Fuzzy primal simplex algorithms for solving fuzzy linear programming problems (original) (raw)
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Applied Mathematics, 2011
Two existing methods for solving a class of fuzzy linear programming (FLP) problems involving symmetric trapezoidal fuzzy numbers without converting them to crisp linear programming problems are the fuzzy primal simplex method proposed by Ganesan and Veeramani [1] and the fuzzy dual simplex method proposed by Ebrahimnejad and Nasseri . The former method is not applicable when a primal basic feasible solution is not easily at hand and the later method needs to an initial dual basic feasible solution. In this paper, we develop a novel approach namely the primal-dual simplex algorithm to overcome mentioned shortcomings. A numerical example is given to illustrate the proposed approach.
A Generalized Model for Fuzzy Linear Programs with Trapezoidal Fuzzy Numbers
2017
In this paper, we generalize a linear programming problem with symmetric trapezoidal fuzzy number which is introduced by Ganesan and et al. in [3] to a general kind of trapezoidal fuzzy number. In this way, we first establish a new arithmetic operation for multiplication of two trapezoidal fuzzy numbers. Then in order to preparing a method for solving the fuzzy linear programming as well as the primal simplex algorithm, we use a general linear ranking function as a convenient approach in the literature. In fact, our main contribution in this work is based on 3 items: 1) Extending the current fuzzy linear program to a general kind which is not essentially including the symmetric trapezoidal fuzzy numbers , 2) Defining a new multiplication role of two trapezoidal fuzzy numbers, 3) Establishing a fuzzy primal simplex algorithm for solving the generalized model. We in particular emphasize that this study can be used for establishing fuzzy dual simplex algorithm, fuzzy prima...
Revised simplex method and its application for solving fuzzy linear programming problems
2012
Linear programming models play an important role in management, economic, data envelopment analysis, operations research and many industrial applications. In many practical situations there is a kind of ambiguity in the parameters of these models which can be expressed by means of fuzzy numbers. In the literature of fuzzy mathematical programming there are many types of the fuzzy linear programming problems. But in this paper, we deal with a kind of linear programming which includes the triangular fuzzy numbers in its parameters. For finding the solution of these problems, we propose a revised simplex algorithm for an extended linear programming problem which is equivalent to the original fuzzy linear programming problem. An illustrative example is presented to clarify the proposed approach. A fuzzy DEA model has been also considered as a practical application to illustrate the effectiveness of the proposed approach.
Applied Mathematical Modelling, 2011
In a recent paper, Ganesan and Veermani [K. Ganesan, P. Veeramani, Fuzzy linear programs with trapezoidal fuzzy numbers, Ann. Oper. Res. 143 (2006) 305-315] considered a kind of linear programming involving symmetric trapezoidal fuzzy numbers without converting them to the crisp linear programming problems and then proved fuzzy analogues of some important theorems of linear programming that lead to a new method for solving fuzzy linear programming (FLP) problems. In this paper, we obtain some another new results for FLP problems. In fact, we show that if an FLP problem has a fuzzy feasible solution, it also has a fuzzy basic feasible solution and if an FLP problem has an optimal fuzzy solution, it has an optimal fuzzy basic solution too. We also prove that in the absence of degeneracy, the method proposed by Ganesan and Veermani stops in a finite number of iterations. Then, we propose a revised kind of their method that is more efficient and robust in practice. Finally, we give a new method to obtain an initial fuzzy basic feasible solution for solving FLP problems.
