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