Aiming at the disadvantage of traditional parallel multipopulation gene expression programming, namely, the conflict between migration of individuals and diversity of subpopulation, a parallel multipopulation gene expression programming based on component thermodynamical migration strategy (CTDPGEP) was proposed. In this algorithm, an elite subspace of each subpopulation, consisting of some excellent individuals and some random individuals, was selected to migrate to the migration-buffer of any other subpopulation. The other subpopulations received the individuals in its own migration-buffer asynchronously using component thermodynamical replacement method. This mechanism not only ensured the excellent individuals being propagated quickly among the subpopulations, but also maintained the diversity of each subpopulation. Thus, it harmonized the conflict between migration of individuals and diversity of subpopulation quantitatively, accelerated the convergence speed as well as preserved the diversity of population to decrease the probability of trapping into local optimum. Experimental results indicated that the proposed algorithm outperformes some newly relevant algorithms both in solution precision and convergence speed.
