An improved binary artificial bee colony algorithm

Abstract

The xor-based artificial bee colony algorithm, called as binABC, is a novel variant of basic artificial bee colony (ABC) algorithm, which is proposed for solving binary optimization problems. This algorithm uses xor logic operator to search solution space instead of subtraction-based solution update rule of basic ABC due to discrete nature of the binary optimization. Similar to basic version of the algorithm, only one decision variable (dimension) is updated by the artificial agents of binABC. This approach causes slow convergence in the algorithm, and a proportional changing, which is depended on the number of decision variable of the optimization problem, is proposed in this study. The proposed approach is applied to solve a well-known binary optimization problem whose name is uncapacitated facility location problem (UFLP). Twelve instances of this problem are used in the experiments and obtained results are compared with the binABC algorithm in terms of solution quality, robustness and convergence characteristics. Experimental results show that the proposed approach is useful for controlling convergence characteristics and obtaining better quality of solution.