scholarly journals A Problem Solving Perspective on Evaluating Knowledge Management Technologies: Using Fuzzy Linear Programming Technique for Multiattribute Group Decision Making with Fuzzy Decision Variables

2006 ◽  
Author(s):  
Yasemin Erensal ◽  
Y. Albayrak
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Knowledge Management ◽  
Problem Solving ◽  
Group Decision ◽  
Fuzzy Linear Programming ◽  
Fuzzy Decision ◽  
Programming Technique ◽  
Decision Variables ◽  
Linear Programming Technique

FUZZY LINMAP METHOD FOR MULTIATTRIBUTE GROUP DECISION MAKING WITH LINGUISTIC VARIABLES AND INCOMPLETE INFORMATION

2007 ◽  
Vol 15 (02) ◽  
pp. 153-173 ◽  
Author(s):  
DENG-FENG LI ◽  
TAO SUN
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Group Decision Making ◽  
Group Decision ◽  
Programming Model ◽  
Implementation Process ◽  
Fuzzy Linear Programming ◽  
Multidimensional Analysis ◽  
Linguistic Variables ◽  
Programming Technique

The aim of this paper is to develop a fuzzy linear programming technique for multidimensional analysis of preference (FLINMAP) in multiattribute group decision making problems with linguistic variables and incomplete preference information. In this paper, linguistic variables are used to assess an alternative on qualitative attributes using fuzzy ratings corresponding to some triangular fuzzy numbers. Each alternative is assessed on the basis of its distance to a fuzzy positive ideal solution (FPIS) which is unknown a priori. The FPIS and the weights of attributes are calculated by constructing a new linear programming model based on the group consistency and inconsistency indices defined on the basis of preferences between alternatives given by the decision makers. The distance of each alternative to the FPIS can be calculated to determine the ranking order of all alternatives. The implementation process of this methodology is demonstrated with an example.

scholarly journals Measuring the technical efficiency of local banks in UAE using rough bi-level linear programming technique

2015 ◽  
Vol 1 (1) ◽  
pp. 26
Author(s):  
Doaa Wafik ◽  
O. E. Emam
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Technical Efficiency ◽  
Auxiliary Problem ◽  
Optimal Solution ◽  
Objective Functions ◽  
Programming Technique ◽  
Decision Making Problem ◽  
Linear Objective Functions ◽  
Linear Programming Technique

The aim of this paper is to use a bi-level linear programming technique with rough parameters in the constraints, for measuring the technical efficiency of local banks in UAE and Egypt, while the proposed linear objective functions will be maximized for different goals. Based on Dauer's and Krueger's goal programmingmethod, the described approach was developed to deal with the bi-level decision-making problem. The concept of tolerance membership function together was used to generate the optimal solution for the problem under investigation. Also an auxiliary problem is discussed to illustrate the functionality of the proposed approach.

scholarly journals Solving Fuzzy Linear Programming Problems with Fuzzy Decision Variables

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 569
Author(s):  
Wu
Keyword(s):  
Linear Programming ◽  
Numerical Method ◽  
Fuzzy Numbers ◽  
Fuzzy Linear Programming ◽  
Optimal Solutions ◽  
Membership Functions ◽  
Fuzzy Decision ◽  
Existence Of Optimal Solutions ◽  
Decision Variables ◽  
Linear Programming Problems

The numerical method for solving the fuzzy linear programming problems with fuzzydecision variables is proposed in this paper. The difficulty for solving this kind of problem is thatthe decision variables are assumed to be nonnegative fuzzy numbers instead of nonnegative realnumbers. In other words, the decision variables are assumed to be membership functions. One of thepurposes of this paper is to derive the analytic formula of error estimation regarding the approximateoptimal solution. On the other hand, the existence of optimal solutions is also studied in this paper.Finally we present two numerical examples to demonstrate the usefulness of the numerical method.

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