City Research Online

Multi-objective optimum selection of ground motion records with genetic algorithms

Mergos, P.E. ORCID: 0000-0003-3817-9520 & Sextos, A. (2018). Multi-objective optimum selection of ground motion records with genetic algorithms. Paper presented at the 16th European Conference on Earthquake Engineering- 16ECEE, 18 - 21 June 2018, Thessaloniki, Greece.

Abstract

Existing ground motion selection methods for the seismic assessment of structural systems consider only spectral compatibility as selection objective. Other important earthquake parameters such as those related to regional seismicity, local soil conditions, strong ground motion intensity and duration are considered indirectly by setting them as selection constraints. This study presents a new framework for the optimum selection of earthquake ground motions, where more than one objectives are considered explicitly in the selection procedure including objectives that are not directly related to spectral matching. To address the multi-objective nature of the optimization problem examined herein, the weighted sum method is used that supports decision making both in the pre-processing and post-processing phase of the selection procedure. The optimum selections are conducted by the use of a mixed-integer genetic algorithm that is able to track near-global optimal solutions of constrained problems with both discrete and continuous design variables. It is found that proposed methodology is able to select ground motion sets that are both spectrum compatible and representative of the seismic conditions of the structural system under investigation.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: ©the authors, 2018.
Publisher Keywords: Selection; Ground motions; Optimum; Multi-objective; Genetic algorithms
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Departments: School of Science & Technology > Engineering
[thumbnail of Mergos_Sextos_16ecee_final.pdf]
Preview
Text - Accepted Version
Download (632kB) | Preview

Export

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Downloads

Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login