Overview
- cutting-edge research in fuzzy decision theory and applications
- how to deal with uncertain and incomplete information in decision-making
- Includes practical case-studies on real-life management problems
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 333)
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About this book
This book shows how common operation management methods and algorithms can be extended to deal with vague or imprecise information in decision-making problems. It describes how to combine decision trees, clustering, multi-attribute decision-making algorithms and Monte Carlo Simulation with the mathematical description of imprecise or vague information, and how to visualize such information. Moreover, it discusses a broad spectrum of real-life management problems including forecasting the apparent consumption of steel products, planning and scheduling of production processes, project portfolio selection and economic-risk estimation. It is a concise, yet comprehensive, reference source for researchers in decision-making and decision-makers in business organizations alike.
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Table of contents (8 chapters)
Authors and Affiliations
Bibliographic Information
Book Title: Advances in Fuzzy Decision Making
Book Subtitle: Theory and Practice
Authors: Iwona Skalna, Bogdan Rębiasz, Bartłomiej Gaweł, Beata Basiura, Jerzy Duda, Janusz Opiła, Tomasz Pełech-Pilichowski
Series Title: Studies in Fuzziness and Soft Computing
DOI: https://doi.org/10.1007/978-3-319-26494-3
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-26492-9Published: 17 November 2015
Softcover ISBN: 978-3-319-36900-6Published: 23 August 2016
eBook ISBN: 978-3-319-26494-3Published: 06 November 2015
Series ISSN: 1434-9922
Series E-ISSN: 1860-0808
Edition Number: 1
Number of Pages: XI, 151
Number of Illustrations: 58 illustrations in colour
Topics: Computational Intelligence, Engineering Economics, Organization, Logistics, Marketing, Operations Research/Decision Theory