Evolutionary multiobjective optimization in engineering management: an empirical application in infrastructure systems
Liu, Chunlu, Yang, Luyu and Xu, Youquan 2006, Evolutionary multiobjective optimization in engineering management: an empirical application in infrastructure systems, in Engineering Management: An Empirical Application in Infrastructure Systems, IEEE Computer Society, Los Alamitos, CA, pp. 1006-1011.
(Some files may be inaccessible until you login with your Deakin Research Online credentials)
Engineering Management: An Empirical Application in Infrastructure Systems
Chen, Yuehui. Abraham, Ajith
International Conference on Intelligent Systems Design and Applications
IEEE Computer Society
Place of publication
Los Alamitos, CA
Generally multiple objectives exist in transportation infrastructure management, such as minimum cost and maximum service capacity. Although solution methoak of multiobjective optimization problems have undergone continual development over the part several decades, the methods available to date are not particularly robust, and none of them perform well on the broad classes. Because genetic algorithms work with apopulation ofpoints, they can capture a number of solutions simultaneously, and easily incorporate the concept of a Pareto optimal set in their optimization process. In this paper, a genetic algorithm is modified to deal with an empirical application for the rehabilitation planning of bridge decks, at a network level, by minimizing the rehabilitation cost and deterioration degree simultaneously.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Field of Research
120201 Building Construction Management and Project Planning
Unless expressly stated otherwise, the copyright for items in Deakin Research Online is owned by the author, with all rights reserved.
Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO.
If you believe that your rights have been infringed by this repository, please contact firstname.lastname@example.org.