  To improve the global optimization ability of traditional GEP algorithm, a
Multicellular gene expression programming algorithm based on fuzzy control
(Multicellular GEP Algorithm Based On Fuzzy Control, MGEP-FC) is proposed. The
MGEP-FC algorithm describes the size of cross rate, mutation rate and real
number mutation rate by constructing fuzzy membership function. According to
the concentration and dispersion of individual fitness values in population,
the crossover rate, mutation rate and real number set mutation rate of genetic
operation are dynamically adjusted. In order to make the diversity of the
population continue in the iterative process, a new genetic operation scheme is
designed, which combines the new individuals with the parent population to
build a temporary population, and the diversity of the temporary and
subpopulation are optimized. The results of 12 Benchmark optimization
experiments show that the MGEP-FC algorithm has been greatly improved in
stability, global convergence and optimization speed.
