Abstract
Closed-loop supply chains have attracted more attention by researchers and practitioners due to strong government regulations, environmental issues, social responsibilities and natural resource constraints over past few years. This paper presents a mixed-integer linear programming model to design a closed-loop supply chain network and optimizing pricing policies under random disruption. Reusing the returned products is applied as a resilience strategy to cope with the waste of energy and improving supply efficiency. Moreover, it is necessary to find the optimal prices for both final and returned products. Therefore, the model is formulated based on demand function and it maximizes total supply chain’s profit. Finally, its application is explored through using the real data of an industrial company in glass industry.
Highlights
The globalization of economic activities along with rapid improvement of information technology in recent years result in shorter circulation of life cycles, smaller transportation capacity and customer’s dynamic behavior in terms of choices and demands
The model takes the risks of disruption into consideration in designing phase of a multi-period and multi-product CLSC network design
The resilience concept is presented by considering disruption risks in a CLSCN
Summary
The globalization of economic activities along with rapid improvement of information technology in recent years result in shorter circulation of life cycles, smaller transportation capacity and customer’s dynamic behavior in terms of choices and demands. This causes the demands to be insecure and increases the significance of supply chain design, . The disruptions in supply chain are unplanned and unpredictable events which spoils the normal process of materials (Ghomi-Avili, Naeini et al 2018) It puts the supply chain companies in danger of finance and operational risks
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