Minimization of Digital Combinational Circuit using Genetic programming with modified fitness function

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Sharma:2016:iCATccT,

• author = "Peeyush Sharma and Trailokya Nath Sasamal",
• booktitle = "2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT)",
• title = "Minimization of Digital Combinational Circuit using Genetic programming with modified fitness function",
• year = "2016",
• pages = "406--410",
• abstract = "Evolutionary Multi-objective optimisation using Genetic Algorithms (GA) are proven more powerful and efficient methods for optimisation of complex digital circuit problems. In this paper, Genetic programming (GP) has been used based on GA to automate the design of the Digital Combinational Circuit. It is desired to minimise the total number of gates used and number of generations for evolved circuit. GP helps in evaluating the fitness for the circuits that is being evolved by GA. Here, evaluation is performed for the best fitness, average fitness and least fitness with the use of different gates used in GP. Results show, with the use of new constraint evaluation function and fitness function leads to improvement in number of generation, elapsed time and minimization in number of gates used in designing.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ICATCCT.2016.7912032",
• month = jul,
• notes = "Also known as \cite{7912032}",

}

Genetic Programming entries for Peeyush Sharma Trailokya Nath Sasamal

Citations