A novel method for solving linear programming problems with symmetric trapezoidal fuzzy numbers
Linear programming (LP) is a widely used optimization method for solving real-life problems because of its efficiency. Although precise data are fundamentally indispensable in conventional LP problems, the observed values of the data in real-life problems are often imprecise. Fuzzy sets theory has been extensively used to represent imprecise data in LP by formalizing the inaccuracies inherent in human decision-making. The fuzzy LP (FLP) models in the literature generally either incorporate the imprecisions related to the coefficients of the objective function, the values of the right-hand-side, and/or the elements of the coefficient matrix. We propose a new method for solving FLP problems in which the coefficients of the objective function and the values of the right-hand-side are represented by symmetric trapezoidal fuzzy numbers while the elements of the coefficient matrix are represented by real numbers. We convert the FLP problem into an equivalent crisp LP problem and solve the crisp problem with the standard primal simplex method. We show that the method proposed in this study is simpler and computationally more efficient than two competing FLP methods commonly used in the literature.
Fuzzy Big-M Method for Solving Fuzzy Linear Programs with Trapezoidal Fuzzy Numbers
International Journal of Research, 2013
The fuzzy primal simplex method [15] and the fuzzy dual simplex method [17] have been proposed to solve a kind of f uzzy linear programming (FLP) problems involving symmetric trap ezoidal fuzzy numbers. The fuzzy simplex method starts with a pri mal fuzzy basic feasible solution (FBFS) for FLP problem and moves to an optimal basis by walking truth sequence of exception of the optimal basis obtained in fuzzy primal simplex method don’t satis fy the optimality criteria for FLP problem. Also this method has no e fficient when a primal fuzzy basic FBFS is not at hand. The fuzzy d ual simplex method needs to an initial dual FBFS. Furthermore, th re exists a shortcoming in the fuzzy dual simplex method when t he dual feasibility or equivalently the primal optimality i s not at hand and in this case, the fuzzy dual simplex method can’t be u sed for solving FLP problem. In this paper, a fuzzy Big-M method is pro posed to solve these problems in which the primal FBFS is not read ily availabl...
Study of Fuzzy Integer Linear Programming Problems (IFLPP) and Simplex Method
International Journal of Scientific Research in Science and Technology, 2023
In this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming problems with triangular fuzzy numbers. A computational method for solving fully fuzzy linear programming problems (FFLPP) is proposed, based upon the new Ranking function. The proposed method is very easy to understand and to apply for fully fuzzy linear programming problems occurring in real life situations as compared to the existing methods. To illustrate the proposed method numerical examples are solved.
Fuzzy Sets and Systems, 2007
Linear programming problems with trapezoidal fuzzy variables (FVLP) have recently attracted some interest. Some methods have been developed for solving these problems by introducing and solving certain auxiliary problems. Here, we apply a linear ranking function to order trapezoidal fuzzy numbers. Then, we establish the dual problem of the linear programming problem with trapezoidal fuzzy variables and hence deduce some duality results. In particular, we prove that the auxiliary problem is indeed the dual of the FVLP problem. Having established the dual problem, the results will then follow as natural extensions of duality results for linear programming problems with crisp data. Finally, using the results, we develop a new dual algorithm for solving the FVLP problem directly, making use of the primal simplex tableau. This algorithm will be useful for sensitivity (or post optimality) analysis when using primal simplex tableaus.
Fuzzy linear programs with trapezoidal fuzzy numbers
2006
The objective of this paper is to deal with a kind of fuzzy linear programming problem involving symmetric trapezoidal fuzzy numbers. Some important and interesting results are obtained which in turn lead to a solution of fuzzy linear programming problems without converting them to crisp linear programming problems.
Optimization and Reoptimization in Fuzzy Linear Programming problems
Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology, 2013
Fuzzy Linear Programming models are quite frequent in practice. The dynamic nature of the real problems often requires reoptimize from the optimal solutions found, what may mean a significant consumption of time and funds. In this paper, in order to efficiently solve this problem, first the optimality conditions and the duality results for fully fuzzy linear programming problems (all parameters and variables are symmetric trapezoidal fuzzy numbers) are generalized. Then, one proposes a fuzzy dual simplex method for solving these problems without the need of converting them to conventional linear programming problems. The resulting algorithm is flexible and easy of applying. For the sake of illustration, finally, an easy example is solved.