Application of the Improved Immune Algorithm to a Structural Design Support System

Abstract

The Genetic Algorithms(GAs) based on multi-point search method and crossover operation are one of the useful search procedures for combinatorial optimization problems and also applied to many kinds of practical optimization. However, in general, the GAs have a tendency to go down rapidly of the diversity of population in the process of searching. In order to improve this drawback, some researchers have proposed new algorithms for maintaining the diversity of population. On the other hand, the Immune Algorithms(IAs) are optimization techniques which imitate the immune systems in an organism. The IAs are able to obtain plural semi-optimum solution with maintaining the diversity of population compared with the GAs. In this study, in order to consider the application to optimal design problems in structures, the improvement of convergent and the maintenance of the diversity of population are attempted. Furthermore, improved IA is applied to the impact resistance design problem. It is found that application of improved IA can be used as effective method of structural optimization design base on several simulation results.