Overview
- Covers use of software language R for a spectrum of modern optimization methods
- Includes exercise sets and solutions
- Suitable for undergraduate and graduate students in Computer Science and Information Technology, and for data analysts
- Includes supplementary material: sn.pub/extras
Part of the book series: Use R! (USE R)
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Table of contents (7 chapters)
Keywords
About this book
This new edition integrates the latest R packages through text and code examples. It also discusses new topics, such as: the impact of artificial intelligence and business analytics in modern optimization tasks; the creation of interactive Web applications; usage of parallel computing; and more modern optimization algorithms (e.g., iterated racing, ant colony optimization, grammatical evolution).
Authors and Affiliations
About the author
Paulo Cortez (Habilitation, PhD) is an Associate Professor (with tenure) at the Department of Information Systems, University of Minho, Portugal. He is also assistant director of the ALGORITMI R&D Centre. From 2012 to 2015, he was Vice-President of the Portuguese Association for Artificial Intelligence (www.appia.pt). Currently, he is Associate Editor of the journals Decision Support Systems and Expert Systems. His research, within the fields of decision support, data science, business analytics, machine learning, and modern optimization, has appeared in Journal of Heuristics, Decision Support Systems, Information Processing and Management, Information Sciences and others.
Bibliographic Information
Book Title: Modern Optimization with R
Authors: Paulo Cortez
Series Title: Use R!
DOI: https://doi.org/10.1007/978-3-030-72819-9
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-72818-2Published: 31 July 2021
eBook ISBN: 978-3-030-72819-9Published: 30 July 2021
Series ISSN: 2197-5736
Series E-ISSN: 2197-5744
Edition Number: 2
Number of Pages: XVII, 254
Number of Illustrations: 43 b/w illustrations
Topics: Statistics and Computing/Statistics Programs, Optimization, Data Structures and Information Theory, Artificial Intelligence, Statistics, general, Professional Computing