Modified genetic algorithm strategy for structural identification

Authors:
M. J. Perry;C. G. Koh;Y. S. Choo
Affiliations:
Department of Civil Engineering, National University of Singapore, Block E1A, 1 Engineering Drive 2, Singapore 117576, Singapore;Department of Civil Engineering, National University of Singapore, Block E1A, 1 Engineering Drive 2, Singapore 117576, Singapore;Department of Civil Engineering, National University of Singapore, Block E1A, 1 Engineering Drive 2, Singapore 117576, Singapore
Venue:
Computers and Structures
Year:
2006

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Abstract

Genetic algorithms (GA) have proved to be a robust, efficient search technique for many problems. As the number of variables involved increases, classical GA will often have difficulty and/or require long computational time in obtaining acceptable results. In this paper, a modified GA strategy is proposed to improve the accuracy and computational time for parameter identification of multiple degree-of-freedom (DOF) structural systems. The strategy includes multiple populations or 'species', a search space reduction procedure and new operators designed to provide a robust and reliable identification. Average absolute error in the estimated stiffness values of 1.4% is achieved for a 20-DOF unknown mass system with 5% noise, and even more importantly the maximum error is reduced to only 3.8%.