Abstract:

In order to reduce the rate of premature convergence and to escape from local optimum, GEP(Gene Expression Programming) based on diversified development strategy is proposed,  which assigns the population with different development strategies to enhance the optimizing ability of GEP through GSBS（Gene Space Balance Strategy), ACMO（Adaptive Crossover and Mutation Operators) and obsolete operator (OBSO). Experiments on function mining show that all of strategies play roles of mining. Compared with the result of GEP. The number of average evolution generations is decreased by 11%, evolution time is decreased by 8%, and the success rate is increased by 20%.

Key words: gene expression programming (GEP), diversity, genetic operator, function mining