Running the business smoothly for protecting the environment is a significant challenge, on which industries are trying something to do at their level best. Reverse logistics play an important role in system design by reducing environmental consequences and increasing economic and social impacts. Given the recent fluctuations of the market, the production cost and ordering cost are considered triangular fuzzy numbers in this study. Customers' demand is met at the right time, and there is no shortage of items; thus, attention can be paid to two warehouses of a retailer. The setup costs Purchasing costs and deterioration costs of this system are affected by the learning effects, which lead to a decrease in the total cost. Inflation is a significant problem in the market because manufacturing, remanufacturing, and retailers are all affected. This study proposes a reverse logistics system model so that customers can resolve their complaints about defective items and carbon emissions under two warehouses. Numerical results show that the fuzzy model is more economically beneficial than the crisp model, finds that the crisp and fuzzy model saw a difference of 0.34% in total cost. Two numerical examples illustrate this study, and a sensitivity analysis is performed using tables and graph.
|Number of pages||23|
|Journal||RAIRO - Operations Research|
|Publication status||Published - 2021 Jul 1|
Bibliographical noteFunding Information:
Acknowledgements. The work is supported by the National Research Foundation of Korea (NRF) grant, funded by the Korea Government (MSIT) (NRF-2020R1F1A1064460). The first author Subhash Kumar is working at Meerut College,Meerut as a research scholar and thankful to UGC, India, for the financial support.
© 2021 EDP Sciences, ROADEF, SMAI.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science Applications
- Management Science and Operations Research