Abstract
This chapter focuses on flexible optimization. Given that we are able to construct fuzzy relations from target values, fuzzy goals, and from fuzzy relation membership functions, we then have a fuzzy constraint set. The next step in the process is to translate a fuzzy constraint set into a real vector constraint set and to redefine the objective function as a maximization of set belonging. If there are crisp relations and constraints, these remain as part of the real-valued constraint set and augment the translated fuzzy constraint set. If all or part of the original (non-fuzzy goal) objective function is real-valued, then the maximization of set belonging is added to the real-valued objective just as one would do when one adds a new variable to the objective function and constraint for real-valued mathematical programming problems.
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
Corresponding author
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Lodwick, W.A., Thipwiwatpotjana, P. (2017). Flexible Optimization. In: Flexible and Generalized Uncertainty Optimization. Studies in Computational Intelligence, vol 696. Springer, Cham. https://doi.org/10.1007/978-3-319-51107-8_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-51107-8_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-51105-4
Online ISBN: 978-3-319-51107-8
eBook Packages: EngineeringEngineering (R0)