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Artificial Bee Colony Algorithm
2020This research focused on introduction to the Artificial Bee Colony (ABC) algorithm, the foraging behavior and waggle dance of honeybees while passing information about a given food source to the rest of the bee colony. The mathematical modelling and real-life application of the bee algorithm in fast moving grocery retail outlet was presented, the ...
Modestus O. Okwu, Lagouge K. Tartibu
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Shuffled artificial bee colony algorithm
Soft Computing, 2016In this study, we have introduced a hybrid version of artificial bee colony (ABC) and shuffled frog-leaping algorithm (SFLA). The hybrid version is a two-phase modification process. In the first phase to increase the global convergence, the initial population is produced using randomly generated and chaotic system, and then in the second phase to ...
Tarun Kumar Sharma, Millie Pant
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Adaptive artificial bee colony optimization
Proceedings of the 15th annual conference on Genetic and evolutionary computation, 2013In this paper, we propose a novel greedy position update strategy for the ABC algorithm. The greedy position update strategy is implemented mainly in two steps. In the first step, good solutions randomly chosen from the top t solutions in the current population are used to guide the search process of onlooker bees. In the second step, the new parameter
Wei-jie Yu, Jun Zhang, Wei-neng Chen
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Scaled artificial bee colony programming
2018 International Conference on Applied Smart Systems (ICASS), 2018Problems of symbolic regression aim to develop a function, described in symbolic form, that fits a given target fitcases. Artificial bee colony programing algorithm (ABCP) is one of the most feasible automatic programming methods that was proposed to solve symbolic regression problems.
BOUDOUAOUI Yassine, HABBI Hacene
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2014
Another version of Artificial Bee Colony ABC optimization algorithm, which is called the Compact Artificial Bee Colony cABC optimization, for numerical optimization problems, is proposed in this paper. Its aim is to address to the computational requirements of the hardware devices with limited resources such as memory size or low price. A probabilistic
Thi-Kien Dao +4 more
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Another version of Artificial Bee Colony ABC optimization algorithm, which is called the Compact Artificial Bee Colony cABC optimization, for numerical optimization problems, is proposed in this paper. Its aim is to address to the computational requirements of the hardware devices with limited resources such as memory size or low price. A probabilistic
Thi-Kien Dao +4 more
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Self-adaptive artificial bee colony
Optimization, 2014Artificial Bee Colony (ABC) optimization algorithm is a swarm intelligence-based nature inspired algorithm, which has been proved a competitive algorithm with some popular nature-inspired algorithms. ABC has been found to be more efficient in exploration as compared to exploitation. With a motivation to balance exploration and exploitation capabilities
Jagdish Chand Bansal +4 more
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Enhanced compact artificial bee colony
Information Sciences, 2015Challenges in many real-world optimization problems arise from limited hardware availability, particularly when the optimization must be performed on a device whose hardware is highly restricted due to cost or space. This paper proposes a new algorithm, namely Enhanced compact Artificial Bee Colony (EcABC) to address this class of optimization problems.
Banitalebi, Akbar +3 more
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Balanced artificial bee colony algorithm
International Journal of Artificial Intelligence and Soft Computing, 2013Artificial bee colony ABC optimisation algorithm is relatively a recent and simple population-based probabilistic approach for global optimisation over continuous and discrete spaces. It has reportedly outperformed a few evolutionary algorithms EAs and other search heuristics when tested over both benchmark and real world problems.
Jagdish Chand Bansal +3 more
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Artificial Bee Colony Algorithm
2019Swarm intelligence and group behavior of honey bees was the inspiration basis of some metaheuristics. The first one is the Artificial Bee Colony (ABC) algorithm which was introduced by Karaboga in 2005 [1] based on the foraging behavior of honey bees. Other algorithms such as bee colony optimization [2] and bees algorithm [3] were also developed which ...
Ali Kaveh, Taha Bakhshpoori
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Binary artificial bee colony optimization
2011 IEEE Symposium on Swarm Intelligence, 2011Artificial bee colony (ABC) optimization is a relatively new population-based, stochastic optimization technique. ABC was developed to optimize unconstrained problems within continuous-valued domains. This paper proposes three versions of ABC that enable it to be applied to optimization problems with binary-valued domains.
G Pampara, A P Engelbrecht
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