Volume 55, Number 4, July-August 2021
|Page(s)||2285 - 2307|
|Published online||13 August 2021|
Fuzzy reverse logistics inventory model of smart items with two warehouses of a retailer considering carbon emissions
Department of Mathematics, Meerut College, Meerut, Uttar Pradesh, India.
2 Department of Industrial Engineering, Yonsei University, 50 Yonsei- ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, South Korea.
* Corresponding author: firstname.lastname@example.org
Accepted: 5 April 2021
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.
Mathematics Subject Classification: 90B05 / 90B30 / 90C30 / 90C70
Key words: Remanufacturing / two warehouses / carbon emission / learning effect / fuzzy environment
© EDP Sciences, ROADEF, SMAI 2021
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