A multi-period, multi-product closed-loop supply chain network design: integrated economic and environmental optimization

[EN] This study proposes a novel multi-period, multi-product, and multi-echelon closed-loop supply chain (CLSC) model that simultaneously addresses economic and environmental objectives under dynamic demand and return conditions. Formulated as a mixed-integer linear programming (MILP) model, the fra...

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Detalles Bibliográficos
Autor: Nakhaeinejad, Mahdi
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/232244
Acceso en línea:https://riunet.upv.es/handle/10251/232244
Access Level:acceso abierto
Palabra clave:Closed-loop supply chain
Multi-period planning
Environmental performance
Clean technology
Multi-objective optimization
Descripción
Sumario:[EN] This study proposes a novel multi-period, multi-product, and multi-echelon closed-loop supply chain (CLSC) model that simultaneously addresses economic and environmental objectives under dynamic demand and return conditions. Formulated as a mixed-integer linear programming (MILP) model, the framework incorporates key operational decisions including facility location, production planning, inventory control, recovery, and disposal while integrating sustainability factors such as the use of clean technologies and environmentally friendly materials. A weighted sum approach is applied to generate Pareto-optimal solutions, enabling decision-makers to explore trade-offs between cost minimization and environmental performance. The model is validated through a numerical example, and a detailed sensitivity analysis is conducted to assess the impact of critical parameters on supply chain behavior. The results reveal that while sustainability initiatives may increase operational costs, strategic planning and capacity optimization can achieve effective cost-environment trade-offs. The proposed model offers a comprehensive and practical decision-support tool for designing efficient and sustainable CLSC systems, contributing to both academic research and real-world supply chain practice.