Multi-guide particle swarm optimization for multi-objective optimization: empirical and stability analysis

This article presents a new particle swarm optimization (PSO)-based multi-objective optimization algorithm, named multi-guide particle swarm optimization (MGPSO). The MGPSO is a multi-swarm approach, where each subswarm optimizes one of the objectives. An archive guide is added to the velocity updat...

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Veröffentlicht in:	Swarm intelligence Jg. 13; H. 3-4; S. 245 - 276
Hauptverfasser:	Scheepers, Christiaan, Engelbrecht, Andries P., Cleghorn, Christopher W.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2019 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Communications Engineering Computer Communication Networks Computer Science Computer Systems Organization and Communication Networks Exploration Exploratory behavior Mathematical and Computational Engineering Networks Optimization Velocity Attainment surface Order-2 stability Multi-objective optimization Stability analysis Multi-guide particle swarm optimization Particle swarm optimization Order-1 stability
ISSN:	1935-3812, 1935-3820
Online-Zugang:	Volltext
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