Multi-objective robust optimization for multi-stage-multi-product agile closed-loop supply chain under uncertainty in the context of circular economy
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| Vydáno v: | Journal of Enterprise Information Management vol. 38, no. 1 (2025), p. 94-126 |
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| Další autoři: | , |
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Emerald Group Publishing Limited
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| 024 | 7 | |a 10.1108/JEIM-12-2020-0514 |2 doi | |
| 035 | |a 3158232206 | ||
| 045 | 2 | |b d20250101 |b d20250228 | |
| 084 | |a 11839 |2 nlm | ||
| 100 | 1 | |a Saeid Jafarzadeh Ghoushchi |u Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran | |
| 245 | 1 | |a Multi-objective robust optimization for multi-stage-multi-product agile closed-loop supply chain under uncertainty in the context of circular economy | |
| 260 | |b Emerald Group Publishing Limited |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a PurposeA circular economy (CE) is an economic system that tries to eliminate waste and continually use resources. Due to growing environmental concerns, supply chain (SC) design should be based on the CE considerations. In addition, responding and satisfying customers are the challenges managers constantly encounter. This study aims to improve the design of an agile closed-loop supply chain (CLSC) from the CE point of view.Design/methodology/approachIn this research, a new multi-stage, multi-product and multi-period design of a CLSC network under uncertainty is proposed that aligns with the goals of CE and SC participants. Recycling of goods is an important part of the CLSC. Therefore, a multi-objective mixed-integer linear programming model (MILP) is proposed to formulate the problem. Besides, a robust counterpart of multi-objective MILP is offered based on robust optimization to cope with the uncertainty of parameters. Finally, the proposed model is solved using the e-constraint method.FindingsThe proposed model aims to provide the strategic choice of economic order to the suppliers and third-party logistic companies. The present study, which is carried out using a numerical example and sensitivity analysis, provides a robust model and solution methodology that are effective and applicable in CE-related problems.Practical implicationsThis study shows how all upstream and downstream units of the SC network must work integrated to meet customer needs considering the CE context.Originality/valueThe main goal of the CE is to optimize resources, reduce the use of raw materials, and revitalize waste by recycling. In this study, a comprehensive model that can consider both SC design and CE necessities is developed that considers all SC participants. | |
| 653 | |a Linear programming | ||
| 653 | |a Customer satisfaction | ||
| 653 | |a Integer programming | ||
| 653 | |a Sensitivity analysis | ||
| 653 | |a Product returns | ||
| 653 | |a Parameter sensitivity | ||
| 653 | |a Context | ||
| 653 | |a Optimization | ||
| 653 | |a Closed loops | ||
| 653 | |a Parameter robustness | ||
| 653 | |a Environmental impact | ||
| 653 | |a Raw materials | ||
| 653 | |a Multiple objective analysis | ||
| 653 | |a Parameter uncertainty | ||
| 653 | |a Circular economy | ||
| 653 | |a Suppliers | ||
| 653 | |a Mathematical programming | ||
| 653 | |a Customers | ||
| 653 | |a Design improvements | ||
| 653 | |a Regeneration | ||
| 653 | |a Profit margins | ||
| 653 | |a Costs | ||
| 653 | |a Genetic algorithms | ||
| 653 | |a Decision making | ||
| 653 | |a Consumption | ||
| 653 | |a Supply chains | ||
| 653 | |a Robustness (mathematics) | ||
| 653 | |a Mixed integer | ||
| 653 | |a Logistics | ||
| 653 | |a Agile manufacturing | ||
| 653 | |a Recycling | ||
| 653 | |a Design | ||
| 653 | |a Economics | ||
| 653 | |a Objectives | ||
| 653 | |a Uncertainty | ||
| 653 | |a Models | ||
| 653 | |a Supply | ||
| 653 | |a Hazardous wastes | ||
| 653 | |a Research methodology | ||
| 653 | |a Consumers | ||
| 653 | |a Economic systems | ||
| 653 | |a Materials | ||
| 653 | |a Economic | ||
| 700 | 1 | |a Hushyar, Iman |u Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran | |
| 700 | 1 | |a Sabri-Laghaie, Kamyar |u Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran | |
| 773 | 0 | |t Journal of Enterprise Information Management |g vol. 38, no. 1 (2025), p. 94-126 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3158232206/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3158232206/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3158232206/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |