Robust Design Optimization with Mixed-discrete Variables Based on Ant Algorithm and Support Vector Machine

摘要

The basic ant optimization algorithm is improved by introducing ant colony scatterance and discrete search. In order to solve the optimization problem with mixed-discrete variables, a program of ant algorithm is designed by using MA TLAB. Based on the introduce of support vector regression (SVR) which is used to compute the values of nonlinear functions such as fuzzy probability,the computational efficiency of robust design optimization is distinctly improved.An example of robust design optimization with mixed-discrete variables is presented, and it shows that the proposed method is effective in engineering application.