Minimization of combinational digital circuit using genetic algorithm

Evolutionary Algorithm (EA) methods are proved more effective for solving complex digital circuit design problems and evaluating the fitness of combinational circuits. They optimize circuits in terms of less number of gates and transistors. In the proposed method, we have calculated the best fitness of the circuit from the designed algorithm by adjusting the parameters of Genetic Algorithm (GA) like mutation rate, crossover rate and number of generations. Then the least fitness, average fitness and worst fitness of the algorithm are evaluated. The digital gates fitness approaches to its maximum for different input parameters in different number of generations. In this method we have defined fitness function which is giving digital gate fitness in less number of generations and also optimizing the total number of gates. Experimental results are showing that proposed EA optimized the digital circuit with less number of gates and maximum fitness is evolved with less number of generations.

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