Bacterial foraging with quorum sensing based optimization algorithm

Optimization methods have been developed by many researchers. Especially, the methods based on evolutionary algorithms (EAs) have received increased attention from diversity fields. Recently, bacterial foraging algorithm mimicked bacterial behavior has been introduced by Passino. However, his work did not implement an important bacterial behavior regulating division so-called dasiaquorum-sensingpsila. The quorum-sensing is a chemical communication including producing, releasing, detecting, and responding to small hormone-like molecules termed autoinducers. This communication allows bacteria to coordinate the behavior of the group. This paper proposes an optimization algorithm based on the bacterial quorum sensing. In order to estimate the performance of the algorithm, we use a multimodal Gaussian having several minima and maxima, and also four benchmark functions. Experimental results show that this proposed method can achieve better performance than conventional bacterial foraging algorithm.