Optimising food baskets in a local food pantry: The case study of El Rebost

• Optimising food baskets considering nutritional needs and dietary restrictions. • Uses a multi-objective MILP model with a relaxed lexicographic optimisation approach. • Significantly improves nutritional coverage, variety, and equity in distribution. • Real-world validation using a case study of the El Rebost food pantry in Spain. • Provides a framework adaptable for other food banks to combat food insecurity. Food banks and food pantries play a crucial role in addressing global food insecurity by collecting and distributing food resources to vulnerable populations. However, effectively addressing diverse nutritional needs and achieving fairness under the limited availability of food resources poses a significant challenge. This study presents a solution procedure for optimising the composition of personalised food baskets delivered by food pantries to needy families. The procedure addresses three key challenges not explored in the literature: allocating discrete food packages from limited stock, accommodating individual dietary restrictions and nutritional requirements, and balancing multiple distribution objectives. We propose a multi-objective mixed-integer linear programming model that maximises the minimum nutritional coverage across all nutrients and beneficiaries, maximises the minimum food product variety, and minimises inequity in food allocation. The objectives are prioritised using relaxed lexicographic optimisation, allowing controlled trade-offs through a relaxation parameter. Applied to 25 weekly instances from El Rebost, a food pantry in Terrassa, Spain, the procedure demonstrates significant improvements over current food baskets – increasing minimum nutritional coverage by 119%, minimum product variety by 17.1%, and reducing inequity by 28% on average. Sensitivity analyses confirm the model’s robustness under varying food resource availability and across larger-scale problem instances. The framework provides food banks and food pantries with a systematic approach for designing nutritionally balanced, diverse, and equitably distributed food baskets tailored to beneficiaries’ dietary needs.

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Publication Details

Journal
Computers & Industrial Engineering
Published
2025-03-17
DOI
https://doi.org/10.1016/j.cie.2025.111053
Primary Topic
Food Waste Reduction and Sustainability
Type
article
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article

Optimising food baskets in a local food pantry: The case study of El Rebost

Laia Ferrer‐Martí, Rafael Pastor, Albert Soler-Noguera, Marc Juanpera et al.
Computers & Industrial Engineering
Food Waste Reduction and Sustainability
article

Optimising food baskets in a local food pantry: The case study of El Rebost

Laia Ferrer‐Martí, Rafael Pastor, Albert Soler-Noguera, Marc Juanpera, Pol Gil-Figuerola, H. Ramalhinho
article en

Abstract

• Optimising food baskets considering nutritional needs and dietary restrictions. • Uses a multi-objective MILP model with a relaxed lexicographic optimisation approach. • Significantly improves nutritional coverage, variety, and equity in distribution. • Real-world validation using a case study of the El Rebost food pantry in Spain. • Provides a framework adaptable for other food banks to combat food insecurity. Food banks and food pantries play a crucial role in addressing global food insecurity by collecting and distributing food resources to vulnerable populations. However, effectively addressing diverse nutritional needs and achieving fairness under the limited availability of food resources poses a significant challenge. This study presents a solution procedure for optimising the composition of personalised food baskets delivered by food pantries to needy families. The procedure addresses three key challenges not explored in the literature: allocating discrete food packages from limited stock, accommodating individual dietary restrictions and nutritional requirements, and balancing multiple distribution objectives. We propose a multi-objective mixed-integer linear programming model that maximises the minimum nutritional coverage across all nutrients and beneficiaries, maximises the minimum food product variety, and minimises inequity in food allocation. The objectives are prioritised using relaxed lexicographic optimisation, allowing controlled trade-offs through a relaxation parameter. Applied to 25 weekly instances from El Rebost, a food pantry in Terrassa, Spain, the procedure demonstrates significant improvements over current food baskets – increasing minimum nutritional coverage by 119%, minimum product variety by 17.1%, and reducing inequity by 28% on average. Sensitivity analyses confirm the model’s robustness under varying food resource availability and across larger-scale problem instances. The framework provides food banks and food pantries with a systematic approach for designing nutritionally balanced, diverse, and equitably distributed food baskets tailored to beneficiaries’ dietary needs.

Computers & Industrial EngineeringVol. 203
Universitat Pompeu Fabra (ES), Consorci Sanitari de Terrassa (ES), Universitat Politècnica de Catalunya (ES)
Zero hunger
Openalex Percentile: Top 95%
Food Waste Reduction and Sustainability
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