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Recent advances in the optimization of fixed time traffic signals have demonstrated a move towards the use of genetic algorithm optimization with traffic network performance evaluated via stochastic microscopic simulation models. This book examines methods for improved optimization. Several modified versions of the genetic algorithm and alternative genetic operators were evaluated on test networks. Application of the CHC search algorithm with real crossover and mutation operators was found to offer improved optimization efficiency over the standard genetic algorithm with binary genetic operators. Computing resources are best utilized by using a single replication of the traffic simulation model with common random numbers for fitness evaluations. Combining the improvements, delay reductions between 13%-32% were obtained over the standard approaches. A coding scheme allowing for complete optimization of signal phasing is proposed. Alternative delay measurements, amendments to genetic operators and modifications to the CHC algorithm are also suggested.
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MSc, Lecturer, School of Statistics and Actuarial Science, University of the Witwatersrand, Johannesburg, South Africa
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- EditoreVDM Verlag Dr. Müller
- Data di pubblicazione2011
- ISBN 10 3639356802
- ISBN 13 9783639356809
- RilegaturaCopertina flessibile
- Numero di pagine232
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Traffic Signals: Advances in Genetic Algorithm Optimization
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(2011)
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Descrizione libro Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Recent advances in the optimization of fixed time traffic signals have demonstrated a move towards the use of genetic algorithm optimization with traffic network performance evaluated via stochastic microscopic simulation models. This book examines methods for improved optimization. Several modified versions of the genetic algorithm and alternative genetic operators were evaluated on test networks. Application of the CHC search algorithm with real crossover and mutation operators was found to offer improved optimization efficiency over the standard genetic algorithm with binary genetic operators. Computing resources are best utilized by using a single replication of the traffic simulation model with common random numbers for fitness evaluations. Combining the improvements, delay reductions between 13%-32% were obtained over the standard approaches. A coding scheme allowing for complete optimization of signal phasing is proposed. Alternative delay measurements, amendments to genetic operators and modifications to the CHC algorithm are also suggested. 232 pp. Englisch. Codice articolo 9783639356809
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Descrizione libro Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kesur KhewalMSc, Lecturer, School of Statistics and Actuarial Science, University of the Witwatersrand, Johannesburg, South AfricaRecent advances in the optimization of fixed time traffic signals have demonstrated a move towa. Codice articolo 4980530
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Traffic Signals : Advances in Genetic Algorithm Optimization
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VDM Verlag Dr. Müller
(2011)
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ISBN 13: 9783639356809
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Descrizione libro Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Recent advances in the optimization of fixed time traffic signals have demonstrated a move towards the use of genetic algorithm optimization with traffic network performance evaluated via stochastic microscopic simulation models. This book examines methods for improved optimization. Several modified versions of the genetic algorithm and alternative genetic operators were evaluated on test networks. Application of the CHC search algorithm with real crossover and mutation operators was found to offer improved optimization efficiency over the standard genetic algorithm with binary genetic operators. Computing resources are best utilized by using a single replication of the traffic simulation model with common random numbers for fitness evaluations. Combining the improvements, delay reductions between 13%-32% were obtained over the standard approaches. A coding scheme allowing for complete optimization of signal phasing is proposed. Alternative delay measurements, amendments to genetic operators and modifications to the CHC algorithm are also suggested. Codice articolo 9783639356809
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Traffic Signals Advances in Genetic Algorithm Optimization
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(2011)
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ISBN 13: 9783639356809
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