Open Problems in Optimization and Data Analysis: 141 (Springer Optimization and Its Applications)
Language: English
Published by Springer, 2018
Series: Book 133 of 176 - Springer Optimization and Its Applications
- Hardcover
- New

Seller: Biblios, frankfurt am main, hessen, GermanyBiblios
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Condition: New
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PRINT ON DEMAND pp. XIX, 330 43 illus., 24 illus. in color.
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- Title
- Open Problems in Optimization and Data Analysis: 141 (Springer Optimization and Its Applications)
- Publisher
- Springer
- Publication year
- 2018
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319991418
- ISBN 13
- 9783319991412
- Series
- Book 133 of 176: Springer Optimization and Its Applications
Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline.
The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016.
"Synopsis" may belong to another edition of this title.
From the Back Cover
Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline.
The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016.
"About the title" may belong to another edition of this title.
Biblios
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