An improved gene expression programming algorithm based on hybrid strategy

Gene expression programming (GEP) is a new evolutionary algorithm, which has the very good applications in the field of function finding. In view of the insufficiency of traditional GEP, this paper puts forward an improved gene expression programming algorithm based on hybrid strategy (HSI-GEP). This paper has two improvements: (1) using mirror and reset mechanism to replace the inferior individuals of population, to improve the quality and the diversity of population; (2) introducing the clonal selection before tournament selection in order to improve the mining ability of algorithm about the superior individuals. The experiments compared with the improved GEP from authoritative literatures about function finding problems have been carried on, and the results show that HSI-GEP is of high quality, has fast convergence rate and obvious competitiveness.