Tuning Metaheuristics

Tuning Metaheuristics
-0 %
A Machine Learning Perspective
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Artikel-Nr:
9783642101496
Veröffentl:
2010
Einband:
Paperback
Erscheinungsdatum:
28.10.2010
Seiten:
232
Autor:
Mauro Birattari
Gewicht:
359 g
Format:
235x155x13 mm
Serie:
197, Studies in Computational Intelligence
Sprache:
Englisch
Beschreibung:

The importance of tuning metaheuristics is widely acknowledged in scientific literature. However, there is very little dedicated research on the subject.  Typically, scientists and practitioners tune metaheuristics by hand, guided only by their experience and by some rules of thumb. Tuning metaheuristics is often considered to be more of an art than a science.

This book lays the foundations for a scientific approach to tuning metaheuristics.  The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning.  By adopting a machine learning perspective, the author gives a formal definition of the tuning problem, develops a generic algorithm for tuning metaheuristics, and defines an appropriate experimental methodology for assessing the performance of metaheuristics.

This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning.
Presents a machine learning approach to methaheuristics
Background and State-of-the-Art.- Statement of the Tuning Problem.- F-Race for Tuning Metaheuristics.- Experiments and Applications.- Some Considerations on the Experimental Methodology.- Conclusions.

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