Robust optimization of risk-aware, resilient and sustainable closed-loop supply chain network design with Lagrange relaxation and fix-and-optimize
This study explores a Robust, Risk-aware, Resilient, and Sustainable Closed-Loop Supply Chain Network Design (3RSCLSCND) to tackle demand fluctuation like COVID-19 pandemic. A two-stage robust stochastic multiobjective programming model serves to express the proposed problems in formulae. The objective functions include minimising costs, CO₂ emissions, energy consumption, and maximising employment by applying Conditional Value at Risk (CVaR) to achieve reliability through risk reduction. The Entropic Value at Risk (EVaR) and Minimax method are used to compare with the proposed model. The authors utilise the Lp-Metric method to solve the multiobjective problem. Since this model is complex, the Lagrange relaxation and Fix-and-Optimise algorithm are applied to find lower and upper bounds in large-scale, respectively. The results confirm the superior power of the model offered in estimating costs, energy consumption, environmental pollution, and employment level. This model and algorithms are applicable for other CLSC problems.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/13675567
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Supplemental Notes:
- © 2021 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
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Authors:
- Lotfi, Reza
- Sheikhi, Zohre
- Amra, Mohsen
- AliBakhshi, Mehdi
- Weber, Gerhard-Wilhelm
- Publication Date: 2024-5
Language
- English
Media Info
- Media Type: Web
- Pagination: pp 705-745
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Serial:
- International Journal of Logistics Research and Applications
- Volume: 27
- Issue Number: 5
- Publisher: Taylor & Francis
- ISSN: 1367-5567
- EISSN: 1469-848X
- Serial URL: http://www.tandfonline.com/toc/cjol20/current
Subject/Index Terms
- TRT Terms: Demand; Design; Feedback control; Supply chain management
- Subject Areas: Freight Transportation; Operations and Traffic Management; Planning and Forecasting;
Filing Info
- Accession Number: 01917917
- Record Type: Publication
- Files: TRIS
- Created Date: May 9 2024 9:25AM