Numerical and Evolutionary Optimization – NEO 2017
Editors: Trujillo, L., Schütze, O., Maldonado, Y., Valle, P. (Eds.)
Free Preview- Presents recent numerical and evolutionary optimization research
- Includes the outcomes of the Numerical and Evolutionary Optimization (NEO 2017) workshop held in Tijuana, Mexico
- Written by experts in the field
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- About this book
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This book features 15 chapters based on the Numerical and Evolutionary Optimization (NEO 2017) workshop, held from September 27 to 29 in the city of Tijuana, Mexico. The event gathered researchers from two complimentary fields to discuss the theory, development and application of state-of-the-art techniques to address search and optimization problems. The lively event included 7 invited talks and 64 regular talks covering a wide range of topics, from evolutionary computer vision and machine learning with evolutionary computation, to set oriented numeric and steepest descent techniques. Including research submitted by the NEO community, the book provides informative and stimulating material for future research in the field.
- Table of contents (16 chapters)
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Deterministic Parameter Control in Differential Evolution with Combined Variants for Constrained Search Spaces
Pages 3-28
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A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems
Pages 29-61
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Evaluating Memetic Building Spatial Design Optimisation Using Hypervolume Indicator Gradient Ascent
Pages 62-86
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Fitting Multiple Ellipses with PEARL and a Multi-objective Genetic Algorithm
Pages 89-107
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Analyzing Evolutionary Art Audience Interaction by Means of a Kinect Based Non-intrusive Method
Pages 108-123
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Table of contents (16 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Numerical and Evolutionary Optimization – NEO 2017
- Editors
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- Leonardo Trujillo
- Oliver Schütze
- Yazmin Maldonado
- Paul Valle
- Series Title
- Studies in Computational Intelligence
- Series Volume
- 785
- Copyright
- 2019
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG, part of Springer Nature
- eBook ISBN
- 978-3-319-96104-0
- DOI
- 10.1007/978-3-319-96104-0
- Hardcover ISBN
- 978-3-319-96103-3
- Softcover ISBN
- 978-3-030-07144-8
- Series ISSN
- 1860-949X
- Edition Number
- 1
- Number of Pages
- XIV, 312
- Number of Illustrations
- 137 b/w illustrations
- Topics