scispace - formally typeset
Journal ArticleDOI

A comparative study of Artificial Bee Colony algorithm

Dervis Karaboga, +1 more
- 01 Aug 2009 - 
- Vol. 214, Iss: 1, pp 108-132
Reads0
Chats0
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.
About
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.

read more

Citations
More filters
Journal ArticleDOI

A comprehensive survey: artificial bee colony (ABC) algorithm and applications

TL;DR: This work presents a comprehensive survey of the advances with ABC and its applications and it is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.
Journal ArticleDOI

Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems

TL;DR: The proposed algorithm is found to secure first rank for the ‘best’ and ‘mean’ solutions in the Friedman’s rank test for all the 24 constrained benchmark problems.
Journal ArticleDOI

Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems

TL;DR: An efficient optimization method called 'Teaching-Learning-Based Optimization (TLBO)' is proposed in this paper for large scale non-linear optimization problems for finding the global solutions.
Journal ArticleDOI

Gbest-guided artificial bee colony algorithm for numerical function optimization

TL;DR: An improved ABC algorithm called gbest-guided ABC (GABC) algorithm is proposed by incorporating the information of global best (gbest) solution into the solution search equation to improve the exploitation of ABC algorithm.
Journal ArticleDOI

Backtracking Search Optimization Algorithm for numerical optimization problems

TL;DR: The Wilcoxon Signed-Rank Test is used to statistically compare BSA's effectiveness in solving numerical optimization problems with the performances of six widely used EA algorithms: PSO, CMAES, ABC, JDE, CLPSO and SADE and shows that in general, BSA can solve the benchmark problems more successfully than the comparison algorithms.
References
More filters
Journal ArticleDOI

Artificial neural networks: a tutorial

TL;DR: The article discusses the motivations behind the development of ANNs and describes the basic biological neuron and the artificial computational model, and outlines network architectures and learning processes, and presents some of the most commonly used ANN models.
Book

Differential Evolution: A Practical Approach to Global Optimization

TL;DR: The differential evolution (DE) algorithm is a practical approach to global numerical optimization which is easy to understand, simple to implement, reliable, and fast as discussed by the authors, which is a valuable resource for professionals needing a proven optimizer and for students wanting an evolutionary perspective on global numerical optimisation.
Book

Introduction to evolutionary computing

TL;DR: The authors have reorganized the material to focus on problems, how to represent them, and then how to choose and design algorithms for different representations, and added a chapter on evolutionary robotics with an outlook on possible exciting developments in this field.
Journal ArticleDOI

On the performance of artificial bee colony (ABC) algorithm

TL;DR: The simulation results show that the performance of ABC algorithm is comparable to those of differential evolution, particle swarm optimization and evolutionary algorithm and can be efficiently employed to solve engineering problems with high dimensionality.
Book ChapterDOI

Artificial Intelligence through Simulated Evolution

TL;DR: This chapter contains sections titled: References Artificial Intelligence through a Simulation of Evolution Natural Automata and Prosthetic Devices and Artificial intelligence through a simulation of Evolution natural automata and prosthetic devices.