Abstract
Cartesian Genetic Programming (CGP) is a graph-based genetic programming technique developed by Miller & Thompson in 2000 which has several advantages over the traditional form of tree-based Genetic programming (GP). In the standard form, CGP uses only mutation as a genetic operator whereas the use of traditional crossover operators of GP when applied to CGP led to disrupted results. Various researchers have come out with new genetic operators which when applied to standard CGP or its variants have given better results either in the form of better convergence or efficiency. In this paper, we performed a comparative evaluation of four genetic operators, namely standard crossover, Clegg’s crossover, Graph-based crossover, and forking operator, on standard CGP and tested them on standard benchmark datasets such as Koza-2, Koza-3, and Nguyen-2. Our evaluation shows that both Clegg’s crossover and forking operator performs better than the others.
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Manazir, A., Raza, K. (2022). Comparative Evaluation of Genetic Operators in Cartesian Genetic Programming. In: Abraham, A., Gandhi, N., Hanne, T., Hong, TP., Nogueira Rios, T., Ding, W. (eds) Intelligent Systems Design and Applications. ISDA 2021. Lecture Notes in Networks and Systems, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-030-96308-8_71
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