An MILP Model for Inventory Transportation

What is it about?

In this work, we investigate a real-life inventory transportation problem faced by the Food Corporation of India (FCI). FCI is the central agency responsible for procurement, storage, and transportation of food grains over a large geographical area of India. Due to lopsided procurement and consumption of major food grains (i.e., rice & wheat) transportation of food grains across the warehouses becomes inevitable. FCI faces a significant challenge to find the optimal amount of food grains to be stored at each warehouse and transported among the warehouses to meet the demand during each period. In this study, we formulate an MILP model to determine the optimal inventory transportation decisions related to food grain transportation in India and demonstrate it via a case study. Commercial optimization packages can be used to solve the problem of this class. However, as we see, they fail to provide a solution for large size problem instances. Therefore, we propose a heuristic-based solution approach to solve the problem. It is seen that under a practical time limit, the proposed heuristic performs significantly well in terms of accuracy as compared to commercial optimizations packages. The nature of the study is generic in nature and can be also applied to various similar real-life problem scenarios.

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Photo by Annie Spratt on Unsplash

Photo by Annie Spratt on Unsplash

Why is it important?

It is a great challenge faced by the FCI to plan the transportation of food grains to avoid shortages over the country as sufficient amount of inventory has to be maintained in each warehouse for strategic buffer level at the end of each period. In this study, an MILP model has been formulated and solved by an efficient heuristics to determine optimal inventory transportation decisions related to food grain transportation.

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