STUDY ON DISTRIBUTION LAW OF TRUNCATED GENERATIONS IN GENETIC ALGORITHMS

The essence of genetic algorithms characterizes their searching by the mode of directed random, which causes the result to be unstable. In order to investigate the law of the unstability during the evolutionary process in genetic algorithms, two novel concepts of the truncated generation and the distribution of truncated generations are firstly presented, and their definitions are also detailed. Then, on the basis of considerable amounts of numerical tests and statistical analysis for truncated generations, the distribution law is revealed with an example of float type genetic algorithms utilized frequently in engineering optimization. And finally, from the viewpoint of information theoretic entropy, the law is explained using maximum entropy principle.