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Tuning Metaheuristics: A Machine Learning Perspective

Condition: BRAND NEW
ISBN: 9783642004827
Author(s): Mauro Birattari
Format: Hardcover
Year: 2009
Edition: 1st
Publisher: Springer
Dimensions: 156 x 234 x 14 (w x l x h)
Pages: 221
Series: Studies in Computational Intelligence
Series Number: 197

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Metaheuristics are a relatively new but already established approachto c- binatorial optimization. A metaheuristic is a generic algorithmic template that can be used for ?nding high quality solutions of hard combinatorial - timization problems. To arrive at a functioning algorithm, a metaheuristic needs to be con?gured: typically some modules need to be instantiated and someparametersneedto betuned.Icallthese twoproblems'structural'an­d 'parametric' tuning, respectively. More generally, I refer to the combination of the two problems as 'tuning'. Tuning is crucial to metaheuristic optimization both in academic research andforpracticalapplications.Never­theless,relativelylittle researchhasbeen devoted to the issue. This book shows that the problem of tuning a me- heuristic can be described and solved as a machine learning problem. Using the machine learning perspective, it is possible to give a formal de?nitionofthetuningproblemandtod­evelopagenericalgorithmfortuning metaheuristics.Moreover,fromthema­chinelearningperspectiveitispossi­ble tohighlightsome?awsinthecurrentre­searchmethodologyandtostatesome guidelines for future empirical analysis in metaheuristics research.
This book is based on my doctoral dissertation and contains results I have obtained starting from 2001 while working within the Metaheuristics Net- 1 work. During these years I have b Please click here to ask a question
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