scholarly journals Predicting the optimal solution in fuzzy linear programming problem

2021 ◽  
Vol 101 (1) ◽  
pp. 25-36
Author(s):  
S.M. Davoodi ◽  
◽  
N.A. Abdul Rahman ◽  
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Fuzzy Numbers ◽  
Fuzzy Variable ◽  
Optimal Solution ◽  
Fuzzy Linear Programming ◽  
Maximum Variation ◽  
Complicated Manner ◽  
Optimal Value ◽  
Variation Range

In this paper we try to define a percentage form of LR fuzzy numbers which is a useful form of fuzzy numbers and its’ arithmetics. So, we show how the maximum variation range of optimal value of fuzzy objective function can be predicted by using this form of fuzzy numbers. Since fuzzy problems are generally solved through a complicated manner, the purpose of this study is releasing a kind of prediction for the final solution in the way that the manager can access to an outlook to optimal solution (Z∗) without solving the problem. Finally, optimal value of fuzzy objective function on fuzzy linear programming is predicted when maximum variation range of fuzzy variable have been predetermined.

NEW IMPROVED METHOD FOR SOLVING THE FUZZY LINEAR PROGRAMMING PROBLEMS WITH VARIABLES GIVEN AS FUZZY NUMBERS

2021 ◽  
Vol 10 (12) ◽  
pp. 3699-3723
Author(s):  
L. Kané ◽  
M. Konaté ◽  
L. Diabaté ◽  
M. Diakité ◽  
H. Bado
Keyword(s):  
Linear Programming ◽  
Fuzzy Numbers ◽  
Optimal Solution ◽  
Fuzzy Linear Programming ◽  
Interval Linear Programming ◽  
Interval Numbers ◽  
Programming Technique ◽  
Solution Approach ◽  
Interval Linear ◽  
Linear Programming Problems

The present paper aims to propose an alternative solution approach in obtaining the fuzzy optimal solution to a fuzzy linear programming problem with variables given as fuzzy numbers with minimum uncertainty. In this paper, the fuzzy linear programming problems with variables given as fuzzy numbers is transformed into equivalent interval linear programming problems with variables given as interval numbers. The solutions to these interval linear programming problems with variables given as interval numbers are then obtained with the help of linear programming technique. A set of six random numerical examples has been solved using the proposed approach.

scholarly journals Comparing different ranking functions for solving fuzzy linear programming problems with fuzzy cost coefficients

2021 ◽  
Vol 4 (2) ◽  
pp. 3-17
Author(s):  
Betsabé Pérez Garrido ◽  
Szabolcs Szilárd Sebrek ◽  
Viktoriia Semenova
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Fuzzy Numbers ◽  
Fuzzy Linear Programming ◽  
Ranking Functions ◽  
Statistical Software ◽  
Linear Programming Problems ◽  
Fuzzy Cost ◽  
The Cost ◽  
Cost Vector

In many applications of linear programming, the lack of exact information results in various problems. Nevertheless, these types of problems can be handled using fuzzy linear programming. This study aims to compare different ranking functions for solving fuzzy linear programming problems in which the coefficients of the objective function (the cost vector) are fuzzy numbers. A numerical example is introduced from the field of tourism and then solved using five ranking functions. Computations were carried out using the FuzzyLP package implemented in the statistical software R.

scholarly journals A New Approach to Find an Optimal Solution of a Fuzzy Linear Programming Problem by Fuzzy Dynamic Programming

2018 ◽  
Vol 7 (4.10) ◽  
pp. 360
Author(s):  
T. Nagalakshmi ◽  
G. Uthra
Keyword(s):  
Dynamic Programming ◽  
Linear Programming ◽  
Objective Function ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Optimal Solution ◽  
Fuzzy Linear Programming ◽  
New Approach ◽  
The Cost ◽  
Recursive Equations

This paper mainly focuses on a new approach to find an optimal solution of a fuzzy linear programming problem with the help of Fuzzy Dynamic Programming. Linear programming deals with the optimization of a function of variables called an objective function, subject to a set of linear inequalities called constraints. The objective function may be maximizing the profit or minimizing the cost or any other measure of effectiveness subject to constraints imposed by supply, demand, storage capacity, etc., Moreover, it is known that fuzziness prevails in all fields. Hence, a general linear programming problem with fuzzy parameters is considered where the variables are taken as Triangular Fuzzy Numbers. The solution is obtained by the method of FDP by framing fuzzy forward and fuzzy backward recursive equations. It is observed that the solutions obtained by both the equations are the same. This approach is illustrated with a numerical example. This feature of the proposed approach eliminates the imprecision and fuzziness in LPP models. The application of Fuzzy set theory in the field of dynamic Programming is called Fuzzy Dynamic Programming. 

