Design of Disaster Relief Logistics Network System by Combining Three Data Envelopment Analysis-based Methods

Abstract

The recent pandemic outbreak and weather-related disasters show that there is no place immune from such emergency events. Thus, it would be essential to provide disaster relief items efficiently through a disaster relief logistics network system (DRLNS). This paper considers a design problem of DRLNS. For this purpose, this study presents a process of combining the multi-objective programming (MOP) model with the three data envelopment analysis (DEA)-based methods. Through a case study, the proposed MOP-DEA design framework would help the decision-makers better evaluate the efficiency of various DRLNS configurations and identify the robust and efficient ones among them.