Optimization of structural support locations using a hybrid genetic algorithm

This paper presents a hybrid genetic algorithm (GA) for the optimization of structural support locations. The objective function considered is either the maximum deflection or maximum bending moment of the structure. The objective function is minimized subjected to the design constraints that are imposed as inequality constraints on the design variables. The proposed algorithm integrates the concepts of the GA method and the finite element method. A real-coded method is used to realistically represent the values of the design variables. Three GA operators consisting of the normalized geometric ranking selection procedure, the arithmetic crossover, and the nonuniform mutation are proposed. Finite element method is used to compute the values of implicit objective functions. The results of two numerical examples one by minimizing the maximum deflection and the other by minimizing the maximum bending moment of the structure, indicate that the proposed method is accurate and computationally efficient in optimizing supporting locations.