Stability Analysis of Artificial Bee Colony Optimization Algorithm

Bansal, Jagdish Chand and Gopal, Anshul and Nagar, Atulya K. (2018) Stability Analysis of Artificial Bee Colony Optimization Algorithm. Swarm and Evolutionary Computation, 41. pp. 9-19. ISSN 2210-6502 (Accepted for Publication)

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Theoretical analysis of swarm intelligence and evolutionary algorithms is relatively less explored area of research. Stability and convergence analysis of swarm intelligence and evolutionary algorithms can help the researchers to fine tune the parameter values. This paper presents the stability analysis of a famous Artificial Bee Colony (ABC) optimization algorithm using von Neumann stability criterion for two-level finite difference scheme. Parameter selection for the ABC algorithm is recommended based on the obtained stability conditions. The findings are also validated through numerical experiments on test problems.

Item Type: Article
Additional Information and Comments: “NOTICE: this is the author’s version of a work that was accepted for publication in Swarm and Evolutionary Computation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version is available at
Keywords: Artificial Bee Colony (ABC) Algorithm, Stability Analysis, Finite Difference Scheme, Parameter Selection, Stable Range
Faculty / Department: Faculty of Science > Mathematics and Computer Science
Depositing User: Atulya Nagar
Date Deposited: 12 Jan 2018 11:30
Last Modified: 26 Nov 2018 14:59

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