Adaptive Simplified Chicken Swarm Optimization Based on Inverted S?Shaped Inertia Weight

Considering the issues of premature convergence and low solution accuracy in solving high-dimensional problems with basic chicken swarm optimization algorithm, an adaptive simplified algorithm based on inverted S-shaped inertia weight (ASCSO-S) is proposed. Firstly, a presented by removing all chicks from swarm. Secondly, designed introduced into updating process roosters hens to dynamically adjust their moving step size thus improve speed algorithm. Thirdly, order enhance exploration ability strategy added hens. Simulation experiments 21 classical test functions show that ASCSO-S superior other comparison algorithms terms speed, accuracy, stability. In addition, applied parameter estimation Richards model, results indicate has best fitting compared three algorithms.