Inventory pre-positioning for humanitarian operations

Abstract

This research examines the impact of inventory pre-positioning on humanitarian operations. The study identifies optimal locations for warehousing non-consumable inventories required for initial deployment of aid. These facility location problems are geometric optimizations using mean annual homeless resulting from hazards (atmospheric disruptions, floods, waves, landslides, seismic disruptions, volcanoes and wildfires) as an indirect estimation of demand for infrastructure inventory. Minimization of per capita distance, or the average global distance from the nearest warehouse to a forecasted homeless person, is advanced as the objective. An array of formulations, solved using mixed-integer linear programs, predict optimal facility configurations, and corresponding per capita distances, under incremental facility constraints; thereby measuring sensitivity of mean distance to facility proliferation. The problems are devised to also gather insights into maximal covering and the effects of initial conditions.

(cont.) Moreover, demand patterns, along with correlated variables such as population and hazard frequency, offer views of regional vulnerability to natural disasters. The results also exhibit the absence of re-configuration, indicating that location decisions may not be impacted by the number of facilities planned.