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Item #:
210079907
Approximation and Optimization: Algorithms, Complexity and Applications (Springer Optimization and Its Applications Book 145)
Item #:
210079907
DOP 4356
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This book focuses on the development of approximation-related algorithms and their relevant applications.
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What Stands Out
Comprehensive Coverage
This book offers a thorough exploration of approximation and optimization techniques, making it an essential resource for students and professionals who need a solid foundation in algorithms and their complexities.
Real-World Applications
Each chapter includes practical applications of algorithms, bridging the gap between theory and practice, thus equipping readers with tools to solve complex optimization problems in various fields.
Expert Insights
Authored by industry experts, this edition provides updated perspectives and methodologies, ensuring the reader benefits from the latest trends and research developments in optimization and computational complexity.
Product Details
- This book focuses on the development of approximation-related algorithms and their relevant applications. Individual contributions are written by leading experts and reflect emerging directions and connections in data approximation and optimization. Chapters discuss state of the art topics with highly relevant applications throughout science, engineering, technology and social sciences. Academics, researchers, data science practitioners, business analysts, social sciences investigators and graduate students will find the number of illustrations, applications, and examples provided useful.This volume is based on the conference Approximation and Optimization: Algorithms, Complexity, and Applications, which was held in the National and Kapodistrian University of Athens, Greece, June 29–30, 2017. The mix of survey and research content includes topics in approximations to discrete noisy data; binary sequences; design of networks and energy systems; fuzzy control; large scale optimization; noisy data; data-dependent approximation; networked control systems; machine learning ; optimal design; no free lunch theorem; non-linearly constrained optimization; spectroscopy.
| Publisher | Springer |
| Publication date | May 10, 2019 |
| Edition | 1st ed. 2019 |
| Language | English |
| File size | 6.2 MB |
| Enhanced typesetting | Not Enabled |
| X-Ray | Not Enabled |
| Word Wise | Not Enabled |
| Print length | 247 pages |
| Format | Print Replica |
| ISBN-13 | 978-3030127671 |
| Page Flip | Not Enabled |
| Part of series | Springer Optimization and Its Applications |
| Item Weight | 1.5 lbs (680 grams) |
Who Should Buy?
-
Students in Optimization
Ideal for graduate students specializing in optimization techniques and algorithms seeking comprehensive resources and insights.
-
Researchers and Academics
Beneficial for researchers exploring advanced topics in approximation and optimization with a focus on real-world applications.
-
Industry Professionals
Useful for professionals working in data analytics, operations research, or fields requiring optimization solutions and methodologies.
-
Beginners in Mathematics
Not suitable for novices; assumes a solid background in mathematics and prior knowledge of algorithms and optimization.
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Pros
- Comprehensive coverage of algorithms
- Clear explanations and examples
- Useful for various applications
- Well-structured chapters
- Great for both students and professionals
Cons
- Some sections may be too advanced for beginners.
Product Price History
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Features & Benefits
- Offers insights into approximation-related algorithms and applications.
- Written by leading experts in the field.
- Covers highly relevant applications in various disciplines including science and engineering.
- Includes a mix of survey and research content.
- Utilizes numerous illustrations, applications, and examples for better understanding.
- Ideal for academics, researchers, data science practitioners, and students.
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