DocumentCode :
1798051
Title :
Genetic adaptive A-Star approach for ttrain trip profile optimization problems
Author :
Jin Huang ; Lei Sun ; Fangyu Du ; Hai Wan ; Xibin Zhao
Author_Institution :
Sch. of Software, Tsinghua Univ., Beijing, China
fYear :
2014
fDate :
9-12 Dec. 2014
Firstpage :
129
Lastpage :
134
Abstract :
Genetic adaptive A-Star searching algorithm for optimizing the running profile of a train in a trip under certain constraints is studied. The train trip profile optimization problem is formulated as a multi-constraints nonlinear optimization problem, and the corresponding use of A-Star searching algorithm is introduced. NSGA-II is employed for the adaptive parameters selection of A-Star searching algorithm. A main structure with the cooperation of NSGA-II and A-Star algorithm is proposed. A practical train trip optimization problem is employed for illustrating how the proposed approach works.
Keywords :
genetic algorithms; railways; search problems; NSGA-II; genetic adaptive A-Star searching algorithm; multiconstraints nonlinear optimization problem; train running profile; train trip optimization problem; train trip profile optimization problem; Algorithm design and analysis; Biological cells; Energy consumption; Estimation; Genetics; Optimization; Resistance; A-Star algorithm; Train Trip Profile; genetic adaptive; optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Vehicles and Transportation Systems (CIVTS), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/CIVTS.2014.7009488
Filename :
7009488
Link To Document :
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