Journal ArticleDOI
A comparative study of Artificial Bee Colony algorithm
Dervis Karaboga,Bahriye Akay +1 more
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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
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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
Guopu Zhu,Sam Kwong +1 more
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
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Journal ArticleDOI
Transport modeling by multi-agent systems: a swarm intelligence approach
TL;DR: This article tries to obtain the answer to the following question: Can some principles of natural swarm intelligence in the development of artificial systems aimed at solving complex problems in traffic and transportation?
Book ChapterDOI
Reaction-Diffusion Model of a Honeybee Colony's Foraging Behaviour
TL;DR: The results elucidate the role of natural clustering of the dances in the small area of the have - it has to facilitate the information flow that is beneficial for overall process of colony's food collection.
Proceedings ArticleDOI
Design of fuzzy logic controllers using genetic algorithms
Chia-Ju Wu,Guan-Ya Lin +1 more
TL;DR: From the simulation results, it is found that the designed FLC is robust and can drive the cart system from any given initial state to the desired final state, which verifies the feasibility and validity of the proposed method.
Journal ArticleDOI
How Information-Mapping Patterns Determine Foraging Behaviour of a Honey Bee Colony
Valery Tereshko,Troy Lee +1 more
TL;DR: A model of foraging behaviour of a honeybee colony based on reaction-diffusion equations is developed and studied how mapping the information about the explored environment to the hive determines this behaviour.
Book ChapterDOI
Using bees to solve a data-mining problem expressed as a max-sat one
TL;DR: This paper presents a very recent metaheuristic introduced to solve a 3-sat problem, based on the process of bees' reproduction, which can be classified as an evolutionary algorithm.