EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS Earthquake Engng Struct. Dyn. 2005; 34:665–685 Published online 14 January 2005 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/eqe.449 Multi-objective framework for structural model identication Yiannis Haralampidis, Costas Papadimitriou ∗; † and Maria Pavlidou Department of Mechanical and Industrial Engineering; University of Thessaly; Pedion Areos; 38334 Volos; Greece SUMMARY Structural identication based on measured dynamic data is formulated in a multi-objective context that allows the simultaneous minimization of the various objectives related to the t between measured and model predicted data. Thus, the need for using arbitrary weighting factors for weighting the relative importance of each objective is eliminated. For conicting objectives there is no longer one solution but rather a whole set of acceptable compromise solutions, known as Pareto solutions, which are optimal in the sense that they cannot be improved in any objective without causing degradation in at least one other objective. The strength Pareto evolutionary algorithm is used to estimate the set of Pareto optimal structural models and the corresponding Pareto front. The multi-objective structural identica- tion framework is presented for linear models and measured data consisting of modal frequencies and modeshapes. The applicability of the framework to non-linear model identication is also addressed. The framework is illustrated by identifying the Pareto optimal models for a scaled laboratory building structure using experimentally obtained modal data. A large variability in the Pareto optimal struc- tural models is observed. It is demonstrated that the structural reliability predictions computed from the identied Pareto optimal models may vary considerably. The proposed methodology can be used to explore the variability in such predictions and provide updated structural safety assessments, taking into consideration all Pareto structural models that are consistent with the measured data. Copyright ? 2005 John Wiley & Sons, Ltd. KEY WORDS: structural identication; multi-objective optimization; Pareto set; reliability 1. INTRODUCTION The problem of identifying the parameters of a structural model using dynamic data has received much attention over the years because of its importance in structural model updat- ing, structural health monitoring and structural control. Comprehensive reviews of structural ∗ Correspondence to: Costas Papadimitriou, Department of Mechanical and Industrial Engineering, University of Thessaly, Pedion Areos, 38334 Volos, Greece. † E-mail: costasp@uth.gr Contract=grant sponsor: Greek Secretariat of Research and Technology Contract=grant sponsor: Greek Earthquake Planning and Protection Organization (OASP) Received 9 July 2003 Revised 12 March 2004 Copyright ? 2005 John Wiley & Sons, Ltd. Accepted 15 October 2004