A bacterial colony chemotaxis algorithm with self-adaptive mechanism

Abstract

Although communication mechanism between individuals was adopted in the existing bacterial colony chemotaxis algorithm, there still are some defects such as premature, lacking diversity and falling into local optima etc. In this paper, from a new angle of view, we intensively investigate self-adaptive searching behaviors of bacteria, and design a new optimization algorithm which is called as self-adaptive bacterial colony chemotaxis algorithm (SBCC). In this algorithm, in order to improve the adaptability and searching ability of artificial bacteria, a self-adaptive mechanism is designed. As a result, bacteria can automatically select different behavior modes in different searching periods so that to keep fit with complex environments. In the experiments, the SBCC is tested by 4 multimodal functions, and the results are compared with PSO and BCC algorithm. The test results show that the algorithm can get better results with high speed. © 2013 Springer-Verlag.