In a supply chain system, deteriorating production systems implement inventory models to account for transportation costs based on the quantity ordered and the distance between the supplier's manufacturing facility and the retailer's warehouse. A crisp model is first created, and then an appropriate fuzzy model is created, taking into account various fuzzy parameters that affect inventory cost. Transportation costs are rarely considered in inventory modelling, as distinct models have been built for suppliers and retailers. The current methodology minimizes the overall average inventory cost of the supply chain, which includes suppliers and retailers jointly, in a clear and fuzzy environment. The retailer's demand parameter is said to be determined by the level of inventory. At the warehouses of suppliers and retailers, degradation happens continuously during production and storage.The objective of this article is to establish an inventory model that, when combined with the signed distance method to defuzzify the fuzzy numbers, optimizes the supply chain's overall average inventory cost. Sensitivity analysis has been done on the model's fuzzy parameters, and a numerical example is provided to confirm the applicability of the model.