A novel multi-objective quantum particle swarm algorithm for suspension optimization

In this paper, a novel multi-objective archive-based Quantum Particle Optimizer (MOQPSO) is proposed for solving suspension optimization problems. The algorithm has been adapted from the well-known single objective QPSO by substantial modifications in the core equations and implementation of new mul...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Computational & applied mathematics Ročník 39; číslo 2
Hlavní autoři:	Grotti, Ewerton, Mizushima, Douglas Makoto, Backes, Artur Dieguez, de Freitas Awruch, Marcos Daniel, Gomes, Herbert Martins
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.05.2020 Springer Nature B.V
Témata:	Algorithms Applications of Mathematics Applied physics Computational mathematics Computational Mathematics and Numerical Analysis Computer programming Genetic algorithms Mathematical Applications in Computer Science Mathematical Applications in the Physical Sciences Mathematics Mathematics and Statistics Multiple objective analysis Numerical models Optimization Computational method stochastic programming 70E55 90C29 Dynamics of multibody systems 90C15 Multi-objective and goal programming 93B40
ISSN:	2238-3603, 1807-0302
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!