Determining the Best Pareto-solution in a Multi-Objective Approach for Model Updating-Reference-Cited by-同舟云学术

Determining the Best Pareto-solution in a Multi-Objective Approach for Model Updating

Published:2019 Issue: Volume: Page:
ISSN:2221-3783
Container-title:IABSE Symposium, Guimarães 2019: Towards a Resilient Built Environment Risk and Asset Management
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Author:

Infantes María¹,Naranjo-Pérez Javier²,Sáez Andrés²^ORCID,Jiménez-Alonso Javier F.³

Affiliation:

1. Department of Mechanics, Universidad de Córdoba, Cordoba, Spain

2. Department of Continuum Mechanics, Universidad de Sevilla, Seville, Spain

3. Department of Building Structures, Universidad de Sevilla, Seville, Spain

Abstract

<p>Using a multi-objective optimization algorithm avoid the use of weighting factors to balance the different residuals in a finite element model updating procedure under the maximum likelihood method. By using this approach, the fittest model is not unique and a set of solutions that form a curve, so-called Pareto optimal front, is obtained. Within this paper, first a review of the state of the art on the criteria used to determine the most adequate model among all the solutions of the Pareto front is presented. Subsequently, a case study of a real footbridge is considered. A finite element model of the footbridge is updated based on its experimental modal parameters. The Non- Dominated Sorting Genetic Algorithm is used to obtain the Pareto front. Since all the solutions in the Pareto front are non-dominated, the selection of the best candidate requires a reasonable criterion. Herein, different procedures to select the best updated model are discussed.</p>

Publisher

International Association for Bridge and Structural Engineering (IABSE)

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