Alternative Mutation Operators in Collaborative Neurodynamic Optimization

摘要

Collaborative neurodynamic optimization (CNO) is a global search technique that integrates the neurodynamic optimization with a swarm intelligence algorithm. Diversity is a key point for global optimization. Mutation operator is employed in CNO to ensure diversity. In the existing literature, the diversification performance of different mutation operators is unknown. In this paper, four mutation operators, Gaussian, Cauchy, Lévy and wavelet mutations, are analyzed to compare the performances of mutation operators. Simulation results on four benchmark multimodal functions are discussed.