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 novel artificial bee colony algorithm with Powell's method
TL;DR: A modified search equation is proposed which is applied to generate a candidate solution in the onlookers phase to improve the search ability of ABC and the Powell's method is used as a local search tool to enhance the exploitation of the algorithm.
Journal ArticleDOI
A novel artificial bee colony algorithm with depth-first search framework and elite-guided search equation
TL;DR: A depth-first search (DFS) framework is designed for ABC and is applied to ABC, GABC and CABC, yielding DFSABC, DFSGABC and DFSCABC respectively, which is better than other ABC variants and non-ABC methods on many benchmark functions.
Journal ArticleDOI
Performance analysis of two-degree of freedom fractional order PID controllers for robotic manipulator with payload
TL;DR: Numerical simulation results indicate that the 2-DOF FOPID controllers are superior to their integer order counterparts and the traditional PID controllers.
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Modified artificial bee colony algorithm based on fuzzy multi-objective technique for optimal power flow problem
TL;DR: In this article, a fuzzy-based modified artificial bee colony (MABC) algorithm is proposed to solve discrete optimal power flow (OPF) problem that has both discrete and continuous variables considering valve point effects.
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.