Parametric Analysis of Genetic Algorithm Toolbox for Truss Problem Optimization

Abstract

Genetic algorithms (GA) are powerful and efficient methods of evolutionary optimization algorithms which conduct search and optimization based on the Darwinian principles of natural genetics and natural selection. They have been extensively used in the recent past for optimization problems of the truss structures. However, for obtaining the best and robust solutions, it is necessary to choose proper GA operators depending upon the type and complexity of the problem. In this research study, genetic algorithm toolbox of MATLAB is used for the optimizing truss structures. The stress and deflections in various members of the truss are obtained using commercially available FEA software ANSYS. An interface has been established between MATLAB and ANSYS for parametric modelling of the problem. The GA operators tested are selection functions, crossover functions and mutation functions. We made use of five selections functions, six crossover functions and three mutation functions to find best set of combination which can be used further for optimization of truss structure.