×

Uh-oh, it looks like your Internet Explorer is out of date.

For a better shopping experience, please upgrade now.

Tuning Metaheuristics: A Machine Learning Perspective
     

Tuning Metaheuristics: A Machine Learning Perspective

by Mauro Birattari
 

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

Overview

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.

Product Details

ISBN-13:
9783642101496
Publisher:
Springer Berlin Heidelberg
Publication date:
12/08/2010
Series:
Studies in Computational Intelligence Series , #197
Edition description:
Softcover reprint of hardcover 1st ed. 2009
Pages:
221
Product dimensions:
6.14(w) x 9.21(h) x 0.49(d)

Customer Reviews

Average Review:

Post to your social network

     

Most Helpful Customer Reviews

See all customer reviews