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Soft Computing

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28-02-2017 | Methodologies and Application

Particle state change algorithm

Authors: Xiang Feng, Hanyu Xu, Huiqun Yu, Fei Luo

Published in: Soft Computing | Issue 8/2018

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Abstract

The matter state change, which is a common phenomenon in nature, shows the process that the matter how to reach the optimal state in the environment. This paper presents a novel particle state change model (PSCM) inspired by mimicking the process of the matter state change. Based on PSCM, a novel particle state change (PSC) algorithm is proposed for solving continuous optimization problems. As a new algorithm, PSC has many differences from other similar nature-inspired algorithms in terms of the basic principle models, mathematical formalization and properties. This paper considers three states of the matter, namely gas state, liquid state and solid state. In a certain circumstance, the matter always converts from an unstable state into a stable state. It is similar to find the optimal solution of an optimization problem. The proposed algorithm also has the advantages in the respects of higher intelligence, effectiveness and lower computation complexity. And the convergence property of PSC is discussed in detail. In order to illustrate the ability of solving optimization problems in continuous domain, the new proposed algorithm is tested on basic function optimization, CEC2016 single-objective real-parameter numerical optimization and CEC2016 learning-base real-parameter single-objective optimization, and compared with eleven existing algorithms. The numerous simulations have shown the effectiveness and suitability of the proposed approach.

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In PSC, popsize is constant (popsize=20).

In this paper, \({\lambda _ - }=10^{-4},\ {\gamma _ - }=10^{-4}\) and we use \(\lambda ,\ \gamma \) instead of \(\lambda _+,\ \gamma _+\).

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Title: Particle state change algorithm
Authors: Xiang Feng
Hanyu Xu
Huiqun Yu
Fei Luo
Publication date: 28-02-2017
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 8/2018
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-017-2520-z

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