Optimization of Rail Transit Departure Frequency Based on Fuzzy Clustering - Take Shanghai Rail Transit Line 9 for Example

Author

Zhong, Wu ; Hanwei, Li

Author_Institution

Coll. of Manage., Shanghai Univ. of Eng. & Sci., Shanghai, China

fYear

2012

fDate

12-14 Oct. 2012

Firstpage

875

Lastpage

877

Abstract

This article takes example of Shanghai Rail Transit Line 9, and uses fuzzy clustering method to classify passenger flow in different periods of the working and non-working days by MATLAB program. Full-day time intervals are divided into five categories, and we optimize the departure frequency based on the five categories. This optimization method improves the operational efficiency of urban railway transport, and reduces the cost of it. The method of research is innovative, and research findings are instructive in practice.

Keywords

fuzzy set theory; pattern clustering; rail traffic; MATLAB program; Shanghai rail transit line 9; cost reduction; fuzzy clustering method; nonworking days; operational efficiency improvement; passenger flow classification; rail transit departure frequency optimization; time intervals; urban railway transport; working days; Cities and towns; Educational institutions; MATLAB; Optimization; Rail transportation; Rails; Time frequency analysis; departure frequency; fuzzy clustering; passenger flow; time intervals;

fLanguage

English

Publisher

ieee

Conference_Titel

Business Computing and Global Informatization (BCGIN), 2012 Second International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4673-4469-2

Type

conf

DOI

10.1109/BCGIN.2012.233

Filename

6382674