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 algorithm for flexible job shop scheduling with worker flexibility
TL;DR: A hybrid artificial bee colony algorithm (HABCA) is presented to solve the proposed FJSPW, and extensive computational experiments confirm that the proposed HABCA is more effective than some well-performing algorithms from the literature, especially on large-scale FJ SPW instances.
Journal ArticleDOI
Artificial bee colony algorithm with multiple search strategies
TL;DR: A novel ABC with multiple search strategies, named MuABC is developed, which offers the highest solution quality, the fastest global convergence, and the strongest robustness among all the contenders on almost all the cases.
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An improved particle swarm optimization method for multirate filter bank design
TL;DR: The design results included in the paper clearly show the improvement of the proposed PSO technique over earlier reported results.
Journal ArticleDOI
Gaussian bare-bones artificial bee colony algorithm
TL;DR: A Gaussian bare-bones ABC is proposed, where a new search equation is designed based on utilizing the global best solution to generate new food sources for scout bees and employs the generalized opposition-based learning strategy to discover more useful information for guiding search.
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A Novel Binary Spider Monkey Optimization Algorithm for Thinning of Concentric Circular Antenna Arrays
TL;DR: The results prove the competence and superiority of binSMO to existing metaheuristic algorithms and it has an ability to become an effective tool for solving binary optimization problems.
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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.