A multi-objective robust fuzzy model for food bank network design examining food nutritional value and freshness

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Kian, R. ORCID: 0000-0001-8786-6349, Ghahremani-Nahr, J. and Ghaderi, A., 2023. A multi-objective robust fuzzy model for food bank network design examining food nutritional value and freshness. In: OR65, Bath, UK, 12-14 September 2023.

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Abstract

To overcome food poverty, charities, and food banks serve as the connection between beneficiaries and donors. They are mostly non-profit organizations and they incur operational costs for storage and delivery of the donated food items. The uncertainty of demand and supply is a challenge to overcome, which necessitates a robust plan. The donated food items are either cold canned food, or hot meals from overproduction of businesses. Thus, their freshness, inventory, and shelf-life cause additional operational challenges in distribution and logistics.

Our study proposes a multi-objective mathematical programming model for a food bank network design to optimize the cost, food freshness, and nutritional value. A robust fuzzy counterpart of the model is developed together with three solution methods including
epsilon-constraint, MOGWO, and NSGA II. According to our numerical study, the MOGWO algorithm shows a better performance in our large instances. Its application in a case study resulted in a supply network with lower cost, smaller fleet size, and higher food quality, although less freshly distributed foods compared to the benchmark network.

The trade-off between the cost and freshness of food is depicted here by examining the shelf-life of products and vehicle capacity. The long-lasting products incur less transportation cost due to the compactness of packaging, and similarly, higher capacity vehicles lead to more cost efficient dispatch with longer routes which decreases the freshness of food.

Item Type:

Conference contribution

Creators:

Kian, R., Ghahremani-Nahr, J. and Ghaderi, A.

Date:

September 2023

Identifiers: