A Multi-stage Stochastic Programming Approach for Pre-positioning of Relief Supplies

TL;DR

This paper introduces a multi-stage stochastic programming model to optimize the pre-positioning of relief supplies, accounting for commodity expiration and demand uncertainty, to improve disaster response efficiency.

Contribution

It develops a novel multi-stage stochastic model that dynamically manages relief inventories considering commodity lifetime and costs, aiding relief agencies in decision-making.

Findings

The model effectively reduces response times in disaster scenarios.

Case study demonstrates practical applicability in the US context.

Provides managerial insights for inventory control during disasters.

Abstract

Pre-positioning of relief supplies is an important aspect of disaster operations management that aims at decreasing the response time by advancing procurement and storage of needed supplies. In this paper we consider commodity life-time period with the related costs in keeping the commodity and removing it from the storage when it is close to expiration (i.e. holding and removal cost). We develop a multi-stage stochastic programming model for pre-positioning of relief supplies, which provides relief agencies insight on how to have dynamically control inventories due to uncertain demands when disasters (e.g., hurricane or earthquake) occur. We also present a case study based on mainland United States to illustrate the proposed model as well as provide managerial insights to relief agencies.