A novel multi-objective optimization model for integrated problem of green closed loop supply chain network design and quantity discount. (20th September 2018)

• Record Type: Journal Article
• Authors: Sadeghi Rad, Reza; Nahavandi, Nasim
• Is Part Of: Journal of cleaner production. Volume 196(2018)
• Page Start: 1549
• Page End: 1565
• Publication Date: 2018-09-20
• Subjects: Closed-loop green supply chain network -- Carbon dioxide emission -- Quantity discount -- Multi-objective -- Transport mode selection; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2018.06.034
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: With the increasing importance of the efficient purchasing function, supplier selection decisions have become more strategic in supply chain management. In the past few years, the closed-loop green supply chain network has faced increasing attention with regard to the environmental regulations, social awareness and customer pressure. In order to cope with these two issues, this paper proposes an integrated mathematical programming model for multi-period, multi-product and capacitated closed loop green supply chain in which suppliers offer quantity discounts in order to motivate buyers to purchase more. The model objective functions are the minimization of economic cost and environmental emissions and maximization of customer satisfaction with determining best suppliers, purchasing amount, location-allocation facilities, transportation mode, technology type, carbon dioxide emissions, inventory levels and flows between facilities. Sensitivity analysis is conducted to validate the model for some test problems. Computational results show the effectiveness and applicability of the proposed model. Also, results have revealed that supply chain total costs are significantly reduced by considering quantity discount.