An improved QPSO algorithm and its application in fuzzy portfolio model with constraints

Aiming at the shortcomings of quantum-behaved particle swarm optimization algorithm (QPSO), an improved quantum-behaved particle swarm optimization algorithm (IQPSO) is put forward, and the improved algorithm is applied in solving a kind of fuzzy portfolio selection problems. Firstly, a kind of port...

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Veröffentlicht in:	Soft computing (Berlin, Germany) Jg. 25; H. 12; S. 7695 - 7706
Hauptverfasser:	He, Guang, Lu, Xiao-li
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2021 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Computational Intelligence Constraint modelling Control Engineering Focus Fuzzy sets Heuristic methods Investments Mathematical Logic and Foundations Mechatronics Optimization algorithms Parameter estimation Particle swarm optimization Random variables Robotics Securities markets Simulation Tax rates Thermal expansion Velocity Fuzzy return rate Hybrid distribution Quantum-behaved particle swarm optimization algorithm Contraction–expansion coefficient Background risk
ISSN:	1432-7643, 1433-7479
Online-Zugang:	Volltext
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