Research on Urban Rail Transit Route Choice Decision Based on the Improved Imperialist Competition Algorithm

doi:10.16182/j.issn1004731x.joss.17-0267

Abstract

Abstract: This paper proposes a method of passenger route selection based on the imperialist competition improvement algorithm (FAST-ICA) to improve the efficiency of passenger route selection. Six key factors influencing the choice of passenger route are selected. On this basis, the generalized travel cost function is constructed and the passenger route selection model is established. By improving the imperial competition way in the imperialist competition algorithm (ICA), the weakest imperial groups are quickly divided up in each iteration of ICA algorithm to accelerate the convergence rate. Based on the proposed FAST-ICA algorithm, the problem of passenger choice in different environments is solved and carried out in-depth analysis. The experimental results show that the FAST ICA algorithm has good stability and fast convergence speed.

Key words: urban rail transit, key influencing factors selection, path selection model, fast imperialist competition algorithm

CLC Number:

TP391.9

Lian Xiaofeng, Ye Lu, Wang Yan, Jia Limin, Ma Huiru. Research on Urban Rail Transit Route Choice Decision Based on the Improved Imperialist Competition Algorithm[J]. Journal of System Simulation, 2019, 31(8): 1692-1701.

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