Gene expression programming for symbolic regression - Jandhyala Manognya (2009)
Gene Expression Programming is an evolutionary algorithm that mimics biological evolution to solve a user defined problem. Just like chromosomes are used to represent human beings, each chromosome in the GEP seeks to represent the solution to the problem. GEP uses linear character chromosomes made up of genes, each of which contains a head and a tail. Population of chromosomes are created to best fit a selection environment. With repeated modification or evolution by means of mutation, inversion, transposition and reproduction, the perfect solution to problems can be achieved.