Green supply chain model for decaying raw materials with reverse logistics and preservation investment under a fuzzy environment

¹ Department of Mathematics, H.N.B. Government Post Graduate College, Khatima, Uttarakhand 262308, India
² Department of Mathematics, M.B.P.G. College, Haldwani City, Nainital 263139, India
³ Department of Mathematics, Government Degree College, Kotabag 263159, India
⁴ Department of Mathematics, Chaudhary Charan Singh University, Meerut, Uttar Pradesh 250004, India
⁵ Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, South Korea
⁶ Center for Global Health Research, Saveetha Medical College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu 250004, India
⁷ Department of Mathematics, Lovely Professional University, Phagwara, Punjab 144411, India

^* Corresponding author: bsbiswajitsarkar@gmail.com

Received: 5 August 2023
Accepted: 8 April 2025

Abstract

In countries around the world, whether developed or developing, there is increasing competition in the industry to strengthen their economies and waste. Managing the supply chain of many goods becomes an essential part of transportation. Along with this, in inventory management, products are most likely to require maintenance, and the production and transportation work necessitate different handling procedures. When a product is manufactured using raw materials in a production house, the manufacturer checks the inventory by producing for a certain time interval. Only some unusable products or products sent by the retailer that cannot be used are sent to the production house again for new products. This study develops an integrated green design production model for deteriorating items with reverse logistics and preservation technology investment under inflation. Firstly, the model is developed in a crisp environment, and then it is extended to a fuzzy environment. Optimal solutions are established numerically, and comparative analysis is performed to validate the result. A comparison study is provided. Finally, sensitivity analysis is done for some influential parameters. It is observed that in each part of the supply chain, the deterioration rate for perishable items is almost uncertain due to several reasons. For that, special methods are used here to reduce the total cost. Results show that the preservation model under a fuzzy environment provides 0.76% less cost than a crisp environment. The cycle time of the retailer and the production time of the producer is less in a fuzzy environment than in a crisp environment.