Overview
- Brings readers to a full understanding of multiple criteria decision making methodologies
- Provides Python code for all methods
- Features guidelines for selecting an appropriate method for specific decision problems
- Compares key multiple criteria decision aid methods and approaches
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 136)
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Table of contents (6 chapters)
Keywords
- Python script
- fuzzy number theory
- group decision making
- mcdm methodologies
- multiple criteria decision making
- Lexicographic Goal Programming
- Weighted Goal Programming
- Chebyshev Goal Programming
- Classical Goal Programming
- Rank reversal
- AHP
- SIR
- PROMETHEE
- VIKOR
- Fuzzy VIKOR methodology
- trapezoidal fuzzy numbers
- Fuzzy TOPSIS
- TOPSIS
- Multiple Criteria Decision Aid
- unicriterion optimization models
About this book
Readers will greatly benefit from this book by learning and applying various MCDM/A methods. (Adiel Teixeira de Almeida, CDSID-Center for Decision System and Information Development, Universidade Federal de Pernambuco, Recife, Brazil)
Promoting the development and application of multicriteria decision aid is essential to ensure more ethical and sustainable decisions. This book is a great contribution to this objective. It is a perfect blend of theory and practice, providing potential users and researchers with the theoretical bases of some of the best-known methods as well as with the computing tools needed to practice, to compare and to put these methods to use. (Jean-Pierre Brans, Vrije Universiteit Brussel, Brussels, Belgium)
This book is intended for researchers, practitioners and students alike in decision support who wish to familiarize themselves quickly and efficiently with multicriteria decision aiding algorithms. The proposed approach is original, as it presents a selection of methods from the theory to the practical implementation in Python, including a detailed example. This will certainly facilitate the learning of these techniques, and contribute to their effective dissemination in applications. (Patrick Meyer, IMT Atlantique, Lab-STICC, Univ. Bretagne Loire, Brest, France)
Authors and Affiliations
Bibliographic Information
Book Title: Multiple Criteria Decision Aid
Book Subtitle: Methods, Examples and Python Implementations
Authors: Jason Papathanasiou, Nikolaos Ploskas
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-319-91648-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-91646-0Published: 27 September 2018
Softcover ISBN: 978-3-030-06272-9Published: 12 January 2019
eBook ISBN: 978-3-319-91648-4Published: 19 September 2018
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: XVII, 173
Number of Illustrations: 18 b/w illustrations, 18 illustrations in colour
Topics: Operations Research, Management Science, Operations Research/Decision Theory, Software Engineering/Programming and Operating Systems, Mathematical Software, Mathematical Applications in Computer Science