Adaptive Multi-phenotype Based Gene Expression Programming Algorithm

Expression theory is the mathematical foundation of evolutionary computation. In order to investigate the problems in Gene expression programming (GEP) expression theory, we clarified the difference between genotypic expression space and phenotypic expression space. We also presented phenotypic expression space definition and theory. Then we analyzed the reason of good and bad performance of different GEP algorithms based on expression space theory. We also proposed a new Adaptive multi-phenotype gene expression programming (AMGEP), in which the potential of genes is fully activated with gene combination. Experiments on benchmark problems showed that genotypic expression space and phenotypic expression space theory can explain the different performance of different algorithms and showed that AMGEP outperform other GEP algorithms in terms of search ability.