Efficiently Implementing Genetic Optimization with Nonlinear Response History Analysis of Taller Buildings
Publication: Journal of Structural Engineering
Volume 140, Issue 8
Abstract
Nonlinear response history analysis is an important tool for accurately determining the performance of tall buildings under severe earthquake loading. When a standard genetic algorithm is used in conjunction with nonlinear response history analysis, it is desirable to use smaller generation sizes because of the computational effort to analyze individual designs. A study was conducted to evaluate how different genetic algorithm techniques influence the reliability and efficiency of the algorithm when used with nonlinear response history analysis and small generation sizes. The system used in the study was a nine-story buckling restrained braced frame that was optimized to minimize brace areas under individual earthquake records. A baseline study showed that a typical genetic algorithm did not converge to the same best design for different random number sequences (seed numbers). Forced diversity improved the reliability of the algorithm such that it converged to the same optimum, regardless of initial seed number. Adaptive mutation decreased the required number of generations when coupled with a noncrossover constraint. Consecutive identical generations were found to predict convergence and provide a basis for an exit criterion.
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Acknowledgments
This work was possible due to support from Brigham Young University. Graham Oxborrow programmed the genetic algorithm into OpenSees as part of another project.
References
AISC. (2010). Seismic provisions for structural steel buildings, American Institute of Steel Construction, Chicago.
Alimoradi, A., Pezeshk, S., and Foley, C. M. (2007). “Probabilistic performance-based optimal design of steel moment-resisting frames. II: Applications.” J. Struct. Eng., 767–776.
Apostolakis, G., and Dargush, G. F. (2010). “Optimal seismic design of moment-resisting steel frames with hysteretic passive devices.” Earthquake Eng. Struct. Dyn., 39(4), 355–376.
ASCE. (2010). Minimum design loads for buildings and other structures, ASCE, Reston, VA.
Balling, R. J. (2006). Computer analysis and optimization of structures, BYU Academic Publishing, Provo, UT.
Balling, R. J., Balling, L. J., and Richards, P. W. (2009). “Design of buckling-restrained braced frames using nonlinear time history analysis and optimization.” J. Struct. Eng., 461–468.
Balling, R. J., Pister, K. S., and Ciampi, V. (1983). “Optimal seismic-resistant design of a planar steel frame.” Earthquake Eng. Struct. Dyn., 11(4), 541–556.
Deb, K. (2001). Multi-objective optimization using evolutionary algorithms, Wiley, New York.
Farhat, F., Nakamura, S., and Takahashi, K. (2009). “Application of genetic algorithm to optimization of buckling restrained braces for seismic upgrading of existing structures.” Comput. Struct., 87(1–2), 110–119.
Foley, C., Pezeshk, S., and Alimoradi, A. (2007). “Probabilistic performance-based optimal design of steel moment-resisting frames. I: Formulation.” J. Struct. Eng., 757–766.
Foley, C. M., and Schinler, D. (2003). “Automated design of steel frames using advanced analysis and object-oriented evolutionary computation.” J. Struct. Eng., 648.
Kaveh, A., Laknejadi, K., and Alinejad, B. (2012). “Performance-based multi-objective optimization of large steel structures.” Acta Mech., 223(2), 355–369.
Lagaros, N. D., Fragiadakis, M., Papadrakakis, M., and Tsompanakis, Y. (2006). “Structural optimization: A tool for evaluating seismic design procedures.” Eng. Struct., 28(12), 1623–1633.
Liu, M., Burns, S. A., and Wen, Y. K. (2003). “Optimal seismic design of steel frame buildings based on life cycle cost considerations.” Earthquake Eng. Struct. Dyn., 32(9), 1313–1332.
Liu, M., Burns, S. A., and Wen, Y. K. (2005). “Multiobjective optimization for performance-based seismic design of steel moment frame structures.” Earthquake Eng. Struct. Dyn., 34(3), 289–306.
Mauldin, M. L. (1984). “Maintaining diversity in genetic search.” Proc., National Conf. on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, Palo Alto, CA, 247–250.
OpenSees [Computer software]. Pacific Earthquake Engineering Research Center (PEER), Berkeley, CA.
Ozbulut, O. E., Roschke, P. N., Lin, P. Y., and Loh, C. H. (2010). “GA-based optimum design of a shape memory alloy device for seismic response mitigation.” Smart Mater. Struct., 19(6), 065004.
Pezeshk, S., Camp, C., and Chen, D. (2000). “Design of nonlinear framed structures using genetic optimization.” J. Struct. Eng., 382–388.
Tan, P., Dyke, S. J., Richardson, A., and Abdullah, M. (2005). “Integrated device placement and control design in civil structures using genetic algorithms.” J. Struct. Eng., 1489–1496.
Rojas, H. A., Pezeshk, S., and Foley, C. M. (2007). “Performance-based optimization considering both structural and nonstructural components.” Earthquake Spectra, 23(3), 685–709.
Wongprasert, N., and Symans, M. D. (2004). “Application of a genetic algorithm for optimal damper distribution within the nonlinear seismic benchmark building.” J. Eng. Mech., 401–406.
Zou, X. K., and Chan, C. M. (2005). “Optimal seismic performance-based design of reinforced concrete buildings using nonlinear pushover analysis.” Eng. Struct., 27(8), 1289–1302.
Zou, X. K., Chan, C. M., Li, G., and Wang, Q. (2007). “Multiobjective optimization for performance-based design of reinforced concrete frames.” J. Struct. Eng., 1462–1474.
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© 2014 American Society of Civil Engineers.
History
Received: Dec 21, 2012
Accepted: Sep 9, 2013
Published online: Mar 17, 2014
Published in print: Aug 1, 2014
Discussion open until: Aug 17, 2014
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