Abstract
One of the global strategic areas in the fight against hunger is the one related to food banks. The mission of food banks is to provide food to people that are in extreme poverty and famine. However, food banks do not have enough resources to supply food to the needy. Hence, hard decisions have to be made every day to determine who will be served, what kind of products, and how many of them will be supplied. In this work, we introduce an optimization model for the Food Bank Resource Allocation Problem, which takes into account inventory management, purchases, product-beneficiary compatibilities, balanced nutrition, and priority of beneficiaries. We also propose an adaptive heuristic to solve large instances of this problem. The mathematical formulation and the proposed heuristic are evaluated over a large set of instances that have been randomly generated based on a real situation of a local food bank. Computational results reveal that our heuristic is able to produce good quality solutions in short computation times.
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