Abstract:
Abstract:Genetic Programming (GP) is one of the evolutionary computation (EC) methods followed withgreat interest by many researchers. When GP first appeared, it has become a popularcomputational intelligence method because of its successful applications and its potentials tofind effective solutions for difficult practical problems of many different disciplines. With theuse of GP in a wide variety of areas, numerous variants of GP methods have emerged to providemore effective solutions for computation problems of diverse application fields. Therefore, GPhas a very rich literature that is progressively growing. Many GP software tools developedalong with process of GP algorithms. There is a need for an inclusive survey of GP literaturefrom the beginning to today of GP in order to reveal the role of GP in the computationalintelligence field. This survey study aims to provide an overview of the growing GP literaturein a systematic way. The researchers, who need to implement GP methods, can gain insight ofpotentials in GP methods, their essential drawbacks and prevalent superiorities. Accordingly,taxonomy of GP methods is given by a systematic review of popular GP methods. In thismanner, GP methods are analyzed according to two main categories, which consider thediscrepancies in their program (chromosome) representation styles and their methodologies.Besides, GP applications in diverse problems are summarized. This literature survey isespecially useful for new researchers to gain the required broad perspective beforeimplementing a GP method in their problems.
