Development of new hybrid discrete-time perishable inventory model based on Weibull distribution with time-varying demand using system dynamics approach

In the 20th century, there has been a significant development in logistics systems owing to market globalisation. From this perspective, our study focuses on designing novel models of inventory systems to reflect these real-time systems with improved accuracy and eventually design optimal control systems. Many mathematical inventory models lack details. Most of the existing models in the literature neglect the inclusion of closing days despite the shortening of the shelf-lifes of perishable items daily. In this study, a hybrid dynamic discrete-time inventory model with random lifetime perishable products, first in–first out (FIFO) and last in-first out (LIFO) issuing policies, positive lead time, and time-varying demand, including closing days, is developed. It is assumed that the demand is an external input to the model, and thus, it is easy to implement or test various market scenarios. The developed model is fitted to real data obtained from the research on the formation of botulinum toxin on packaged cubed melons and microbial spoilage at various incubation temperatures. Our study shows that the implementation of the Weibull distribution in modelling perishability can improve the accuracy of reflecting the performance of real physical inventory systems. We compare the developed model to an existing one in the literature, considering different issuing policies: FIFO, LIFO, and their combination. The study also includes a comparative analysis of the fixed and random lifetimes of products in terms of closing days.