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Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 41)
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Table of contents (10 chapters)
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Front Matter
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Back Matter
About this book
Uncertainty in the problem data often cannot be avoided when dealing with practical problems. Errors occur in real-world data for a host of reasons. However, over the last thirty years, the fuzzy set approach has proved to be useful in these situations. It is this approach to optimization under uncertainty that is extensively used and studied in the second part of this book. Typically, the membership functions of fuzzy sets involved in such problems are neither concave nor convex. They are, however, often quasiconcave or concave in some generalized sense. This opens possibilities for application of results on generalized concavity to fuzzy optimization. Despite this obvious relation, applying the interface of these two areas has been limited to date. It is hoped that the combination of ideas and results from the field of generalized concavity on the one hand and fuzzy optimization on the other hand outlined and discussed in Generalized Concavity in Fuzzy Optimization and Decision Analysis will be of interest to both communities. Our aimis to broaden the classes of problems that the combination of these two areas can satisfactorily address and solve.
Authors and Affiliations
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School of Business Administration, Silesian University, Karviná, Czech Republic
Jaroslav Ramík
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School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan
Milan Vlach
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Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic
Milan Vlach
Bibliographic Information
Book Title: Generalized Concavity in Fuzzy Optimization and Decision Analysis
Authors: Jaroslav Ramík, Milan Vlach
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/978-1-4615-1485-5
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 2002
Hardcover ISBN: 978-0-7923-7495-4Published: 30 September 2001
Softcover ISBN: 978-1-4613-5577-9Published: 01 November 2012
eBook ISBN: 978-1-4615-1485-5Published: 06 December 2012
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: XV, 296
Topics: Optimization, Mathematical Logic and Foundations, Calculus of Variations and Optimal Control; Optimization, Convex and Discrete Geometry, Operations Research/Decision Theory