Title: Route optimisation models and algorithms for hazardous materials transportation under different environments
Authors: Changxi Ma; Yinzhen Li; Ruichun He; Fang Wu; Bo Qi; Qing Ye
Addresses: School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou Anning Road 88, Gansu, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou Anning Road 88, Gansu, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou Anning Road 88, Gansu, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou Anning Road 88, Gansu, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou Anning Road 88, Gansu, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou Anning Road 88, Gansu, 730070, China
Abstract: This study focuses on how to determine the optimum transportation route for hazardous materials under the certain, fuzzy or stochastic environment. On the basis of analysing the transportation route selection problem of hazardous materials (TRSP-HM), three objectives are presented and the multi-objective routing programming model (MRPM) for hazardous materials transportation (HMT) is put forward under the certain environment, and an improved label algorithm is proposed to solve the MRPM. After defining the maximum-chance optimum route and the α-optimum routes, the multi-objective routing chance-constrained programming model (MRCPM) and multi-objective routing dependent-chance programming model (MRDPM) for HMT under the fuzzy or stochastic environment are established respectively. Then, the integration intelligent algorithm is developed to solve the proposed models, which integrates the fuzzy simulation, neural networks, stochastic simulation and genetic algorithm. Finally, the proposed models and algorithms are successfully tested with the help of two real cases.
Keywords: transport engineering; chance-constrained programming models; dependent-chance programming models; route optimisation; modelling; hazardous materials transport; fuzzy simulation; neural networks; stochastic simulation; genetic algorithms; fuzzy logic.
DOI: 10.1504/IJBIC.2013.055473
International Journal of Bio-Inspired Computation, 2013 Vol.5 No.4, pp.252 - 265
Received: 03 Mar 2013
Accepted: 04 Mar 2013
Published online: 31 Mar 2014 *