Global-best harmony search

By Mahamed G. H. Omran, Mehrdad Mahdavi. Applied Mathematics and Computation, 2008

799 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/dbaa34092df9ccb2286d47ca60ec6884884206a5

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Citations in the corpus

Mathematical and Metaheuristic Applications in Design Optimization of Steel Frame Structures: An Extensive Review (2013, methodology): “[219, 220], adaptive harmony search method [215], improved harmony search method by Santos Coelho and de Andrade Bernert [221], and dynamic harmony search method by Saka et al.”
Shape optimization of structures for frequency constraints by sequential harmony search algorithm (2013, methodology): “In recent years, several improved versions of HS algorithms have been presented in the literature (Omran and Mahdavi 2008 , Pan et al .”
A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms (2011, methodology): “The methods which predicate on the collective search of the patterns for the solutions of the related problem are generally known as the artificial swarm intelligence methods (Dorigo et al. 2000, 2004; Martinoli et al. 2004; Sousa et al. 2004; Mahamed and Mehrdad 2008; Karaboga and Akay 2009b).”
Gbest-guided artificial bee colony algorithm for numerical function optimization (2010, methodology): “The experimental results tested on a set of numerical benchmark functions show that GABC algorithm can outperform ABC algorithm in most of the experiments.”
Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems (2008, background): “The approach of Mahdavi et al. [11] required 200,000 evaluations of the fitness function.”
Electromagnetic field optimization: A physics-inspired metaheuristic optimization algorithm (2016, methodology): “…form 18 July 2015 Accepted 21 July 2015 Keywords: Global optimization Metaheuristics Population-based optimization Golden ratio Evolutionary algorithms a b s t r a c t This paper presents a physics-inspired metaheuristic optimization algorithm, known as Electromagnetic Field Optimization (EFO).”
Chaotic harmony search algorithms (2010, methodology): “Another work is called as global-best harmony search (GHS) and is inspired by the concept of particle swarm optimization (PSO) [5].”
Particle-swarm harmony search for water network design (2009, methodology): “Recently, some researchers have improved the HS algorithm by introducing the particle-swarm concept to continuous-value optimization problems such as benchmark mathematical functions (Omran and Mahdavi 2008 ) and structural design (Li et al .”
Harmony Search as a Metaheuristic Algorithm (2010, methodology): “In the context of HS algorithms, the combination of HS with PSO, the global-best harmony search has been developed [20].”