Tuning Metaheuristics: A Machine Learning Perspective: 197 (Studies in Computational Intelligence, 197) - Image 1

£73.96

Springer Tuning Metaheuristics: A Machine Learning Perspective: 197 (Studies in Computational Intelligence, 197)

Name: Tuning Metaheuristics: A Machine Learning Perspective: 197 (Studies in Computational Intelligence, 197)
Brand: Springer
Price: 73.96 GBP
Availability: InStock

AI & Machine Learning

Price History & Forecast

Last 81 days • 81 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 81 days • 1 price levels

Days at Price

Price Analysis

Most common price: £74 (81 days, 100.0%)

Price range: £74 - £74

Price levels: 1 different prices over 81 days

Description

Product Description 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. From the Back Cover 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 Specifications

Brand: Springer
Format: hardcover
ASIN: 3642004822
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 08 April 2009
Listed Since: 30 January 2009

Barcode

No barcode data available

Springer Tuning Metaheuristics: A Machine Learning Perspective: 197 (Studies in Computational Intelligence, 197)

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Adaptive and Multilevel Metaheuristics: 136 (Studies in Computational Intelligence, 136)

Metaheuristics for Data Clustering and Image Segmentation: 152 (Intelligent Systems Reference Library, 152)

Hybrid Metaheuristics: An Emerging Approach to Optimization: 114 (Studies in Computational Intelligence, 114)

Metaheuristics: Progress in Complex Systems Optimization: 39 (Operations Research/Computer Science Interfaces Series, 39)

Recent Advances in Evolutionary Multi-objective Optimization: 20 (Adaptation, Learning, and Optimization, 20)

Computational Intelligence-based Optimization Algorithms: From Theory to Practice

Metaheuristic Algorithms: Theory and Practice

Nature-Inspired Optimization Algorithms

NEO 2016: Results of the Numerical and Evolutionary Optimization Workshop NEO 2016 and the NEO Cities 2016 Workshop held on September 20-24, 2016 in ... (Studies in Computational Intelligence, 731)

Autonomous Search

Numerical and Evolutionary Optimization – NEO 2017: 785 (Studies in Computational Intelligence, 785)

Evolutionary Multiobjective Optimization: Theoretical Advances and Applications (Advanced Information and Knowledge Processing)

Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications (Springer Tracts in Nature-Inspired Computing)

Proceedings of International Conference on Scientific and Natural Computing: Proceedings of SNC 2021 (Algorithms for Intelligent Systems)

Optimization and Applications: 12th International Conference, OPTIMA 2021, Petrovac, Montenegro, September 27 – October 1, 2021, Proceedings: 13078 (Lecture Notes in Computer Science, 13078)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2013): Learning, Optimization and Interdisciplinary Applications: 512 (Studies in Computational Intelligence, 512)

Genetic Algorithms and Fuzzy Multiobjective Optimization: 14 (Operations Research/Computer Science Interfaces Series, 14)

Lösung des Traveling-Salesman-Problems mittels Monte-Carlo-Simulation und Simulated Annealing auf einem HPC-Cluster

Linear and Nonlinear Optimization: 253 (International Series in Operations Research & Management Science, 253)

Computational Intelligence Paradigms: Theory & Applications using MATLAB

Nonlinear Conjugate Gradient Methods for Unconstrained Optimization: 158 (Springer Optimization and Its Applications, 158)

Optimization Theory and Methods: Nonlinear Programming: 1 (Springer Optimization and Its Applications, 1)

Optimization Theory and Methods: Nonlinear Programming: 1 (Springer Optimization and Its Applications, 1)

Multi-Objective Machine Learning: 16 (Studies in Computational Intelligence, 16)