Multi-objective optimisation of surplus food recovery and redistribution units in India

Nistha Dubey and Ajinkya Tanksale

International Journal of Operational Research, 2025, vol. 53, issue 2, 228-254

Abstract: Food banks are not-for-profit organisations that collect surplus and leftover food and distribute it to unfortunate people of society with an aim to alleviate hunger. The problem can be modelled as multi depot-VRP. We endeavour three primary objectives of food banks - efficiency, effectiveness, and equity. The measure for efficiency is minimum total transportation cost, minimum total shortage for effectiveness, and minimum of the maximum shortage of network is taken for equity. This paper proposes a MILP model for multi-objective optimisation of surplus food recovery and redistribution in India. Our study is the first to evaluate Indian food banks from a multi-objective perspective. To solve the proposed problem, state-of-the-art-solver Gurobi is used for weighted sum method, augmented ∈-constraint method, and augmented weighted Tchebycheff methods. Non-dominated sorting genetic algorithm is developed to solve the larger network problems. The results of the computational experiments show significant trade-off behaviour between efficiency and effectiveness.

Keywords: food banks; vehicle routing problem; VRP; multi-depot; non-dominated sorting genetic algorithm; NSGA-II; multi-objective; split loads; India. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=146895 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:53:y:2025:i:2:p:228-254

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().