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Supply Chain Sustainability Assessment using Hybrid Simulation-Optimization Modeling
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Farzaneh Rezaee   , Nazanin Pilevari * , Reza Radfar |
| , pilevari.nazanin@wtiau.ac.ir |
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Abstract: (736 Views) |
Abstract
Objective: From economic, environmental and social perspectives, the sustainability of the supply chain can give a competitive advantage to organizations. By designing a hybrid discrete event agent-based simulation model based on the simulation-optimization approach and meta-heuristic algorithms, this study has sought to evaluate the sustainability of the supply chain and improve the economic, environmental and social objectives of the supply chain.
Method: First, by identifying supply chain agents, an agent-based simulation model is developed. After designing the hybrid simulation model, the verification and validation phases are performed. By combining the simulation model with meta-heuristic algorithms and using the simulation-optimization approach, the optimal/near-optimal values of the components affecting the sustainability of the supply chain are finally extracted.
Findings: In addition to being able to reflect all the complexities of supply chains, the hybrid simulation optimization approach can also improve the key components affecting the sustainability of the supply chain.
Results: Implementation of sustainable supply chain components without optimizing the key variables of the supply chain can lead to the deterioration of performance and sustainability of the supply chain. The components of the maximum levels of product and inventory maintenance and how to implement environmental and social aspects in all the elements of the supply chain have a direct effect on the chain performance and should have appropriate values in different scenarios.
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| Keywords: sustainable supply chain management, agent-based modeling, simulation-optimization approach |
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Full-Text [PDF 934 kb]
(1460 Downloads)
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Type of Study: Original |
Subject:
Supply Chain Management and Logistics
Received: 2023/11/13 | Accepted: 2024/01/9 | Published: 2024/01/24
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