@inproceedings{52895953aa204fb88be1aaaef344e416,
title = "A review on hybridization of particle swarm optimization with artificial bee colony",
abstract = "Particle swarm optimization (PSO) and artificial bee colony (ABC) are two formidable population-based optimizers inspired by swarm intelligence(SI). They follow different philosophies and paradigms, and both are successfully and widely applied in scientific and engineering research. The hybridization of PSO and ABC represents a promising way to create more powerful SI-based hybrid optimizers, especially for specific problem solving. In the past decade, numerous hybrids of ABC and PSO have emerged with diverse design ideas from many researchers. This paper is aimed at reviewing the existing hybrids based on PSO and ABC and giving a classification and an analysis of them.",
keywords = "Artificial bee colony (ABC), Hybridization, Particle swarm optimization (PSO), Review, Swarm intelligence",
author = "Bin Xin and Yipeng Wang and Lu Chen and Tao Cai and Wenjie Chen",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 8th International Conference on Swarm Intelligence, ICSI 2017 ; Conference date: 27-07-2017 Through 01-08-2017",
year = "2017",
doi = "10.1007/978-3-319-61833-3_25",
language = "English",
isbn = "9783319618326",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "242--249",
editor = "Ben Niu and Hideyuki Takagi and Yuhui Shi and Ying Tan",
booktitle = "Advances in Swarm Intelligence - 8th International Conference, ICSI 2017, Proceedings",
address = "Germany",
}