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Journal ArticleDOI

A comparative study of Artificial Bee Colony algorithm

Dervis Karaboga, +1 more
- 01 Aug 2009 - 
- Vol. 214, Iss: 1, pp 108-132
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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.
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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.

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Application of machine learning, deep learning and optimization algorithms in geoengineering and geoscience: comprehensive review and future challenge

TL;DR: In this paper , a systematic review on the state-of-the-art application of ML, DL and OA algorithms in geoengineering and geoscience is presented, where the authors provide fundamental guidelines for researchers and engineers in the discipline of geoengineering or similar research areas.
Journal ArticleDOI

Integrating TOPSIS with interval-valued intuitionistic fuzzy cognitive maps for effective group decision making

TL;DR: A novel multi-criteria group decision-making method that integrates TOPSIS with IVIFCMs, a tool that is able to model interactions among highly imprecise criteria that is more consistent than the existing state-of-the-art methods used to solve the addressed decision problem.
Journal ArticleDOI

Deterministic approaches for solving practical black-box global optimization problems

TL;DR: In this paper, some innovative and powerful deterministic approaches developed by the authors to construct numerical methods for solving the mentioned problems are surveyed and their efficiency is shown on solving both the classes of random test problems and some practical engineering tasks.
Journal ArticleDOI

A modification of tree-seed algorithm using Deb’s rules for constrained optimization

TL;DR: The experimental analysis and results show that the proposed method produces promising and comparable results for the constrained optimization benchmark set in terms of solution quality and robustness.
Proceedings ArticleDOI

An integrated algorithm based on artificial bee colony and particle swarm optimization

TL;DR: A novel hybrid swarm intelligent algorithm is developed to share valuable information mutually between particle swarm and bee colony and performs better than both PSO and ABC.
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

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.