Biologically Adaptive Artificial Bee Colony for Numerical Optimization
The artificial bee colony (ABC) algorithm is a well-known algorithm for solving numerical optimal problems. In this paper, a biologically adaptive artificial bee colony (BAABC) algorithm is proposed. In BAABC, the initialization of population is performed by the Halton Sequence so the population is generated in potential solution space. Besides, the size of population is varying according to status of solution searching. If BAABC finds a good solution, the size of population is increased for enhancing solution searching and vice versa. To examine the proposed method, fifteen evaluated functions are adopted in experiments. The result shows that BAABC performs better than related ABC methods on most of the test function.