1P-ABC, a Simplified ABC Variant for Continuous Optimization Problems

In this paper a novel simplified and fast variant of the ABC algorithm is proposed, 1 Population ABC (1P-ABC), with the aim to increase the efficiency of the ABC algorithm by using only one population of bees, the employed bees, while maintaining a good e ectiveness of the algorithm in solving dicult nonlinear optimization problems. The novel 1P-ABC algorithm was tested, both regarding the efficiency and the success rate, against three known variants of ABC, the original ABC algorithm, an improved variant, Gbest-guided Artificial Bee Colony (GABC), and another improved variant, Fast ABC (F-ABC). The testing was conducted by employing an original testing methodology over a set of 11 scalable, multimodal, continuous optimization functions (10 unconstrained and 1 constrained) most of them with known global solutions. The novel proposed 1P-ABC algorithm outperformed the other ABC variants in efficiency, while for the success rate the results were mixed.