BINARY HONEY BADGER ALGORITHM ENHANCED WITH TIME-VARYING SIGMOID TRANSFER FUNCTION AND CROSSOVER STRATEGY

Modeling the foraging behavior of honey badgers, the Honey Badger Algorithm (HBA) is a recently proposed metaheuristic algorithm. In this study, a binary version of this algorithm that was proposed for solving continuous optimization problems was developed. The S-shaped transfer function and crossover strategy were used to transform the continuous algorithm into a binary algorithm. Eight S-shaped transfer functions with constant and time-varying features were used, and the most successful function was determined. Additionally, the effect of time-varying transfer functions was examined. Three strategies, single-point, two-point, and uniform, were applied as crossover strategies, and the uniform strategy, which was more successful than others, was integrated into the algorithm. The binary algorithm (BinHBA) developed in this way was tested on a total of twenty-seven knapsack problems, fifteen small-scale and twelve large-scale. Statistical tests were employed to analyze the results and compare them with methods found in the existing literature. The results showed that the proposed BinHBA for binary optimization problems is effective and preferable.