for the management of perishable goods.
Keywords
- Sustainable supply chain
- Perishable products
- Robust possibilistic programming
- Fuzzy optimization
- Multi-objective model
- Uncertainty
Main Subjects
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