scholarly journals Solving a Fully Fuzzy Linear Programming Problem through Compromise Programming

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Haifang Cheng ◽  
Weilai Huang ◽  
Jianhu Cai
Keyword(s):  
Linear Programming ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Fuzzy Numbers ◽  
Equality Constraints ◽  
Compromise Programming ◽  
Fuzzy Linear Programming ◽  
Programming Approach ◽  
Optimal Value ◽  
Fuzzy Equality

In the current literatures, there are several models of fully fuzzy linear programming (FFLP) problems where all the parameters and variables were fuzzy numbers but the constraints were crisp equality or inequality. In this paper, an FFLP problem with fuzzy equality constraints is discussed, and a method for solving this FFLP problem is also proposed. We first transform the fuzzy equality constraints into the crisp inequality ones using the measure of the similarity, which is interpreted as the feasibility degree of constrains, and then transform the fuzzy objective into two crisp objectives by considering expected value and uncertainty of fuzzy objective. Since the feasibility degree of constrains is in conflict with the optimal value of objective function, we finally construct an auxiliary three-objective linear programming problem, which is solved through a compromise programming approach, to solve the initial FFLP problem. To illustrate the proposed method, two numerical examples are solved.

SIMULATION OBJECTIVES OF FUZZY LINEAR PROGRAMMING WITH AN α-LEVEL METHOD OF λ-CONTINUE

2019 ◽  
Vol 6 (2) ◽  
pp. 71-76
Author(s):  
Alevtina Jur'evna Shatalova ◽  
Konstantin Andreevich Lebedev Konstantin Andreevich
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Optimization Problems ◽  
Linear Optimization ◽  
Optimal Solution ◽  
Investment Project ◽  
Fuzzy Linear Programming ◽  
Distribution Law ◽  
Linear Optimization Problems ◽  
Level Method

The article describes an approach that allows to formally describe the arising uncertainties in linear optimization problems. The generalized parametric alpha-level method of lambda-continuation of the fuzzy linear programming problem is considered. The model offers two methods that take into account the expansion of the binary fuzzy ratio (“strong” and “weak”). After the condition is formed taking into account the incoming quantities in the form of fuzzy numbers (the objective function and the system of constraints), the optimal solution (the value of the objective function) for each alpha and lambda is calculated using the simplex method implemented in Mathcad. On its basis, a mathematical model is built that will take into account the random values of alpha and lambda with a uniform distribution law. The paper presents a description of the simulation study, which confirms the conclusions about the possibilities of the method. Using the proposed theory, the decision-maker receives more information showing the behavior of the system with small changes in the input parameters to make more informed conclusions about the choice of financing of an investment project. The developed method of simulation of fuzzy estimation can be applied to other economic models with the appropriate necessary modification, for example, to assess the creditworthiness of the enterprise.

scholarly journals A MOLP Method for Solving Fully Fuzzy Linear Programming withLRFuzzy Parameters

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xiao-Peng Yang ◽  
Xue-Gang Zhou ◽  
Bing-Yuan Cao ◽  
S. H. Nasseri
Keyword(s):  
Linear Programming ◽  
Solution Method ◽  
Fuzzy Numbers ◽  
Optimal Solution ◽  
Order Relation ◽  
Fuzzy Programming ◽  
Fuzzy Linear Programming ◽  
Programming Method ◽  
Multiobjective Linear Programming ◽  
Fuzzy Parameters

Kaur and Kumar, 2013, use Mehar’s method to solve a kind of fully fuzzy linear programming (FFLP) problems withLRfuzzy parameters. In this paper, a new kind of FFLP problems is introduced with a solution method proposed. The FFLP is converted into a multiobjective linear programming (MOLP) according to the order relation for comparing theLRflat fuzzy numbers. Besides, the classical fuzzy programming method is modified and then used to solve the MOLP problem. Based on the compromised optimal solution to the MOLP problem, the compromised optimal solution to the FFLP problem is obtained. At last, a numerical example is given to illustrate the feasibility of the proposed method.

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