Optimizing rehabilitation plan of bridge decks using multiobjective genetic algorithm

Most of the optimization problems in the infrastructure management have multiple objectives which are heterogeneous due to the changes of essential factors. However, in the previous research, attention was mainly paid to cost optimization by minimizing or maximizing a given objective function. Multiobjective optimization (MO) extends optimization theory by permitting multiple objectives to be optimized simultaneously. Although the solution methods of MO problems have undergone continual development over the past three decades, methods available to date are not particularly robust, and none of them performs well on the broad classes of MO problems. Because Genetic Algorithms (GAs) 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. The rehabilitation plan of bridge decks represents a resource intensive activity, and has been paid special attention. In this paper, a simple Genetic Algorithm with two additional techniques are used to deal with the rehabilitation plan of bridge decks by minimizing the rehabilitation cost and deterioration degree simultaneously.