Hybrid Orthogonal Genetic Algorithm and Its Application in Function Optimization

Article Abstract: According to the hybrid optimization strategy and the rules of hybrid genetic algorithms,it creates a new mutating operator — orthogonal mutation operator on the basis of the operator of adaptive orthogonal local search.This kind of operator can provide with adaptive global search and local search at the same time.It can keep the most effective searching when the probability of mutation means 1.0,combining using the orthogonal crossover operator;it can keep the most effective searching when the probability of crossover means 1.0.And then,it solves the problem of the optimizing to the group of uncertain probabilities of crossover and mutation in genetic algorithm.Moreover,the paper has designed some groups of new operators such as truncation selection and negative-correlation partnership,best-fit-crossover strategy,the best individual holding strategy and repeated individual elimination,etc.On the one hand,these hybrid operators can keep the speed of searching,on the other hand,they can provide global search（reliability） by means of the promotion of high levels of population diversity.And then,it solves the problem of the contradiction between the ＂high speed constringency＂ and ＂the most global-optimized＂.As a result,the method is effective in the dealing with some common function.