Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Short Communication: Fuzzy multiobjective optimization of truss-structures using genetic algorithm
Advances in Engineering Software
A hybrid genetic algorithm for reinforced concrete flat slab buildings
Computers and Structures
Advances in Engineering Software
A hybrid Fox and Kirsch's reduced basis method for structural static reanalysis
Structural and Multidisciplinary Optimization
Advances in Engineering Software
A hybrid OC-GA approach for fast and global truss optimization with frequency constraints
Applied Soft Computing
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Structural optimization with frequency constraints is highly nonlinear dynamic optimization problems. Genetic algorithm (GA) has greater advantage in global optimization for nonlinear problem than optimality criteria and mathematical programming methods, but it needs more computational time and numerous eigenvalue reanalysis. To speed up the design process, an adaptive eigenvalue reanalysis method for GA-based structural optimization is presented. This reanalysis technique is derived primarily on the Kirsch's combined approximations method, which is also highly accurate for case of repeated eigenvalues problem. The required number of basis vectors at every generation is adaptively determined and the rules for selecting initial number of basis vectors are given. Numerical examples of truss design are presented to validate the reanalysis-based frequency optimization. The results demonstrate that the adaptive eigenvalue reanalysis affects very slightly the accuracy of the optimal solutions and significantly reduces the computational time involved in the design process of large-scale structures.