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Journal ArticleDOI

A comparative study of Artificial Bee Colony algorithm

Dervis Karaboga, +1 more
- 01 Aug 2009 - 
- Vol. 214, Iss: 1, pp 108-132
TLDR
Results show that the performance of the ABC is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters.
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This article is published in Applied Mathematics and Computation.The article was published on 2009-08-01. It has received 2835 citations till now. The article focuses on the topics: Artificial bee colony algorithm & Meta-optimization.

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Citations
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Journal ArticleDOI

Artificial Bee Colony Algorithm with Local Search for Numerical Optimization

TL;DR: A novel hybrid Hooke Jeeves ABC (HJABC) algorithm with intensification search based on the HookeJeeves pattern search and the ABC is presented to demonstrate how the standard ABC can be improved by incorporating a hybridization strategy.
Journal ArticleDOI

A Novel Artificial Bee Colony Algorithm for Structural Damage Detection

TL;DR: A novel artificial bee colony (ABC) algorithm to detect structural damage via modal and frequency analyses is proposed (named as TCABC algorithm), and tabu search method and chaotic search method are adopted in the proposed algorithm to enhance the exploration and exploitation ability.
Journal ArticleDOI

Adaptive variational mode decomposition and its application to multi-fault detection using mechanical vibration signals

TL;DR: The results indicate that the proposed adaptive variational mode decomposition (AVMD) method outperforms in separating impulsive multi-fault signals, thus being an efficient method for multi-Fault diagnosis of rotating machines.
Journal ArticleDOI

Short-term hydro generation scheduling of Xiluodu and Xiangjiaba cascade hydropower stations using improved binary-real coded bee colony optimization algorithm

TL;DR: The simulation results demonstrate that the proposed IB-RBCO method can get higher-quality solutions with less water consumption and shorter calculating time when facing the complex STHGS problem.
Journal ArticleDOI

An improved artificial bee colony algorithm and its application to reliability optimization problems

TL;DR: Numerical experiments indicate that the improved version of ABC algorithm, called IABC, provides competitive results compared to several state-of-the-art algorithms in terms of convergence speed, robustness, and solution accuracy.
References
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Proceedings ArticleDOI

Particle swarm optimization

TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Book

Adaptation in natural and artificial systems

TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI

Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces

TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Book

Self-Organizing Maps

TL;DR: The Self-Organising Map (SOM) algorithm was introduced by the author in 1981 as mentioned in this paper, and many applications form one of the major approaches to the contemporary artificial neural networks field, and new technologies have already been based on it.
Book

Genetic Algorithms + Data Structures = Evolution Programs

TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.