Jetzt 20% Rabatt auf alle English Books. Jetzt in über 4 Millionen Büchern stöbern und profitieren!
Willkommen, schön sind Sie da!
Logo Ex Libris

Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic

  • Kartonierter Einband
  • 105 Seiten
(0) Erste Bewertung abgeben
Bewertungen
(0)
(0)
(0)
(0)
(0)
Alle Bewertungen ansehen
In this book, a methodology for parameter adaptation in meta-heuristic op-timization methods is proposed. This methodology is base... Weiterlesen
20%
78.00 CHF 62.40
Sie sparen CHF 15.60
Print on Demand - Exemplar wird für Sie gedruckt.
Kein Rückgaberecht!
Bestellung & Lieferung in eine Filiale möglich

Beschreibung

In this book, a methodology for parameter adaptation in meta-heuristic op-timization methods is proposed. This methodology is based on using met-rics about the population of the meta-heuristic methods, to decide through a fuzzy inference system the best parameter values that were carefully se-lected to be adjusted. With this modification of parameters we want to find a better model of the behavior of the optimization method, because with the modification of parameters, these will affect directly the way in which the global or local search are performed.Three different optimization methods were used to verify the improve-ment of the proposed methodology. In this case the optimization methods are: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), where some parameters are se-lected to be dynamically adjusted, and these parameters have the most im-pact in the behavior of each optimization method.Simulation results show that the proposed methodology helps to each optimization method in obtaining better results than the results obtained by the original method without parameter adjustment.

Proposes a methodology for parameter adaptation in meta-heuristic optimization methods

Uses three different optimization methods: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), to verify the improvement of the proposed methodology

Demonstrates the advantage of the methodology by using various simulations



Inhalt
Introduction.- Theory and Background.- Problems Statement.- Methodology.- Simulation Results.- Statistical Analysis and Comparison of Results.

Produktinformationen

Titel: Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic
Autor:
EAN: 9783319708508
ISBN: 978-3-319-70850-8
Format: Kartonierter Einband
Herausgeber: Springer, Berlin
Genre: Technik
Anzahl Seiten: 105
Gewicht: 190g
Größe: H238mm x B7mm x T156mm
Jahr: 2018
Untertitel: Englisch
Auflage: 1st ed. 2018

Weitere Produkte aus der Reihe "SpringerBriefs in Computational Intelligence"