Article,
Comparison Between Genetic Algorithm and Genetic Programming Approach for Modeling the Stress Distribution
Materials and Manufacturing Processes, 20 (3): 497--508 (2005)
DOI: doi:10.1081/AMP-200053541
Abstract
We compare genetic algorithm (GA) and genetic
programming (GP) for system modelling in metal forming.
As an example, the radial stress distribution in a
cold-formed specimen (steel X6Cr13) was predicted by GA
and GP. First, cylindrical workpieces were forward
extruded and analysed by the visioplasticity method.
After each extrusion, the values of independent
variables (radial position of measured stress node,
axial position of measured stress node, and coefficient
of friction) were collected. These variables influence
the value of the dependent variable, radial stress. On
the basis of training data, different prediction models
for radial stress distribution were developed
independently by GA and GP. The obtained models were
tested with the testing data. The research has shown
that both approaches are suitable for system modeling.
However, if the relations between input and output
variables are complex, the models developed by the GP
approach are much more accurate.
