An Hybrid Operator Improved Monarch Butterfly Optimization Algorithm
For The monarch butterfly optimization algorithm has the problems of slow convergence,easy to fall into local optimum,and low solution accuracy,based on the above,a hybrid operator monarch butterfly opti-mization algorithm based on Cauchy-Gaussian is proposed,which improves the algorithm by introducing the hybrid Cauchy-Gaussian operator in the migration operation and adjustment operation of the standard monarch butterfly algorithm,and playing the strong global search ability of the Cauchy operator and the strong local search ability of the Gaussian operator to improve the algorithm performance.Finally,20 single-peak,multi-peak,hybrid and composite measurement functions are tested by numerical simulation experiments,and al-so compared with other algorithms.The results show that the improved emperor butterfly optimization algorithm has improved the performance of convergence and solution accuracy,and the improved algorithm has better a-daptability and robustness than other algorithms.
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维普
