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
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Multipurpose image watermarking in the domain of DWT based on SVD and ABC
Irshad Ahmad Ansari,Millie Pant +1 more
TL;DR: The robust insertion is also optimized with the help of ABC (Artificial Bee colony) in such a way that maximum robustness can be assured corresponding to user specific threshold of imperceptibility.
Journal ArticleDOI
Selection of wire electrical discharge machining process parameters using non-traditional optimization algorithms
TL;DR: An attempt is made to apply six most popular population-based non-traditional optimization algorithms, i.e. genetic algorithm, particle swarm optimization, sheep flock algorithm, ant colony optimization, artificial bee colony and biogeography-based optimization for single and multi-objective optimization of two WEDM processes.
Journal ArticleDOI
Multi-objective fuzzy disassembly line balancing using a hybrid discrete artificial bee colony algorithm
TL;DR: A hybrid discrete artificial bee colony algorithm is proposed to solve the problem whose performance is studied over a well-known test problem taken from open literature and over a new data set introduced in this study.
Journal ArticleDOI
A hybrid artificial bee colony algorithm for the job shop scheduling problem
Rui Zhang,Shiji Song,Cheng Wu +2 more
TL;DR: A novel artificial bee colony (ABC) algorithm is proposed for solving the job shop scheduling problem with total weighted tardiness criterion and a tree search algorithm is devised to enhance the exploitation capability of ABC.
Journal ArticleDOI
Identification of structural models using a modified Artificial Bee Colony algorithm
Hao Sun,Hilmi Luş,Raimondo Betti +2 more
TL;DR: In this paper, a modified version of the ABC algorithm is presented to identify structural systems, and a nonlinear factor for convergence control is introduced in the algorithm to enhance the balance of global and local searches.
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
Rainer Storn,Kenneth Price +1 more
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.