Application of genetic programming for modelling of material characteristics

Genetic programming, which is one of the most general evolutionary computation methods, was used in this paper for the modelling of tensile strength and electrical conductivity in cold formed material. No assumptions about the form and size of expressions were made in advance, but they were left to the self organization and intelligence of evolutionary process. Genetic programming does this by genetically breeding a population of computer programs using the principles of Darwinian’s natural selection and biologically inspired operations. In our research, copper alloy was cold formed by drawing using different process parameters and then tensile strengths and electrical conductivity (dependent variables) of the specimens were determined. The values of independent variables (effective strain, coefficient of friction) influence the value of the dependent variables. Many different genetic models for both dependent variables were developed by genetic programming. The accuracies of the best models were proved by a testing data set. Also, comparison between the genetic and regression models is presented in the paper. The research showed that very accurate genetic models can be obtained by the proposed method.

► Genetic programming harnesses the power of natural selection to turn computers into optimization tools.
► Many different genetic models for material characteristics were developed by genetic programming.
► Genetic models show much greater accuracy then regression models.