Improved Black Hole Algorithm Based on Golden Sine Operator and Levy Flight Operator

Abstract

The black hole (BH) algorithm is a new type of natural heuristic algorithm inspired by the movement law of the “black hole” celestial body in the universe. BH algorithm has received extensive attention due to its advantages such as fewer parameters, simple algorithm structure and strong exploitation. For the shortcomings of poor exploaration and premature convergence of BH algorithm, the improved golden sine (G-S) operator is introduced into BH algorithm to greatly improve the exploaration. Then the Levy flight operator with controlled step size has become a better local search operator from the global search operator, so the improved Levy flight operator is introduced to further improve the exploitation of BH algorithm. Ultimately, the golden sine operator and Levy flight operator based black hole (GSLBH) algorithm is able to balance the exploaration with exploitation. GSLBH, BH, Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WAO), Firefly Algorithm (FA), Golden Sine Algorithm (Gold-SA) were adopted to carry out the simulation experiments with 17 benchmark functions, respectively, and the statistical data results are analyzed and compared. Finally, it can be concluded that the proposed improved black hole algorithm has better exploaration, and the convergence speed and accuracy of the algorithm have been further improved.