GeneAS: A Robust Optimal Design Technique for Mechanical Component Design

A robust optimal design algorithm for solving nonlinear engineering design optimization problems is presented. The algorithm works according to the principles of genetic algorithms (GAs). Since most engineering problems involve mixed variables (zero-one, discrete, continuous), a combination of binary GAs and real-coded GAs is used to allow a natural way of handling these mixed variables. The combined approach is called GeneAS to abbreviate Genetic Adaptive Search. The robustness and flexibility of the algorithm come from its restricted search to the permissible values of the variables. This also makes the search efficient by requiring a reduced search effort in converging to the optimum solution. The efficiency and ease of application of the proposed method are demonstrated by solving four mechanical component design problems borrowed from the optimization literature. The proposed technique is compared with traditional optimization methods. In all cases, the solutions obtained using GeneAS are better than those obtained with the traditional methods. These results show how GeneAS can be effectively used in other mechanical component design problems.