Budget allocation of food procurement for natural disaster response

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 infor-mation 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.& COPY; 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

Automated summary

This paper examines a variant of the lot sizing problem in the context of disaster management. Different formulations, including classical robust optimization, risk-minimization stochastic programming, and adjustable robust optimization, are proposed to address uncertainties. Experiments using data from West Java, Indonesia are conducted to evaluate the advantages and drawbacks of each method. Overall, this research provides decision makers with a toolbox for procurement decisions and offers insights into budget allocation and storage management in disaster scenarios.