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Algorithm

Artificial Bee Colony (ABC) is one of the most recently defined
algorithms by
Dervis Karaboga in 2005, motivated by the intelligent
behavior of honey bees. It is as simple as Particle Swarm
Optimization (PSO) and Differential Evolution (DE) algorithms, and
uses only common control parameters such as colony size and maximum
cycle number. ABC as an optimization tool, provides a populationbased
search procedure in which individuals called foods positions are
modified by the artificial bees with time and the bee’s aim is to
discover the places of food sources with high nectar amount and
finally the one with the highest nectar. In ABC system, artificial
bees fly around in a multidimensional search space and some (employed
and onlooker bees) choose food sources depending on the experience
of themselves and their
nest mates, and adjust their positions. Some (scouts)
fly and choose the food sources randomly without using experience.
If the nectar amount of a new source is higher than that of the
previous one in their memory, they memorize the new position and
forget the previous one. Thus, ABC system combines local search
methods, carried out by employed and onlooker bees, with global
search methods, managed by onlookers and scouts, attempting to
balance exploration and exploitation process.
Since 2005, some members of the intelligent systems research group,
the head of the group is
D.Karaboga, have studied on ABC algorithm
and its applications to real worldproblems.
Karaboga and
Basturk
have studied on the version of ABC algorithm for unconstrained
numerical optimization problems and its extended version for the
constrained optimization problems.
Dervis Karaboga (2010) Artificial bee colony algorithm. Scholarpedia, 5(3):6915.
Two new improved implemantation codes of ABC have been just published in Information Sciences: M. Mernik, SH. Liu, D. Karaboga, M. Crepinsek, "On clarifying misconceptions when comparing variants of the Artificial Bee Colony Algorithm by offering a new implementation", Information Sciences, DOI: 10.1016/j.ins.2014.08.040.
A version of ABC algorithm in CRAN (The Comprehensive R Archive) by George G. Vega Yon.
A comprehensive survey: artificial bee colony (ABC) algorithm and applications
A demo program of Artificial Bee Colony Programming ABCP
Artificial Bee Colony Programming ABCP for Symbolic Regression
A Special Session on Artificial Bee Colony Algorithm in CEC 2012
ABC Algorithm Source Code by Delphi for Constrained Optimization has been released (17.05.2011)
Step by Step Procedure of ABC Algorithm can be downloaded from
here (pdf) (16.05.2011)
Neural Network Training by ABC
algorithm, XOR Problem Example has been released (15.03.2011)
A Special Session on Artificial Bee Colony Algorithm in CEC 2011
JAVA Code of
the ABC algorithm has been released (15.04.2010)
C Code of
the ABC algorithm has been released (14.12.2009)
MATLAB Code
of the ABC algorithm version 2 has been released (14.12.2009) (more
optimized coding)
MATLAB code of the basic ABC algorithm has been released (30.12.2008). Please click for
downloading.
You can download the software
demonstrating the scatter of bees in the search space from here
(26.11.2008)
Detailed Pseudocode of the ABC Algorithm can be downloaded from
here (pdf) (14.10.2008)
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Intelligent Systems
Research Group, Department of Computer Engineering, Erciyes University,
Turkiye 










