On random fuzzy variables of second order and their application to linear statistical inference with fuzzy data

Metrika ◽  
2000 ◽  
Vol 51 (3) ◽  
pp. 201-221 ◽  
Author(s):  
Wolfgang Näther
Keyword(s):  
Statistical Inference ◽  
Second Order ◽  
Fuzzy Data ◽  
Fuzzy Variables ◽  
Linear Statistical Inference ◽  
Random Fuzzy Variables

Linear Statistical Inference and its Applications.

1967 ◽  
Vol 62 (317) ◽  
pp. 290 ◽  
Author(s):  
Bradley Efron ◽  
C. Radhakrishna Rao
Keyword(s):  
Statistical Inference ◽  
Linear Statistical Inference

Sensitivity Analysis on Linear Programming Problems with Trapezoidal Fuzzy Variables

2013 ◽  
pp. 64-82
Author(s):  
Seyed Hadi Nasseri ◽  
Ali Ebrahimnejad
Keyword(s):  
Linear Programming ◽  
Simplex Algorithm ◽  
Programming Models ◽  
Fuzzy Data ◽  
Fuzzy Variables ◽  
Fuzzy Environment ◽  
Dual Simplex ◽  
Linear Programming Problems ◽  
Simplex Tableau ◽  
Dual Simplex Algorithm

In the real word, there are many problems which have linear programming models and sometimes it is necessary to formulate these models with parameters of uncertainty. Many numbers from these problems are linear programming problems with fuzzy variables. Some authors considered these problems and have developed various methods for solving these problems. Recently, Mahdavi-Amiri and Nasseri (2007) considered linear programming problems with trapezoidal fuzzy data and/or variables and stated a fuzzy simplex algorithm to solve these problems. Moreover, they developed the duality results in fuzzy environment and presented a dual simplex algorithm for solving linear programming problems with trapezoidal fuzzy variables. Here, the authors show that this presented dual simplex algorithm directly using the primal simplex tableau algorithm tenders the capability for sensitivity (or post optimality) analysis using primal simplex tableaus.

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