Abstract
Traditionally, mathematical programming models produce crisp decision vectors such that some objectives achieve the optimal values. However, for practical purposes, sometimes we should provide a fuzzy decision rather than a crisp one. Bouchon-Meunier et al [26] surveyed various approaches to maximizing a numerical function over a fuzzy set. Buckley and Hayashi [32] presented a fuzzy genetic algorithm (GA) for maximizing a real-valued function by selecting an optimal fuzzy set.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Liu, B. (2002). Fuzzy Programming with Fuzzy Decisions. In: Theory and Practice of Uncertain Programming. Studies in Fuzziness and Soft Computing, vol 102. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1781-2_12
Download citation
DOI: https://doi.org/10.1007/978-3-7908-1781-2_12
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-662-13196-1
Online ISBN: 978-3-7908-1781-2
eBook Packages: Springer Book Archive