Learning and Intelligent Optimization: 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers

Author:   Clarisse Dhaenens ,  Laetitia Jourdan ,  Marie-Eléonore Marmion
Publisher:   Springer International Publishing AG
Edition:   2015 ed.
Volume:   8994
ISBN:  

9783319190839


Pages:   313
Publication Date:   09 June 2015
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Learning and Intelligent Optimization: 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers


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Overview

This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Learning and Optimization, LION 9, which was held in Lille, France, in January 2015. The 31 contributions presented were carefully reviewed and selected for inclusion in this book. The papers address all fields between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. Special focus is given to algorithm selection and configuration, learning, fitness landscape, applications, dynamic optimization, multi-objective, max-clique problems, bayesian optimization and global optimization, data mining and - in a special session - also on dynamic optimization.

Full Product Details

Author:   Clarisse Dhaenens ,  Laetitia Jourdan ,  Marie-Eléonore Marmion
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2015 ed.
Volume:   8994
Dimensions:   Width: 15.50cm , Height: 1.80cm , Length: 23.50cm
Weight:   4.978kg
ISBN:  

9783319190839


ISBN 10:   3319190830
Pages:   313
Publication Date:   09 June 2015
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Benchmark problems and performance measures.- Tracking moving optima.- Dynamic multiobjective optimization.- Adaptation, learning, and anticipation.- Handling noisy fitness functions.- Using fitness approximations.- Searching for robust optimal solutions.- Comparative studies.- Hybrid approaches.- Theoretical analysis.- Real-world applications.

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