Modelling An Inventory Model For Food Grains In Northern Telangana Using Meta Heuristic Techniques.

Abstract

To explore the inventory optimization of circulation businesses, a demand analysis was conducted first, with the supply-demand balance in mind. Cold storage facilities are one of India's most rapidly growing industries. Despite a high production of perishable food, India's cold storage business is still in its infancy. Increasing urbanization and the rise of organized retail, food service, and food processing sectors, on the other hand, are leading to the growth of India's cold storage chain industry. This study used a multi-level Public Distribution System (PDS) of facilities such as godowns and distribution centers such as Mandal Level Stock Points (MLSPs). Traditional optimization approaches usually necessitate the formulation of an explicit mathematical model based on specific assumptions. The validity of such models and methodologies for real-world applications is primarily determined by how closely the beliefs reflect reality. In contrast to previous methods, meta-heuristics do not require such assumptions, allowing for more realistic modelling of the inventory control system and its solution. It is proposed in this work to provide a model to reduce overall overheads, including ordering and reordering expenses and inventory holding costs, enabling seamless product distribution from warehouses to MLSPs and fair pricing shops (FPS). The ideal ending inventory at the end of each time period and a total variable cost estimate for Food Corporation of India (FCI) using realistic data for the Binary Particle Swarm Optimization (BPSO) technique. When comparing the overall cost of the existing system to the total cost of the PDS problem under discussion using the BPSO method, roughly forty cores and 33.47% decrease the total cost.