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Allocation Optimization Problem for Peruvian Food Bank
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Author(s): Ricardo Campos-Caycho (Pontificia Universidad Católica, Peru), Renzo A. Benavente-Sotelo (Ponticia Universidad Católica del Perú, Peru), Yasser A. Hidalgo-Gómez (Pontificia Universidad Católica del Perú, Peru), Christian A. Blas-Bazán (Pontificia Universidad Católica del Perú, Peru), Pamela Ivonne Borja-Ramos (Pontificia Universidad Católica del Perú, Peru), Stephanie M. Dueñas-Calderón (Pontificia Universidad Católica del Perú, Peru), Patricia Elkfury-Cominges (Pontificia Universidad Católica del Perú, Peru), Pamela Arista-Yampi (Pontificia Universidad Católica del Perú, Peru)and Jorge Luis Yupanqui-Chacón (Pontificia Universidad Católica del Perú, Peru)
Copyright: 2021
Pages: 15
Source title:
Research Anthology on Food Waste Reduction and Alternative Diets for Food and Nutrition Security
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-5354-1.ch035
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Abstract
Food insecurity is a recurrent condition in which members of a household do not have enough food to cover their nutritional needs; this condition contributes to increasing social vulnerability of those affected. In Peru, there are more than 9 million people who suffer this condition, which generates malnutrition and anemia, mostly in children. On the other hand, the waste of food is associated with production the large amounts of greenhouse gas emissions that affect global warming. According to reports in Peru, 20% of what is food produced becomes waste. This scenario in terms of food for Peruvians represents 3 billion calories in wasted food that could feed 2 million people. The Peruvian Food Bank manages food donations, ensuring this food can reach people in need through humanitarian aid entities. This applied research work uses the tools of operations research to determine a solution to the problem of maximizing the combination of food orders to be distributed based on their total nutritional value to the beneficiaries, seeking maximum coverage and minimum logistic costs.
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