Journal ArticleDOI
Global-best harmony search
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A new variant of HS, called global-best harmony search (GHS), is proposed in this paper where concepts from swarm intelligence are borrowed to enhance the performance of HS.About:
This article is published in Applied Mathematics and Computation.The article was published on 2008-05-01. It has received 753 citations till now. The article focuses on the topics: HS algorithm & Harmony search.read more
Citations
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Journal ArticleDOI
Gbest-guided artificial bee colony algorithm for numerical function optimization
Guopu Zhu,Sam Kwong +1 more
TL;DR: An improved ABC algorithm called gbest-guided ABC (GABC) algorithm is proposed by incorporating the information of global best (gbest) solution into the solution search equation to improve the exploitation of ABC algorithm.
Journal ArticleDOI
A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms
Pinar Civicioglu,Erkan Beşdok +1 more
TL;DR: Empirical results reveal that the problem solving success of the CK algorithm is very close to the DE algorithm and the run-time complexity and the required function-evaluation number for acquiring global minimizer by theDE algorithm is generally smaller than the comparison algorithms.
Book ChapterDOI
Harmony Search as a Metaheuristic Algorithm
TL;DR: This first chapter intends to review and analyze the powerful new Harmony Search algorithm in the context of metaheuristic algorithms, and tries to identify the characteristics of meta heuristics and analyze why HS is a good meta heuristic algorithm.
Journal ArticleDOI
A survey on new generation metaheuristic algorithms
TL;DR: In this survey, fourteen new and outstanding metaheuristics that have been introduced for the last twenty years other than the classical ones such as genetic, particle swarm, and tabu search are distinguished.
Journal ArticleDOI
A self-adaptive global best harmony search algorithm for continuous optimization problems
TL;DR: In the proposed SGHS algorithm, a new improvisation scheme is developed so that the good information captured in the current global best solution can be well utilized to generate new harmonies.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
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.
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.
Proceedings ArticleDOI
A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Book
Genetic Programming: On the Programming of Computers by Means of Natural Selection
TL;DR: This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming.
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