Research on scheduling of the RGV system based on QPSO

This paper presents an improved quantum behaved particle swarm optimization (QPSO) algorithm for rail guided vehicles system (RGV). First, a model of RGV system that using interleaving is proposed. Then an optimization methods based on QPSO is proposed , and a Gaussian mutation operator is defined t...

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Bibliographic Details
Published inIEEE ICCA 2010 pp. 1169 - 1174
Main Authors Jian Luo, Chang-qing Wu, Wen-cai Hong, Yong Cheng, San-yao Xu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2010
Subjects
Automation
Buffer storage
Intelligent vehicles
Interleaved codes
Optimization methods
Particle swarm optimization
Remotely operated vehicles
Routing
Scheduling algorithm
System recovery
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Summary:This paper presents an improved quantum behaved particle swarm optimization (QPSO) algorithm for rail guided vehicles system (RGV). First, a model of RGV system that using interleaving is proposed. Then an optimization methods based on QPSO is proposed , and a Gaussian mutation operator is defined to improve the algorithm's local convergence ability. The feasibility and effectiveness of proposed approach is illustrated by the simulation experiment.
ISBN:9781424451951
1424451957
ISSN:1948-3449
1948-3457
DOI:10.1109/ICCA.2010.5524023