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
An adaptive artificial bee colony algorithm for global optimization
Alkın Yurtkuran,Erdal Emel +1 more
TL;DR: In this article, the authors proposed an adaptive artificial bee colony algorithm (AABC), which employs six different search rules that have been successfully used in the literature, and a probabilistic selection is applied to determine the search rule to be used in generating a candidate solution.
Journal ArticleDOI
Patch-Levy-based initialization algorithm for Bees Algorithm
TL;DR: A novel initialization algorithm based on the patch concept and Levy flight distribution is proposed to initialize the population of bees in BA and it is incorporated into a proposed enhanced BA variant that significantly outperforms other BA variants and state-of-the-art variants of the Artificial Bee Colony (ABC) algorithm.
Book ChapterDOI
Improved Artificial Bee Colony Algorithm with Chaos
Bin Wu,Shu-hai Fan +1 more
TL;DR: A Chaotic ABC (CABC) that use chaotic searching behavior for candidate food position produced in order to improve the convergence characteristics and to prevent the ABC to get stuck on local solutions is proposed.
Proceedings ArticleDOI
Automatic Data Clustering based on Hybrid Atom Search Optimization and Sine-Cosine Algorithm
TL;DR: The main objective of the proposed clustering method, called ASOSCA, is to find automatically the optimal number of centroids and their positions in order to minimize the CS-index (which refers to Compact- separated index).
Journal ArticleDOI
Library personalized recommendation service method based on improved association rules
TL;DR: The paper proposes a framework to help users understand others’ behavior, which will aid them better take part in group and community with more contribution and delightedness and provides a helpful inspiration for Big Data mining and software development.
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.