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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 103
PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING
Edited by: Y. Tsompanakis
Paper 27

Subway Station Condition Assessment using Analytic Network Processes

I. Gkountis and T. Zayed

Department of Building, Civil and Environmental Engineering,
Concordia University, Montréal, Québec, Canada

Full Bibliographic Reference for this paper
I. Gkountis, T. Zayed, "Subway Station Condition Assessment using Analytic Network Processes", in Y. Tsompanakis, (Editor), "Proceedings of the Third International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 27, 2013. doi:10.4203/ccp.103.27
Keywords: multi-criteria decision making, analytic network process, subway station, condition assessment.

Summary
Transit authorities worldwide operate subway systems which in many cases face extensive deterioration and carry thousands of passengers daily; therefore the task of condition assessment is directly linked with public safety. Currently, transit providers base their condition rating and performance evaluation mostly on empirical solutions. The purpose of this research is to develop an assessment model for the functional condition of subway stations. To achieve this objective, the factors that affect subway stations are divided into appropriate criteria and sub-criteria (structural/architectural, electrical/mechanical, communications and power supply). The criteria weights are evaluated using the analytic network process which is capable of capturing the interdependency among criteria. The station condition index (SCI) is determined through multiplication of criteria weights and criteria evaluation of the stations that originate from the authority's inspection reports. Data were collected from experts through interviews and questionnaires. According to the results, the power supply criterion is the most important with 41.23% weight, followed by communications criteria with 35.28%. From the implementation of the model to Athens subway stations, it is concluded that stations are found to be in medium to good condition with the SCI value ranging from 3.299 to 4.047. A comparative study among other decision making methods is conducted to compare and validate the proposed model. This research is relevant to subway authorities, industry practitioners and researchers.

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