A Study of Metro Organization Based on Multi-objective Programming and Hybrid Genetic Algorithm

  • Jun Zhang School of Highway, Chang’an University, Xi’an, China
  • Jiang Li Jinan Urban Construction Group Co. Ltd, Jinan, China
  • Yan Wu School of Highway, Chang’an University, Xi’an, China

Abstract

Based on the train routing mode ascertained by suitability analysis, we construct a multi-objective problem to optimize the train routing, marshaling number and train headway from the perspective of general cost and segment load ratio by analyzing relevant characteristics like trip time, trip cost, operation cost, spatial distribution characteristics etc. Then the Singular Value Decomposition method and simulation software RailSys have been adopted to calibrate related parameters for the subsequent calculation. By comparison, the Genetic Algorithm is recommended to get an optimal solution to this multi-objective problem, and we improve the traditional algorithm by modifying the coding type, fitness function and crossover operation to enhance the efficiency and convergence. Finally, an operational mode which both satisfies the technological and passenger conditions has been identified to guarantee travellers’ safety, improve operation efficiency, save trip time and decrease cost.

Keywords: urban rail transit, train organization, multi-objective programming, genetic algorithm
Published online
2017-08-23
How to Cite
Zhang, J., Li, J. and Wu, Y. (2017) “A Study of Metro Organization Based on Multi-objective Programming and Hybrid Genetic Algorithm”, Periodica Polytechnica Transportation Engineering, 45(4), pp. 223-229. doi: https://doi.org/10.3311/PPtr.9586.
Section
Articles