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Issue title: Applied Mathematics Related to Nonlinear Problems
Guest editors: Juan L.G. Guirao and Wei Gao
Article type: Research Article
Authors: Tang, Zhaopinga; b | Qin, Jina; * | Sun, Jianpingb
Affiliations: [a] School of Traffic and Transportation Engineering, Central South University, Changsha Hunan, China | [b] School of Transportation and Logistics, East China Jiaotong University, Nanchang Jiangxi, China
Correspondence: [*] Corresponding author. Jin Qin, School of Traffic and Transportation Engineering, Central South University, Changsha Hunan, China. E-mail: qinjin@csu.edu.cn.
Abstract: Considering the uncertainty existing in the railway emergency rescues such as the demand uncertainty of resources, the uncertainty of emergency start time, as well as the uncertainty of urgency degree to rescue and emergency, it was studied that the railway emergency resources dispatching optimization problems with multi-demand point, multi-depot and multi-resource in the paper. The uncertainties in problems were dealt with by fuzzy theory method. A multi-objective programming model is established by maximizing the time satisfaction degree of resources dispatching and minimizing the total cost. In view that the initial emergency rescue resources may be inadequate, by use of GC-TOPSIS with objective entropy weight, the emergency rescue priority queue were sorted. Combined with the ideal point method, the restricted parameter interval search method for optimal solution was proposed, which can quickly seek the Pareto optimal solution. It provides the effective solving method for large-scale railway rescue resource dispatching under uncertainty conditions.
Keywords: Emergency resource dispatching, uncertainty, GC-TOPSIS model, fuzzy theory, the restricted parameter interval method
DOI: 10.3233/JIFS-169317
Journal: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2677-2686, 2017
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