Developing model-based software to optimise wheat storage and transportation: A real-world application

This paper investigates a real-world case of a logistical management problem. We determine the optimal amounts of wheat to be transported from each producing province to each consuming province per month across the year. The problem was formulated as a linear integer programming (LIP) model, which could then be solved using LINGO optimisation software. As the LIP model needs to be run each month, a genetic algorithm (GA) was developed to solve the real-size problems in a reasonable time period. The solutions obtained by LINGO are compared with those obtained from the GA and the results show that the developed GA is efficient in terms of computational time and the quality of the solutions obtained.

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► It describes a real-life logistics problem in agri-food industry in a country.
► It models the problem mathematically using some creations to cope the complexity.
► It develops a genetic algorithm to solve the designed model.
► It shows the output of the problem using real data and does sensitivity analysis.