Ground Motion Record Selection Using Multi-objective Optimization Algorithms: A Comparative Study.

Kaveh, Ali; Moghanni, Roya Mahdipour; Javadi, Seyed Mohammad

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.

GENETIC algorithms; MATHEMATICAL optimization; PARTICLE swarm optimization; EARTHQUAKE engineering; MOTION; COMPARATIVE studies

Periodica Polytechnica: Civil Engineering, 2019, Vol 63, Issue 3, p812

0553-6626

Academic Journal

10.3311/PPci.14354