Chaotic inertia weight in black hole algorithm for function optimization

In this study, we will use chaotic inertia weight into the Black Hole Algorithm (BH) in order to further enhance its global search ability. This study proposes a Chaotic Inertia Weight Black Hole Algorithm (CIWBH) method by using chaotic theory into Black Hole Algorithm. In CIWBH, chaos characteristics are combined with the BH algorithm with the intention of further enhancing its performance. Twenty-three benchmark functions are utilized to investigate the efficiency of CIWBH. The results show that the performance of CIWBH are comparable as well as superior to that of the BH algorithm and other metaheuristic algorithms, Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). Simulation results show the efficiency of the proposed algorithm.