gep
Gene Expression Programming (GEP) is a type of evolutionary computation that evolves computer programs or mathematical expressions. It uses a population of fixed-length, linear chromosomes that encode expression trees via a genotype-phenotype mapping. Each chromosome is composed of one or more genes; each gene encodes a sub-expression using a function set and a terminal set. The phenotype is assembled by linking these sub-expressions into a complete form such as a parse tree or an arithmetic expression, ensuring syntactically correct outputs.
During evolution, standard genetic operators such as mutation and recombination are applied to the linear chromosomes.
Compared with traditional genetic programming, GEP separates genotype from phenotype more clearly and guarantees syntactic validity
Common applications include symbolic regression, data-driven modeling, system identification, time-series forecasting, and rule-based classification. Researchers also
Because the acronym GEP can refer to other terms in different domains, some texts may use gep