A Novel Learning Multi-Swarm Particle Swarm Optimization
Data
2023
Autorzy
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
Particle swarm optimization (PSO) is one of the metaheuristic
optimization methods. Because of its many advantages, it is often used to
solve real-world engineering problems. However, in case of complex, multidimensional
tasks, PSO faces some problems related to premature convergence
and stagnation in local optima. To eliminate this inconveniences, in
this paper, a new learning multi-swarm particle swarm optimization method
(LMPSO) with local search operator has been proposed. The presented approach
was tested on a set of nonlinear functions and a CEC2015 test suite.
The obtained results were compared with other optimization methods.
Opis
Słowa kluczowe
learning particle swarm optimization, learning strategy, multiswarm, particle swarm optimization, pso, optimization, swarm intelligence, nauka optymalizacji roju cząstek, strategia uczenia się, optymalizacja roju cząstek, pso, optymalizacja, inteligencja roju
Cytowanie
Borowska B., A Novel Learning Multi-Swarm Particle Swarm Optimization. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 337-341, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.53.