The closed-loop supply chain management (CLSCM) is an attractive research field for the corporate and academic worlds; however, closing the loop is not a simple task. Reverse logistics activities increase management complexities and uncertainties by establishing multi-fold collection and return management processes. Unlike traditional supply chain management, where managers deal with only stochastic demand, in closed-loop supply chain management, they deal with both stochastic demand and returns, which increases the cumulative uncertainty in the system. Firms usually use disposable packaging, and demand uncertainties also increase the negative environmental implications of logistics activities. This study aims to investigate optimal remanufacturing strategy and reusable packaging capacity under stochastic demand and return rate for single and multi-retailer closed-loop supply chain models. The results show that a hybrid policy is an optimal option for both single and multi-retailer cases; however, the rate of remanufacturing increases for multiple-retailers. Furthermore, remanufacturing cost, manufacturing cost, and ordering cost of retailers are the principal drivers of hybrid supply chain management. The results further suggest that supply chain managers should reduce manufacturing and remanufacturing costs because they play a central role in deciding the optimal remanufacturing rate. Increasing the remanufacturing rate increases ordering quantities and reduces setup and ordering costs in the system. Thus the remanufacturing is a relatively inexpensive policy for supply chains with higher setup and ordering costs. Numerical examples, sensitivity analysis, and comparative study show the robustness and validity of the proposed model.
Bibliographical noteFunding Information:
This research was supported by the Yonsei University Research Fund of 2020 (Project Number 2020-22-0509 ).
© 2020 Elsevier Ltd
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Environmental Science(all)
- Strategy and Management
- Industrial and Manufacturing Engineering