Improved Mayfly Optimization Algorithm and its Application in Roundness Error Evaluation
In modern industrial production,roundness error has important reference value in inspecting and evaluating the pro-duction quality of parts.Therefore,an improved mayfly optimization algorithm(MMOA)is proposed to make up for the shortcom-ings of traditional error evaluation methods,that is,slow convergence speed and low accuracy.The improved mayfly optimiza-tion algorithm establishes a mathematical model according to the calculation formula of the minimum region method as the fit-ness evaluation standard.Aiming at the shortcomings of the basic mayfly optimization algorithm(MOA),the Cauchy distribu-tion variation function is introduced to update the global optimal mayfly individual position,and the nonlinear adaptive parame-ter is introduced as the inertia weight of the position update formula of all mayflies.In the iterative process,the simulated anneal-ing algorithm is integrated to reduce the binding force of individuals by local extreme points,and improve the local optimization ability and robustness of the algorithm.Finally,in order to prove the improvement effect of MMOA,simulation experiments are carried out.Experiments show that MMOA can effectively and correctly evaluate roundness error,and the evaluation accuracy is better than genetic algorithm and particle swarm optimization algorithm,and better than MO A in solution quality and stability,which provides a new method for roundness error evaluation.
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维普
