Two-Stage Multiobjective Optimization of Maintenance Scheduling for Pavements
Publication: Journal of Infrastructure Systems
Volume 23, Issue 3
Abstract
Pavements heavily influence the management costs in highway networks. Operating pavements represents a challenging task involving complex decisions on the application of maintenance actions to keep them at a reasonable level of performance. The major difficulty in applying computational tools to support decision making lies in a large number of pavement sections as a result of a high length of road networks. This paper addresses maintenance scheduling for pavements by consolidating this task into two stages. In each stage, multiobjective optimization is used to optimize maintenance schedules. The main motivation is to obtain a computationally treatable model for large road networks. The first stage is defined by a collection of pavement sections composing the road network. In this stage, the performance and maintenance models are addressed. These models account for uncertainties in the future performance and effects of maintenance by defining model parameters as random variables. The second stage refers to combining maintenance schedules for individual sections to determine the optimal maintenance plan at the network level. The results obtained for the real road network demonstrate the validity and usefulness of the proposed framework. Moreover, this framework is general and can be extended to different types of infrastructure assets.
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Acknowledgments
The authors wish to thank ANI (“Agência Nacional de Inovação”) for the financial support given to the R&D project “SustIMS—Sustainable Infrastructure Management Systems” (FCOMP-01-0202- FEDER-023113), through the Operational Programme for Competitiveness Factors (COMPETE); and FCT (“Fundação para a Ciência e a Tecnologia”) for the Ph.D. scholarship (reference to SFRH/BD/85984/2012).
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©2017 American Society of Civil Engineers.
History
Received: Jan 28, 2016
Accepted: Oct 18, 2016
Published online: Jan 23, 2017
Discussion open until: Jun 23, 2017
Published in print: Sep 1, 2017
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