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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A hybrid artificial bee colony assisted differential evolution algorithm for optimal reactive power flow
Yuancheng Li,Yiliang Wang,Bin Li +2 more
TL;DR: A hybrid ABC assisted DE algorithm, denoted as DE–ABC, is proposed in this study to overcome DE’s disadvantage of requiring large population size and strengthen the global search ability.
Journal ArticleDOI
Evolutionary algorithms for the optimal management of coastal groundwater: A comparative study toward future challenges
TL;DR: Comparisons show that SCE, CACO, and PSO yield superior solutions among the EAs according to the quality of solutions whereas ABC presents the poor performance, and cACO provides the better solutions than the worst EA (ABC) for the problem with the highest decision variables and more complexity.
Journal ArticleDOI
An Improved Artificial Bee Colony Algorithm for Solving Hybrid Flexible Flowshop With Dynamic Operation Skipping
TL;DR: The proposed DABC algorithm to solve the hybrid flexible flowshop scheduling problem with dynamic operation skipping features in molten iron systems is favorably compared against several presented algorithms, both in solution quality and efficiency.
Journal ArticleDOI
Classification of DNA microarrays using artificial neural networks and ABC algorithm
TL;DR: The aim of this research is to propose a methodology for classifying DNA microarray that performs a feature selection process based on a swarm intelligence algorithm to find a subset of genes that best describe a disease.
Journal ArticleDOI
A discrete artificial bee colony algorithm incorporating differential evolution for the flow-shop scheduling problem with blocking
TL;DR: In this article, a discrete artificial bee colony (ABC) algorithm is presented to solve the above scheduling problem with a makespan criterion by incorporating the ABC with differential evolution (DE), which contains three key operators.
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.