Maximizing the cost-effectiveness of relief prepositioning inventory and funding assurance strategy by integrating stockpiles, supply contract, and insurance.

Abstract

Relief organizations face numerous challenges, such as funding shortfalls, delays in relief operations, and uncertain demand. A single prepositioning inventory strategy (e.g., stockpiles or supply contract) does not provide an effective solution to these challenges. Therefore, we propose a prepositioning inventory and funding assurance strategy that combines stockpiles, supply contracts with suppliers, and insurance agreements for relief organizations. A deterministic model for the proposed strategy is established along with the objective of maximizing cost-effectiveness. We establish two benchmark models: one combining stockpiles with supply contract and the other combining stockpiles with catastrophe insurance. Then, we compare the relief performance of maximizing cost-effectiveness with minimizing economic costs and minimizing social costs in the proposed strategy. Two-stage robust optimization models are established to address disaster uncertainties. The column-and-constraint generation algorithm is designed to solve robust models, and the Charnes-Cooper transform method is used to transform the fractional objective to an integrated objective. The results of two case studies in Dali and Zhaotong, China, show that the proposed strategy with maximizing cost-effectiveness leads to the acquisition of a moderate amount of insurance with options purchased in quantities that are larger than the stockpiles. Compared with the two benchmark strategies, the proposed strategy can improve cost-effectiveness and achieve cost reduction, especially in years with large disasters. In addition, the objectives of minimizing economic costs and social costs emphasize overly conservative prepositioning inventory and funding assurance strategies, while the optimization results of maximizing cost-effectiveness show robustness when facing disasters with various severities.