Structural inverse analysis by hybrid simplex artificial bee colony algorithms
Computers and Structures
Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions
Information Sciences: an International Journal
Structural and Multidisciplinary Optimization
An oriented spanning tree based genetic algorithm for multi-criteria shortest path problems
Applied Soft Computing
Group technology based adaptive cell formation using predator-prey genetic algorithm
Applied Soft Computing
A hybrid stock selection model using genetic algorithms and support vector regression
Applied Soft Computing
Advances in Engineering Software
A fuzzy genetic algorithm for automatic orthogonal graph drawing
Applied Soft Computing
Satisficing solutions of multi-objective fuzzy optimization problems using genetic algorithm
Applied Soft Computing
Damage detection based on improved particle swarm optimization using vibration data
Applied Soft Computing
Finite Elements in Analysis and Design
Interactive genetic algorithms with large population and semi-supervised learning
Applied Soft Computing
Advances in Engineering Software
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The truss optimization constrained with vibration frequencies is a highly nonlinear and more computational cost problem. To speed up the convergence and obtain the global solution of this problem, a hybrid optimality criterion (OC) and genetic algorithm (GA) method for truss optimization is presented in this paper. Firstly, the OC method is developed for multiple frequency constraints. Then, the most efficient variables are identified by sensitivity analysis and modified as iteration scheme. Finally, OC method, serving as a local search operator, is integrated with GA. The numerical results verify that the hybrid method provides powerful ability in searching for more optimal solution and reducing computational effort.