Detail publikace

Particle Swarm Optimization for Problems with Variable Number of Dimensions

KADLEC, P. ŠEDĚNKA, V.

Originální název

Particle Swarm Optimization for Problems with Variable Number of Dimensions

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

KADLEC, P.; ŠEDĚNKA, V.

Vydáno

27. 4. 2017

Nakladatel

Taylor and Francis

Místo

Londýn, UK

ISSN

0305-215X

Periodikum

ENGINEERING OPTIMIZATION

Ročník

49

Číslo

4

Stát

Spojené království Velké Británie a Severního Irska

Strany od

382

Strany do

399

Strany počet

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"
}