Fuzzy inventory model for deteriorating items in a green supply chain with carbon concerned demand

Abstract

With the environment deterioration becoming a serious concern, numerous industries have realized that it’s critical to focus on manufacturing with reduced waste and low carbon emission. Studies show that consumers are getting cognizant of environment preservation and prefer low-carbon developed products. It is seen that in some cases, customers are willing to pay even more for products developed using low carbon emission technologies. Furthermore, government initiatives towards going green has resulted in industries focusing on reducing their carbon footprints throughout the supply chain by employing green supply chain methodologies. In this study, we will develop an inventory model for deteriorating items in green supply chain considering recycling, reverse logistics and remanufacturing. Demand is assumed to be carbon dependent. Products are considered to be deteriorating in nature with time dependent deterioration rate. A crisp model is developed to minimize total average cost. In the crisp model, it is assumed that demand, deterioration and returned rate are precisely known. However, in reality these parameters are imprecise in nature. To model this impreciseness, a fuzzy model is developing considering these parameters as triangular fuzzy numbers. Total cost function is defuzzified using signed distance method and is shown to be convex and a unique solution exists. Numerical analysis is carried out for both crisp and fuzzy cases.