Innovative Applications of O.R.
Budget allocation of food procurement for natural disaster response

https://doi.org/10.1016/j.ejor.2023.05.015Get rights and content
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Highlights

  • We present methods to optimise when and how much to buy when procuring food supplies for disasters.

  • Uses real data on disasters from West Java, Indonesia.

  • Compares approaches for finding a robust solution to a practical problem with uncertainty.

  • Contributes to the literature on humanitarian food supply chains.

Abstract

This paper studies a variant of the lot sizing problem that arises in the context of disaster management. In this problem, a fixed budget has to be allocated efficiently over multiple time periods to procure large quantities of a staple food that will be stored and later delivered to people affected by disaster strikes whose numbers are unknown in advance. Starting from the deterministic model where perfect information is assumed, different formulations to address the uncertainties are constructed: classical robust optimisation, risk-minimisation stochastic programming, and adjustable robust optimisation. Experiments conducted using data from West Java, Indonesia allow us to discuss the advantages and drawbacks of each method. Our methods constitute a toolbox to support decision makers with making procurement decisions and answering managerial questions such as which annual budget is fair and safe, or when storage peaks are likely to occur.

Keywords

Humanitarian logistics
Disaster management
Procurement lot sizing
Robust optimisation
Stochastic programming

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