Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

This paper considers linear programming problems (LPPs) where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables). New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and...

Full description

Bibliographic Details
Main Authors: Hideki Katagiri, Kosuke Kato, Takeshi Uno
Format: Article
Language:English
Published: MDPI AG 2017-10-01
Series:Symmetry
Subjects:
discrete fuzzy random variable
linear programming
possibility measure
necessity measure
expectation model
Pareto optimal solution
Online Access:https://www.mdpi.com/2073-8994/9/11/254

Internet

https://www.mdpi.com/2073-8994/9/11/254

Similar Items