Performance Review of Harmony Search,Differential Evolution and Particle Swarm Optimization

Pandey, Hari (2017) Performance Review of Harmony Search,Differential Evolution and Particle Swarm Optimization. IOP Conference Series: Materials Science and Engineering, 225. ISSN 1757-8981 DOI https://doi.org/10.1088/1757-899X/225/1/012221

[img]
Preview
Text
Paper1010.pdf - Published Version
Available under License Creative Commons Attribution.

Download (443kB) | Preview

Abstract

Metaheuristic algorithms are effective in the design of an intelligent system. These algorithms are widely applied to solve complex optimization problems, including image processing, big data analytics, language processing, pattern recognition and others. This paper presents a performance comparison of three meta-heuristic algorithms, namely Harmony Search, Differential Evolution, and Particle Swarm Optimization. These algorithms are originated altogether from different fields of meta-heuristics yet share a common objective. The standard benchmark functions are used for the simulation. Statistical tests are conducted to derive a conclusion on the performance. The key motivation to conduct this research is to categorize the computational capabilities, which might be useful to the researchers.

Item Type: Article
Uncontrolled Keywords: Differential Evolution, Harmony Search, Optimization, Particle Swarm Optimization.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computing and Information Systems
Date Deposited: 31 Oct 2018 12:42
URI: http://repository.edgehill.ac.uk/id/eprint/10804

Archive staff only

Item control page Item control page