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Kinetic Gas Molecule Optimization (KGMO)

Kinetic Gas Molecule Optimization (KGMO)
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Copyright: 2018
Pages: 36
Source title: Electrocardiogram Signal Classification and Machine Learning: Emerging Research and Opportunities
Source Author(s)/Editor(s): Sara Moein (Mount Sinai School of Medicine, USA)
DOI: 10.4018/978-1-5225-5580-3.ch008

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Abstract

In this chapter, an optimization algorithm that is based on the kinetic energy of gas molecules, namely kinetic gas molecule optimization (KGMO), is introduced. This algorithm has some agents that are gas molecules, which move in the search space; these agents are subject to the kinetic theory of gases, which defines the rules for gas molecule interactions in the model. This algorithm has a good performance in terms of finding the global minima in 23 nonlinear benchmark functions, and the performance is compared with two other benchmark algorithms, namely particle swarm optimization (PSO) and the recently developed high-performance gravitational search algorithm (GSA).

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