Journal ArticleDOI
A comparative study of Artificial Bee Colony algorithm
Dervis Karaboga,Bahriye Akay +1 more
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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
An Artificial Bee Colony Algorithm for the Job Shop Scheduling Problem with Random Processing Times
Rui Zhang,Cheng Wu +1 more
TL;DR: An artificial bee colony (ABC) algorithm for SJSSP with the objective of minimizing the maximum lateness and the K-armed bandit model is utilized for reducing the computational burden in the exact evaluation process.
Journal ArticleDOI
Artificial bee colony algorithm based on knowledge fusion
TL;DR: A novel ABC based on knowledge fusion (KFABC) is proposed, which outperforms nine ABC and three differential evolution algorithms in optimization capability.
Journal ArticleDOI
Modified Backtracking Search Optimization Algorithm Inspired by Simulated Annealing for Constrained Engineering Optimization Problems.
TL;DR: A modified BSA inspired by simulated annealing (BSAISA) to overcome the deficiency of BSA is proposed and it is demonstrated that BSAISA is more effective than BSA and more competitive with other well-known algorithms in terms of convergence speed.
Book ChapterDOI
Artificial Bee Colony Optimization: A New Selection Scheme and Its Performance
TL;DR: The findings show that the ideal population size and whether it is advantageous to use OBs depends on the hardness of the optimization goal, and two newly proposed variants of the ABC outperform the standard ABC significantly on all test functions.
Journal ArticleDOI
Hierarchical artificial bee colony algorithm for RFID network planning optimization.
TL;DR: Simulation results show that the proposed algorithm, called HABC, is superior for solving RNP, in terms of optimization accuracy and computation robustness.
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.