Bacterial foraging algorithm with varying population

Most of evolutionary algorithms (EAs) are based on a fixed population. However, due to this feature, such algorithms do not fully explore the potential of searching ability and are time consuming. This paper presents a novel nature-inspired heuristic optimization algorithm: bacterial foraging algorithm with varying population (BFAVP), based on a more bacterially-realistic model of bacterial foraging patterns, which incorporates a varying population framework and the underlying mechanisms of bacterial chemotaxis, metabolism, proliferation, elimination and quorum sensing. In order to evaluate its merits, BFAVP has been tested on several benchmark functions and the results show that it performs better than other popularly used EAs, in terms of both accuracy and convergency.