Research on Grey Wolf Optimization Algorithm Based on Adaptive Adjustment Strategy

Abstract A grey wolf optimization algorithm based on an adaptive adjustment strategy (Improvements-Grey Wolf Optimization, IGWO) is proposed in this paper to address the issues with Grey Optimization (GWO) algorithm, which has a slow convergence speed later stages and where local search global cannot be taken into effective balance. First, chaotic logistic map used initialize population. Next, inverse trigonometric function-based mathematical model developed achieve purposes. Finally, new location update method next-generation improve traversability. Additionally, CEC2013-Benchmark standard test function was evaluate benefits of performance compared GWO, PSO, DEGWO (DE-Grey optimization) algorithms. The improved GWO greatly increased speed, capability, stability. It performs better than other three algorithms as well.