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Evolutionary Multiobjective Optimization in Engineering Management: An Empirical Study on Bridge Deck Rehabilitation

机译:工程管理中的进化多目标优化:桥面修复的实证研究

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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.
机译:工程管理中有多个目标,例如最小成本和最大服务能力。尽管在过去的几十年中,多目标优化问题的解决方法得到了不断发展,但是迄今为止可用的方法并不是特别可靠,并且在广泛的类别中都没有一个很好的表现。由于遗传算法可以处理大量点,因此它们可以同时捕获多个解决方案,并且可以轻松地将Pareto最优集的概念纳入其优化过程。本文对遗传算法进行了改进,通过同时最小化修复成本和恶化程度,在网络水平上处理桥面板的修复计划。

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