A survey of bacterial foraging optimization

• Published in: Neurocomputing (Amsterdam) Vol. 452; pp. 728 - 746
• Main Authors: Guo, Chen, Tang, Heng, Niu, Ben, Boon Patrick Lee, Chang
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 10.09.2021
• Subjects: Bacterial foraging optimization; CiteSpace; Knowledge mapping; Swarm intelligence; Knowledge mapping; Bacterial foraging optimization; CiteSpace; Swarm intelligence
• ISSN: 0925-2312; 1872-8286
• DOI: 10.1016/j.neucom.2020.06.142

Bacterial foraging optimization algorithm (BFO) is a biological-inspired swarm intelligence optimization algorithm that simulates the foraging behavior of bacteria to obtain maximal energy during the searching process. Since its inception, it has evoked wide attention from researchers. The number of articles about BFO and its variants has grown significantly over the past decades and continues to grow. Hence, there is a clear need for a scientific and comparative review of extant BFO literature based on a common framework that offers a quick glimpse of the development of BFO. In light of this, we develop a bibliometric review via using CiteSpace to construct a knowledge mapping, and then conduct a thorough literature review of BFO research. Based on the analytical results, we present the influential researchers, journals or proceedings, and articles, and discuss various key issues of BFO. Finally, we suggest serval research directions that require further attention. This survey is expected to exhibit a lucid outline and useful guidance for the researchers of BFO.