Evolutionary multiobjective optimization in engineering management: an empirical study on bridge deck rehabilitation
Liu, Chunlu 2005, Evolutionary multiobjective optimization in engineering management: an empirical study on bridge deck rehabilitation, in PDCAT 2005 : Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005 proceedings, IEEE Computer Society, Los Alamitos, CA, pp. 773-777.
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PDCAT 2005 : Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005 proceedings
Shen, Hong. Nakano, Koji.
Parallel and Distributed Computing Applications and Technologies Conference
IEEE Computer Society
Place of publication
Los Alamitos, CA
There exist multiple objectives in engineering management such as minimum cost and maximum service capacity. Although solution methods of multiobjective optimization problems have undergone continual development over the past several decades, the methods available to date are not particularly robust, and none of them performs well on the broad classes. Because genetic algorithms work with a population of points, they can capture a number of solutions simultaneously, and easily incorporate the concept of Pareto optimal set in their optimization process. In this paper, a genetic algorithm is modified to deal with the rehabilitation planning of bridge decks at a network level by minimizing the rehabilitation cost and deterioration degree simultaneously.
Field of Research
120201 Building Construction Management and Project Planning
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