A new model for a 72-h post-earthquake emergency logistics location-routing problem under a random fuzzy environment

Abstract

The 72-h post-earthquake location-routing problem is key to post-earthquake emergency logistics. In the 72-h post-earthquake period, lack of information about the road conditions increases relief effort uncertainty. A bi-level model under a random fuzzy environment is presented in this paper to solve this problem. The Rescue Control Center is the upper level decision-maker and is responsible for distribution center location selection from the available candidates, and the logistics company is the lower level decision-maker, who needs to select the optimal routes so as achieve the shortest possible transportation time. Random fuzzy variables are used to handle the uncertainties and a random fuzzy simulation-based interactive genetic algorithm is designed to search for optimal solutions to the bi-level model. Finally, a case study on the emergency logistics for the Lushan earthquake demonstrates the practicality and efficiency of the model, and some strategies are proposed to further improve relief work.