Multi-Criteria Decision Making Models for Water Pipelines
Publication: Journal of Performance of Constructed Facilities
Volume 30, Issue 4
Abstract
The deterioration of water pipelines leads to impaired water quality, increased breakage rate, and reduced hydraulic capacity. The planning of maintenance programs for water pipelines is essential to minimize health and safety concerns and ensure an adequate supply of water in a safe, cost-effective, reliable, and sustainable manner. It is essential to assess the performance of water pipelines to assist municipalities in planning inspection and rehabilitation programs for their pipelines. Several models have been developed to assess the condition or performance of water pipelines based on several affecting factors. However, none of them considered the interdependency relationships between the factors. Moreover, some models did not account for the factors’ weights uncertainty. This paper presents the development of performance assessment models for water pipelines. The models consider three groups of factors affecting water pipeline performance, namely, physical, environmental, and operational. The models were developed using data collected from questionnaire surveys distributed among water pipeline experts in Qatar. The factors’ weights were calculated using four different methods, namely, analytic hierarchy process (AHP), fuzzy AHP (FAHP), analytic network process (ANP), and fuzzy ANP (FANP). The results showed that the FANP is the most accurate method since it incorporates the interdependency and uncertainty into the decision making process.
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Acknowledgments
The authors gratefully acknowledge the support provided by Qatar National Research Fund (QNRF) for this research project under Award No. QNRF-NPRP 4–529–2–193.
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Published In
Journal of Performance of Constructed Facilities
Volume 30 • Issue 4 • August 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Oct 16, 2014
Accepted: Sep 28, 2015
Published online: Nov 18, 2015
Discussion open until: Apr 18, 2016
Published in print: Aug 1, 2016
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