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 high-efficiency adaptive artificial bee colony algorithm using two strategies for continuous optimization
TL;DR: A highly efficient variant of ABC algorithm which is two-strategy adaptive, where among the two proposed search strategies, one has strong exploration ability and the other has strong exploitation ability is proposed.
Journal ArticleDOI
Computational Experiment Research on the Equalization-Oriented Service Strategy in Collaborative Manufacturing
TL;DR: The computational experiment-based evaluation method is proposed and results show that collaborative equalization strategy can effectively enhance the service utilization rate and reduce the completion time in short supply environment;equalization strategy is the optimal one in oversupply market environment.
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Artificial bee colony algorithm based on Parzen window method
TL;DR: Experimental results not only demonstrate the stability and convergence of ABCPW, but also showABCPW outperforms several popular algorithms.
Journal ArticleDOI
Predictive models for concrete properties using machine learning and deep learning approaches: A review
Mohammad Mohtasham Moein,Ashkan Saradar,Komeil Rahmati,S. H. Ghasemzadeh Mousavinejad,James M. Bristow,Vartenie Mardiros Aramali,Moses Karakouzian +6 more
TL;DR: In this article , a review of successful ML and DL model applications to predict concrete mechanical properties is presented, highlighting their applications, performance, current knowledge gaps, and suggestions for future research.
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A new approach to minimum attribute reduction based on discrete artificial bee colony
Dongyi Ye,Zhaojiong Chen +1 more
TL;DR: The experimental results show that the proposed algorithm overall outperforms all the other algorithms in terms of solution quality and is therefore promising for solving the minimum attribute reduction problem.
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.
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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.
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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.
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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.