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A genetic algorithm(GA)-based new method is designed to evaluate the circularity error of mechanical parts. The method uses the capability of nonlinear optimization of GA to search for the optimal solution of circularity error. The finely-designed GA (FDGA) characterized dynamical bisexual recombination and Gaussian mutation. The mathematical model of the nonlinear problem is given. The implementation details in FDGA are described such as the crossover or recombination mechanism which utilized a bisexual reproduction scheme and the elitist reservation method; and the adaptive mutation which used the Gaussian probability distribution to determine the values of the offspring produced by mutation mechanism. The examples are provided to verify the designed FDGA. The computation results indicate that the FDGA works very well in the field of form error evaluation such as circularity evaluation.
A genetic algorithm (GA) -based new method is designed to evaluate the circularity error of mechanical parts. The method uses the capability of nonlinear optimization of GA to search for the optimal solution of circularity error. The finely-designed GA (FDGA) The mathematical model of the nonlinear problem is given. The mathematical model of the nonlinear problem is given. The implementation details in FDGA are described as the crossover or recombination mechanism which uses a bisexual recombination scheme and the elitist reservation method; and the adaptive mutation which used the The examples are provided to verify the designed FDGA. The computation results indicate that the FDGA works very well in the field of form error evaluation such as circularity evaluation.