RESEARCH ARTICLE
Integration of Probabilistic Effectiveness with a Two-stage Genetic Algorithm Methodology to Develop Optimum Maintenance Strategies for Bridges
Elia A. Tantele*, Renos A. Votsis, Toula Onoufriou
Article Information
Identifiers and Pagination:
Year: 2015Volume: 9
First Page: 266
Last Page: 276
Publisher ID: TOBCTJ-9-266
DOI: 10.2174/1874836801509010266
Article History:
Received Date: 17/4/2015Revision Received Date: 14/7/2015
Acceptance Date: 16/7/2015
Electronic publication date: 27/10/2015
Collection year: 2015
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Preventative Maintenance (PM) measures can be used to postpone/delay the initiation of corrosion from chloride attack in reinforced concrete bridges. However there are a lot of uncertainties that influence their degree of effectiveness. Also the time-application of these measures can raise a conflict between safety requirements and budgets. This paper presents a stochastic approach for estimating the effectiveness of different PM measures. Additionally a two-stage optimisation methodology using the principles of Genetic Algorithms (GA) is developed to address the problem of the timeapplication by linking the effectiveness with the cost to produce optimum PM strategies. Futhermore, the role of the presented time-dependent probabilistic approach in the proposed two-stage GA methodology for obtaining optimum PM strategies is demonstrated.