Ground Motion Record Selection using Multi-objective Optimization Algorithms: A Comparative Study
Roya Mahdipou Moghanni
Seyed Mohammad Javadi
|Published in:||Periodica Polytechnica Civil Engineering|
Performing time history dynamic analysis using site-specific ground motion records according to the increasing interest in the performance-based earthquake engineering has encouraged studies related to site-specific Ground Motion Record (GMR) selection methods. This study addresses a ground motion record selection approach based on three different multi-objective optimization algorithms including Multi-Objective Particle Swarm Optimization (MOPSO), Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Pareto Envelope-based Selection Algorithm II (PESA-II). The method proposed in this paper selects records efficiently by matching dispersion and mean spectrum of the selected record set and target spectrums in a predefined period. Comparison between the results shows that NSGA II performs better than the other algorithms in the case of GMR selection.
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