To solve the problems of low convergence speed and poor optimization ability of snake optimization algorithms,an advanced snake optimization algorithm(ASO)based on improved Tent chaotic mapping and Levy flight disturbance was pro-posed.An improved Tent chaotic map was introduced to enhance the diversity of the initial population.In the exploration and development process of snake swarms,adaptive probability thresholds were introduced to balance the algorithm's global search and local development capabilities.To ensure the direction of population evolution,the Levy flight disturbance and greedy algo-rithm were combined to generate larger disturbances for disadvantaged snake individuals.By comparing with the other four meta heuristic algorithms on 9 complex test functions,experimental results show that the advanced snake optimization algorithm has significant improvements in convergence speed,solution accuracy,and stability.The Wilcoxon rank sum test proves that ASO is significantly different from other algorithms.The ASO algorithm was applied to solve the spring design optimization problem.
维普
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