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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
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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

Lévy flight artificial bee colony algorithm

TL;DR: The proposed Lévy flight inspired search strategy outperforms the basic ABC and recent variants of ABC, namely, Gbest-guided ABC, best-so-far ABC and modified ABC in most of the experiments.
Journal ArticleDOI

The analysis of discrete artificial bee colony algorithm with neighborhood operator on traveling salesman problem

TL;DR: This study focused on analysis of discrete ABC with neighborhood operator for well-known traveling salesman problem and different discrete neighborhood operators are replaced with solution updating equations of the basic ABC.
Journal ArticleDOI

Review: Coastal groundwater optimization—advances, challenges, and practical solutions

TL;DR: In this article, the authors present a review of the state-of-the-art tools for coastal groundwater management (CGM) in terms of their performance and choice of robust tools such as EAs, surrogate models, and parallel processing techniques.
Journal ArticleDOI

Combustion optimization of a boiler based on the chaos and Lévy flight vortex search algorithm

TL;DR: A logic self-map chaos and Levy flight Vortex Search (I-VS) algorithm is proposed for boiler combustion optimization and experimental results show that the I-VS-FLN model has better generalization ability than five other models.
Journal ArticleDOI

Tackling global optimization problems with a novel algorithm – Mouth Brooding Fish algorithm

TL;DR: This paper proposes a novel global optimization algorithm inspired by Mouth Brooding Fish in nature, which simulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem.
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.