A new model for a 72-h post-earthquake emergency logistics location-routing problem under a random fuzzy environment. Issue 5 (19th October 2016)

• Record Type: Journal Article
• Authors: Xu, Jiuping; Wang, Ziqi; Zhang, Mengxiang; Tu, Yan
• Is Part Of: Transportation letters. Volume 8:Issue 5(2016)
• Page Start: 270
• Page End: 285
• Publication Date: 2016-10-19
• Subjects: Location-routing problem -- 72-h post-earthquake -- Random fuzzy variables -- Bi-level programming model -- RFS-IGA; Transportation -- Research -- Periodicals; Transportation -- Periodicals; Urban transportation -- Periodicals; 388.072
• DOI: 10.1080/19427867.2015.1126064
• Languages: English
• ISSNs: 1942-7867

Abstract

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.