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Single Objective Artificial Bee Colony Optimization

version 1.0.0.0 (6.42 KB) by SKS Labs
Artificial Bee Colony (Termination Criterion: Maximum number of functional evaluations)

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Updated 22 Jan 2018

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Artificial Bee Colony is a single objective optimization technique for unconstrained optimization problems. It has been reported that ABC has been improperly implemented in various works (specially with respect to functional limitations). This implementation is based on the Algorithm 1 provided in the following

On clarifying misconceptions when comparing variants of the Artificial Bee Colony Algorithm by offering a new implementation, Information Sciences 291, (2015) 115-127; https://doi.org/10.1016/j.ins.2014.08.040

Note:
(i) Unlike other computational intelligence techniques, the number of functional evaluations cannot be deterministically determined based on the number of food sources and the number of cycles.

(ii) The user defined parameters are (a) the number of food sources, (b) the number of maximum functional evaluations and (c) the parameter 'limit' which governs the removal of a solution from the solution pool. This has been widely used as (dimension of the problem * No. of food sources) but has been reported to have significant impact on the performance of the algorithm.

(iii) This implementation ensures monotonic convergence.

Cite As

SKS Labs (2020). Single Objective Artificial Bee Colony Optimization (https://www.mathworks.com/matlabcentral/fileexchange/65794-single-objective-artificial-bee-colony-optimization), MATLAB Central File Exchange. Retrieved .

Comments and Ratings (2)

Yu

Hello SKS Lab.
Do you have a simulation for optimal tap selectionof voltage regulators?
Thanks. My email: msamodrou@gmail.com

MATLAB Release Compatibility
Created with R2017b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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