Overview
- Introduces basic R codes to solve optimization problems
- Describes DEA models in crisp and fuzzy environments
- Mathematical models are illustrated by several examples
Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 386)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (5 chapters)
Keywords
About this book
This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph.D. students in various disciplines, as well as practitioners and researchers.
Authors and Affiliations
Bibliographic Information
Book Title: Data Envelopment Analysis with R
Authors: Farhad Hosseinzadeh Lotfi, Ali Ebrahimnejad, Mohsen Vaez-Ghasemi, Zohreh Moghaddas
Series Title: Studies in Fuzziness and Soft Computing
DOI: https://doi.org/10.1007/978-3-030-24277-0
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-24276-3Published: 05 August 2019
Softcover ISBN: 978-3-030-24279-4Published: 14 August 2020
eBook ISBN: 978-3-030-24277-0Published: 23 July 2019
Series ISSN: 1434-9922
Series E-ISSN: 1860-0808
Edition Number: 1
Number of Pages: XIV, 236
Number of Illustrations: 70 b/w illustrations, 1 illustrations in colour
Topics: Computational Intelligence, Optimization, Operations Research/Decision Theory, Engineering Economics, Organization, Logistics, Marketing