Performance assessment of multicriteria damage identification genetic algorithms

Damage detection methods based on model updating method have usually been developed as single objective optimization problems. However, the lack of a clear objective function in the context of real-world damage detection problems advises simultaneous optimizations of several objectives with the purpose of improving the performance of the procedure. The application of genetic algorithms for solving multiobjective optimization constitutes an emergent research area nowadays. However, their application to damage identification problems is very limited and, practically, no comparative study has been presented up to now. In this paper, some multiobjective GAs based on aggregating functions and Pareto optimality are compared.