Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Civil structure condition assessment by FE model updating: methodology and case studies
Finite Elements in Analysis and Design
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Localising and quantifying damage by means of a multi-chromosome genetic algorithm
Advances in Engineering Software
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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.