An Adaptive Fuzzy Chicken Swarm Optimization Algorithm

The chicken swarm optimization (CSO) algorithm is a new intelligence (SIO) and has been widely used in many engineering domains. However, there are two apparent problems with the CSO algorithm, i.e., slow convergence speed difficult to achieve global optimal solutions. Aiming at attacking these of CSO, this paper, we propose an adaptive fuzzy (FCSO) algorithm. proposed FCSO uses system adaptively adjust number chickens random factors achieves balance exploitation exploration capabilities We integrate cosine function into compute position update roosters improve speed. compare eight commonly used, state-of-the-art SIO algorithms terms performance both low- high-dimensional spaces. also verify nonparametric statistical Friedman test. results experiments on 30 black-box benchmarking (BBOB) functions demonstrate that our outperforms other accuracy. In order further test applicability apply it four typical constraints processes. show better accuracy over standard