Ezzati et al. (2013) proposed a method for comparing triangular fuzzy numbers and using it, propose a new algorithm to find the fuzzy optimal solution of fully fuzzy linear programming problems with equality constrain...
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Ezzati et al. (2013) proposed a method for comparing triangular fuzzy numbers and using it, propose a new algorithm to find the fuzzy optimal solution of fully fuzzy linear programming problems with equality constraints. Ezzati et al. also claimed that the fuzzy optimal solution of fully fuzzy linear programming problems with inequality constraints can also be obtained by the same algorithm by transforming it into fully fuzzy linear programming problems with equality constraints. In this note, it is proved that the fully fuzzy linear programming problems with inequality constraints cannot be transformed into fully fuzzy linear programming problems with equality constraints and hence, the algorithm, proposed by Ezzati et al. to find the fuzzy optimal solution of fully fuzzy linear programming problems with equality constraints, cannot be used for finding the fuzzy optimal solution of fully fuzzy linear programming problems with inequality constraints. (C) 2014 Elsevier Inc. All rights reserved.
In this paper, we use He's homotopy perturbation method (HPM) for solving linearprogramming ( LP) problems. By applying HPM for this class of problems, optimal solutions of a primal LP problem and its correspondi...
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In this paper, we use He's homotopy perturbation method (HPM) for solving linearprogramming ( LP) problems. By applying HPM for this class of problems, optimal solutions of a primal LP problem and its corresponding dual problem can be obtained at the same time. The efficiency of the method is shown by solving some examples.
There are several daily life problems where we have to deal with the uncertainties and we are forced to solve the uncertain linearprogramming models. Certain methods have been presented for dealing with linear progra...
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There are several daily life problems where we have to deal with the uncertainties and we are forced to solve the uncertain linearprogramming models. Certain methods have been presented for dealing with linear programming problems based on fuzzy sets and intuitionistic fuzzy sets which are characterized by membership degree, membership and non-membership degrees, respectively. In this study, we first extend the concept of crisp linear programming problem in Pythagorean fuzzy environment based on triangular Pythagorean fuzzy numbers. The profit/cost coefficients in objective function, input/output coefficients and right-hand side coefficients and decision variables of a linear programming problem are considered as triangular Pythagorean fuzzy numbers. Further, we present methods for solving fully Pythagorean fuzzy linear programming problems for non-negative and unrestricted triangular Pythagorean fuzzy numbers with equality constraints. We also apply the proposed technique to solve practical models.
The augmented Lagrangian and Newton methods are used to simultaneously solve the primal and dual linear programming problems. The proposed approach is applied to the primal linear programming problem with a very large...
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The augmented Lagrangian and Newton methods are used to simultaneously solve the primal and dual linear programming problems. The proposed approach is applied to the primal linear programming problem with a very large number (approximate to 10(6)) of nonnegative variables and a moderate (approximate to 10(3)) number of equality-type constraints. Computation results such as the solution of a linear programme with 10 million primal variables are presented.
Approximating a given continuous probability distribution of the data of a linear program by a discrete one yields solution methods for the stochastic linear programming problem with complete fixed recourse. For a pro...
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Approximating a given continuous probability distribution of the data of a linear program by a discrete one yields solution methods for the stochastic linear programming problem with complete fixed recourse. For a procedure along the lines of [8], the reduction of the computational amount of work compared to the usual revised simplex method is figured out. Furthermore, an alternative method is proposed, where by refining particular discrete distributions the optimal value is approximated.
Necessary and sufficient conditions for a linear programming problem whose parameters (both in constraints and in the objective function) are prescribed by intervals are given under which any linearprogramming proble...
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Necessary and sufficient conditions for a linear programming problem whose parameters (both in constraints and in the objective function) are prescribed by intervals are given under which any linear programming problem with parameters being fixed in these intervals has a finite optimum.
The augmented Lagrangian and Newton methods are used to simultaneously solve the primal and dual linear programming problems. The proposed approach is applied to the primal linear programming problem with a very large...
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The augmented Lagrangian and Newton methods are used to simultaneously solve the primal and dual linear programming problems. The proposed approach is applied to the primal linear programming problem with a very large number (approximate to 10(6)) of nonnegative variables and a moderate (approximate to 10(3)) number of equality-type constraints. Computation results such as the solution of a linear programme with 10 million primal variables are presented.
We consider a finite state-action discounted constrained Markov decision process with uncertain running costs and known transition probabilities. We propose equivalent linearprogramming, second-order cone programming...
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We consider a finite state-action discounted constrained Markov decision process with uncertain running costs and known transition probabilities. We propose equivalent linearprogramming, second-order cone programming and semidefinite programmingproblems for the robust constrained Markov decision processes when the uncertain running cost vectors belong to polytopic, ellipsoidal, and semidefinite cone uncertainty sets, respectively. As an application, we study a variant of a machine replacement problem and perform numerical experiments on randomly generated instances of various sizes. (C) 2022 Elsevier B.V. All rights reserved.
In this paper we consider two-person zero-sum games with fuzzy multiple payoff matrices. We assume that each player has a fuzzy goal for each of the payoffs. A degree of attainment of the fuzzy goal is defined and the...
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In this paper we consider two-person zero-sum games with fuzzy multiple payoff matrices. We assume that each player has a fuzzy goal for each of the payoffs. A degree of attainment of the fuzzy goal is defined and the max-min strategy with respect to the degree of attainment of the fuzzy goal is examined. If all of the membership functions both for the fuzzy payoffs and for the fuzzy goals are linear, the formulated mathematical programmingproblem which yields the max-min strategy can be reduced to the linear programming problem by making use of Sakawa's method, the variable transformations, and the relaxation procedure.
This study addresses the problem of synthesising functional observers for positive time-delay systems subjected to unknown inputs. A functional observer architecture for the problem is presented. The existence conditi...
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This study addresses the problem of synthesising functional observers for positive time-delay systems subjected to unknown inputs. A functional observer architecture for the problem is presented. The existence conditions of the observer and a linear programming problem characterising the existence conditions of such a functional observer are also established. An algorithm for designing the observer is presented. Finally, examples are given to showcase the effectiveness of the observer.
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