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

  • Ali Kaveh Iran University of Science and Technology
  • Roya Mahdipou Moghanni Iran University of Science and Technology
  • Seyed Mohammad Javadi Iran University of Science and Technology

Abstract

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.

Keywords: ground motion record selection, multi-objective particle swarm optimization, non-dominated sorting genetic algorithm II, pareto envelope-based selection algorithm II
Published online
2019-08-08
How to Cite
Kaveh, A., Mahdipou Moghanni, R., & Javadi, S. M. (2019). Ground Motion Record Selection Using Multi-objective Optimization Algorithms: A Comparative Study. Periodica Polytechnica Civil Engineering, 63(3), 812-822. https://doi.org/10.3311/PPci.14354
Section
Research Article