Publication detail

Particle Swarm Optimization for Problems with Variable Number of Dimensions

KADLEC, P. ŠEDĚNKA, V.

Original Title

Particle Swarm Optimization for Problems with Variable Number of Dimensions

Type

journal article in Web of Science

Language

English

Original Abstract

Some real-life optimization problems show apart from the dependence on the combination of state variables also the dependence on the complexity of the model describing the problem. Changing model complexity implies changing the number of degrees of freedom (the number of decision space dimensions). A new method called Particle Swarm Optimization for Variable Number of Dimensions is developed here. The well-known particle swarm optimization procedure is modified to handle spaces with variable number of dimensions within a single run. Some well-known benchmark problems are modified to depend on the number of dimensions. Novel performance metrics are defined in the article to evaluate convergence properties of the method. Some recommendations for setting the optimization are made according to results of the method on the proposed benchmark test-suite. The method is compared with the conventional swarm strategies able to solve problems with variable number of dimensions.

Keywords

model selection, particle swarm optimization, evolutionary optimization, variable number of dimensions

Authors

KADLEC, P.; ŠEDĚNKA, V.

Released

27. 4. 2017

Publisher

Taylor and Francis

Location

Londýn, UK

ISBN

0305-215X

Periodical

ENGINEERING OPTIMIZATION

Year of study

49

Number

4

State

United Kingdom of Great Britain and Northern Ireland

Pages from

382

Pages to

399

Pages count

18

URL

http://dx.doi.org/10.1080/0305215X.2017.1316845

BibTex

@article{BUT134370,
  author="Petr {Kadlec} and Vladimír {Šeděnka}",
  title="Particle Swarm Optimization for Problems with Variable Number of Dimensions",
  journal="ENGINEERING OPTIMIZATION",
  year="2017",
  volume="49",
  number="4",
  pages="382--399",
  doi="10.1080/0305215X.2017.1316845",
  issn="0305-215X",
  url="http://dx.doi.org/10.1080/0305215X.2017.1316845"
}