Journal ArticleDOI
A comparative study of Artificial Bee Colony algorithm
Dervis Karaboga,Bahriye Akay +1 more
TLDR
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
Electromagnetic Inverse Scattering of Axially Moving Cylindrical Targets
TL;DR: Electromagnetic inverse scattering techniques are considered to reconstruct the permittivity and the velocity profiles of axially moving cylindrical targets and it is shown that it provides good approximations of the profiles to be reconstructed in a very efficient way when the peak velocity is small with respect to the speed of light in vacuum.
Journal ArticleDOI
Optimization of Spot-Welded Joints Combined Artificial Bee Colony Algorithm with Sequential Kriging Optimization
TL;DR: A metamodel-based optimization procedure is proposed to find the optimum locations of spotwelded joints for maximum fatigue life and shows that more competent optimum can be found and the optimization can be executed more efficiently, compared to the conventional methods.
Journal ArticleDOI
A novel artificial bee colony algorithm for inverse kinematics calculation of 7-DOF serial manipulators
Li Zhang,Nanfeng Xiao +1 more
TL;DR: CPABC is applied to the inverse kinematics calculation of 7-DOF serial manipulator and the simulation results show that CPABC has stronger global searching ability and more fast convergence rate than that of other ABC algorithms.
Journal ArticleDOI
Multi-objective environmental/economic dispatch solution with penalty factor using artificial bee colony algorithm
TL;DR: In this article, a multi-objective EED solution has been recommended by using artificial bee colony (ABC) algorithm for the solution of the problem, the obtained results from ABC algorithm were compared to those of other algorithms in the literature.
An Efficient Modified Artificial Bee Colony Algorithm for Job Scheduling Problem
TL;DR: An Efficient artificial bee colony (ABC) algorithm, where additional mutation and crossover operator of Genetic algorithm (GA) in the classical ABC algorithm is proposed in this paper, for solving the job scheduling problem with the criterion to decrease the maximum completion time.
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.