id |
ascaad2014_013 |
authors |
Binhomaid, Omar and Tarek Hegazy |
year |
2014 |
title |
Comparison between Genetic Optimization and Heuristic Methods for Prioritizing Infrastructure Rehabilitation Programs |
source |
Digital Crafting [7th International Conference Proceedings of the Arab Society for Computer Aided Architectural Design (ASCAAD 2014 / ISBN 978-603-90142-5-6], Jeddah (Kingdom of Saudi Arabia), 31 March - 3 April 2014, pp. 175-182 |
summary |
In recent years, infrastructure rehabilitation has been in the focus of attention in North America and around the world. A large percentage of existing infrastructure assets is deteriorating due to harsh environmental conditions, insufficient capacity, and age. Due to stringent budget limits, however, asset management systems become important to assess the life cycle performance of various assets, and accordingly prioritize the assets for rehabilitation purposes. While many asset management systems have been introduced in the literature, almost no studies have compared the effectiveness of their asset prioritization methods. This paper presents an extensive comparison between heuristic and optimization methods for prioritizing large-scale rehabilitation programs, under budget constraints. The paper first introduces different life cycle cost analysis (LCCA) formulations for three case studies obtained from the literature related to buildings, pavements, and bridges. Based on extensive experiments with the three case studies and on different network sizes, heuristic techniques proved its practicality for handling various network sizes. The performance of genetic optimization, on the other hand, was more efficient on small-scale networks but showed steep degradation in performance with large-scale problems. This research can be beneficial to municipalities and asset managers and can help them design efficient methods to sustain the safety and operability of the civil infrastructure, with least cost. |
series |
ASCAAD |
email |
omar-s-h@hotmail.com |
full text |
file.pdf (240,409 bytes) |
references |
Content-type: text/plain
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last changed |
2016/02/15 13:09 |
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