Harmony Search as a Metaheuristic Algorithm
By Xin-She Yang. 2010
556 citations recorded by the source corpus.
This first chapter intends to review and analyze the powerful new Harmony Search (HS) algorithm in the context of metaheuristic algorithms. We will first outline the fundamental steps of HS, and show how it works. We then try to identify the characteristics of metaheuristics and analyze why HS is a good metaheuristic algorithm. We then review briefly other popular metaheuristics such as particle swarm optimization so as to find their similarities and differences with HS. Finally, we will discuss the ways to improve and develop new variants of HS, and make suggestions for further research including open questions.
Subfields: Artificial Intelligence, Computational Theory and Mathematics, Industrial and Manufacturing Engineering
View Paper: https://www.semanticscholar.org/paper/ad426f6d07a62302ac954ae49f87767a3a9b881c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Xin-She Yang
- Tansel Dökeroğlu
- Amir H. Gandomi
- Seyedali Mirjalili
- Arpan Kumar Kar
- Ahmet Cosar
- Tayfun Kucukyilmaz
- Ender Sevinç
In Computational Theory and Mathematics
- Xin-She Yang
- Amir H. Gandomi
- Tansel Dökeroğlu
- Suash Deb
- Arpan Kumar Kar
- Ahmet Cosar
- Tayfun Kucukyilmaz
- Ender Sevinç
In Industrial and Manufacturing Engineering
- Amir H. Gandomi
- Suash Deb
- Xin-She Yang
- Amir Hossein Alavi
- Tansel Dökeroğlu
- Abdolreza Hatamlou
- Ahmet Cosar
- Tayfun Kucukyilmaz
Citations in the corpus
- Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems (2011, methodology): “In contrast, most metaheuristic algorithms use either uniform distributions or Gaussian to generate new explorative moves [3, 4].”
- Black hole: A new heuristic optimization approach for data clustering (2013, background): “The action of finding the harmony in music is similar to finding the optimal solution in an optimization process [27].”
- Engineering optimisation by cuckoo search (2010, methodology): “Two important characteristics of metaheuristics are: intensification and diversification (Blum and Roli 2003, Gazi and Passino 2004, Yang 2009).”
- A New Metaheuristic Bat-Inspired Algorithm (2010, methodology): “7, this algorithm is virtually reduced to a simple Harmony Search (HS) as the frequency/wavelength change is essentially the pitch adjustment, while the rate of pulse emission is similar to the harmonic acceptance rate (here with a twist) in the harmony search algorithm [4, 15].”
- A survey on new generation metaheuristic algorithms (2019, methodology): “HS is proposed by Yang (2009) in 2001 and has been applied to numerous optimization problems since then (Manjarres et al., 2013).”