Fuzzy MCDM; Fuzzy multicriteria decision-making
Definition
By multicriteria decision-making, we understand choosing the best alternative a i taken from a set A = {a 1, …, a n } according to m criteria G 1, …, G m . In classical theory, it is assumed that the criteria can be characterized precisely, and so, it is possible to decide unambiguously whether each alternative fulfills the given criterion or not. However, this is rarely the case in practice, and so, the fuzzy set approach has been proposed which makes it possible to assume that the criteria can be evaluated imprecisely, for example, “high quality, low reliability, very low weight,” etc. Unlike classical approach which first removes imprecision and then constructs a decision model, the fuzzy set approach removes imprecision only at the very end, if necessary.
The basic concepts of fuzzy decision-making are the following:
- 1.
Decision based on the imprecisely defined set of alternatives, i.e., a fuzzy set of...
This is a preview of subscription content, log in via an institution to check access.
Recommended Reading
Bellman R, Zadeh LA. Decision making in a fuzzy environment. Manag Sci. 1970;17:140–64.
Calvo T, Mayor G, Mesiar R (eds.). Aggregation operators: new trends and applications. Heidelberg: Physica-Verlag; 2002.
Chen SJ, Hwang CL. Fuzzy multiple attribute decision-making, Methods and applications. Lecture notes in economics and mathematical systems, vol. 375. Heildelberg: Springer; 1993.
Cheng CH, Mon DL. Evaluating weapon system by analitical hierarchy process based on fuzzy scales. Fuzzy Set Syst. 1994;63:1–10.
Carlsson C, Fuller R. Fuzzy reasoning in decision making and optimization. Heidelberg/New York: Springer; 2002.
Fodor J, Roubens M. Fuzzy preference modelling and multicriteria decision support. Dordrecht: Kluwer Academic Publishers; 1994.
Grabisch M, Nguyen H, Walker E. Fundamental of uncertainty calculi, with applications to fuzzy inference. Dordrecht: Kluwer Academic; 1995.
Kacprzyk J, Yager RR. Management decision support systems using fuzzy sets and possibility theory. Berlin: Springer; 1985.
Klir GJ, Bo Yuan. Fuzzy set theory: foundations and applications. Upper Saddle River: Prentice Hall; 1995.
Pedrycz W, Ekel P, Parreiras R. Fuzzy multicriteria decision-making: models, methods and applications. Chichester: Wiley; 2010.
Sakawa M. Fuzzy sets and interactive multiobjective optimization, Applied information technology, New York: Plenum Press; 1993.
Novák V., Perrfilieva I., Dvořák A. Insight into Fuzzy Modeling. Wiley & Sons, Hoboken, New Jersey, 2016.
Novák V. Fuzzy sets and their applications. Bristol: Adam Hilger; 1989.
Saaty TJ. Fundamentals of decision making and priority theory With the analytic hierarchy process. Pittsburgh, Pennsylvania: RWS Publications; 2000.
Slowinski R (ed.). Fuzzy sets in decision analysis, operations research and statistics. Handbook of fuzzy sets series. Dordrecht: Kluwer Academic Publishers; 1998.
Zimmermann HJ. Fuzzy set theory and its applications. Dordrecht, Boston: Kluwer Nijhoff; 1985.
Zopounidis C, Pardalos PM, Baourakis G. Fuzzy sets in management, economics and marketing. Singapore: World Scientific; 2001.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media LLC
About this entry
Cite this entry
Novák, V. (2017). Fuzzy Set Approach. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_564-2
Download citation
DOI: https://doi.org/10.1007/978-1-4899-7993-3_564-2
Received:
Accepted:
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4899-7993-3
Online ISBN: 978-1-4899-7993-3
eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering