Abstract

Municipalities are experiencing high inefficiency and financial burden imposed by their underperforming aging infrastructure. One-third of Canada’s municipal infrastructure is in fair, poor, and failing condition states, increasing the risk of service disruption and leaving decision-makers with no choice but to undertake immediate intervention. Furthermore, the massive number of intervention activities occurring in cities leads to detrimental social, environmental, and economic impacts on the community. Thus, coordinating municipal infrastructure maintenance is progressively becoming of paramount importance to cope with those tough challenges and reduce service disruptions, repair cost, and time. This research presents an asset management solution to ensure proper expenditure utilization while maintaining infrastructure performance. The framework revolves around three core models: (1) a central database that contains detailed asset inventory for the infrastructure systems; (2) multidimensional computational models to assess the performance of the intervention plan through the duration and cost savings as well as the asset condition state; and (3) a trilevel multiobjective goal optimization model that relies on a combination of metaheuristic rules, goal optimization, and genetic algorithms to plan the corridor interventions across the planning horizon. To demonstrate the functionality of the framework, the system was applied to a 9-km stretch of roads, water, and sewer networks from the city of Montreal. The preliminary results of the coordinated intervention scenario displayed an overall improvement of 8%, broken down to 11% improvement in the network condition state, 7% financial savings, and 6% temporal savings, as opposed to the conventional (uncoordinated) intervention scenario. Furthermore, the coordinated intervention scenario proved to be more efficient in more than 70% of the corridors under study, revealing less number of visits to the same corridor and causing less service disruption to the surrounding community, as opposed to the conventional intervention scenario.

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Data Availability Statement

All data generated or analyzed during the study are included in the published article.

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Go to Journal of Infrastructure Systems
Journal of Infrastructure Systems
Volume 26Issue 4December 2020

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Received: Apr 22, 2018
Accepted: Jul 13, 2020
Published online: Sep 19, 2020
Published in print: Dec 1, 2020
Discussion open until: Feb 19, 2021

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Manager, Global Infrastructure Advisory, Klynveld Peat Marwick Goerdeler Canada, Montreal, QC, Canada H3A 3J2 (corresponding author). ORCID: https://orcid.org/0000-0001-6492-6767. Email: [email protected]
Mahmoud Ahmed [email protected]
Ph.D. Candidate and Research Assistant, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., Montreal, QC, Canada H3G 2J1. Email: [email protected]
Associate Professor, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., Montreal, QC, Canada H3G 2J1. ORCID: https://orcid.org/0000-0002-6106-6092. Email: [email protected]

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