Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization
Joint Authors
Li, Chaofeng
Mao, Yu
Zhou, Changxi
Wei, Xiao
Yang, Hong
Mao, Li
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-01-28
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Artificial bee colony (ABC) algorithm has good performance in discovering the optimal solutions to difficult optimization problems, but it has weak local search ability and easily plunges into local optimum.
In this paper, we introduce the chemotactic behavior of Bacterial Foraging Optimization into employed bees and adopt the principle of moving the particles toward the best solutions in the particle swarm optimization to improve the global search ability of onlooker bees and gain a hybrid artificial bee colony (HABC) algorithm.
To obtain a global optimal solution efficiently, we make HABC algorithm converge rapidly in the early stages of the search process, and the search range contracts dynamically during the late stages.
Our experimental results on 16 benchmark functions of CEC 2014 show that HABC achieves significant improvement at accuracy and convergence rate, compared with the standard ABC, best-so-far ABC, directed ABC, Gaussian ABC, improved ABC, and memetic ABC algorithms.
American Psychological Association (APA)
Mao, Li& Mao, Yu& Zhou, Changxi& Li, Chaofeng& Wei, Xiao& Yang, Hong. 2016. Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112928
Modern Language Association (MLA)
Mao, Li…[et al.]. Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization. Mathematical Problems in Engineering No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1112928
American Medical Association (AMA)
Mao, Li& Mao, Yu& Zhou, Changxi& Li, Chaofeng& Wei, Xiao& Yang, Hong. Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112928
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112928