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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Acknowledgements
The first two authors sincerely thank CONACYT (National Council of Science and Technology from Mexico), PAICYT IT480-15, and FIME-UANL for their support to this work. The research activity of the third author has been partially funded by Tecnologico de Monterrey—Research Group in Optimization and Data Science 0822B01006.
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Gómez-Pantoja, J.Á., Salazar-Aguilar, M.A. & González-Velarde, J.L. The food bank resource allocation problem. TOP 29, 266–286 (2021). https://doi.org/10.1007/s11750-020-00581-y
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DOI: https://doi.org/10.1007/s11750-020-00581-y