Hardcover. The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated. Source-codes used for the examples are also presented, this allows a reflection on the "superfluous chance," succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases. The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc. ) and other more sophisticated. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Bibliographic Details

Title: Guided Randomness in Optimization, Volume 1 (Hardcover)
Publisher: ISTE Ltd and John Wiley & Sons Inc, London
Publication Date: 2015
Language: English
ISBN 10: 1848218052
ISBN 13: 9781848218055
Binding: Hardcover
Condition: new

About this title

Synopsis

The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated. Source-codes used for the examples are also presented, this allows a reflection on the "superfluous chance," succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases.

About the Author

Maurice Clerc is recognized as one of the foremost PSO specialists in the world. A former France Telecom Research and Development engineer, he maintains his research activities as a consultant for the XPS (eXtended Particle Swarm) project.

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