In this paper, a method is proposed for solving multi-objective linear fractional programming (MOLFP) problem. Here, the MOLFP problem is transformed into an equivalent multi-objective linearprogramming (MOLP) proble...
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ISBN:
(纸本)9788132216803;9788132216797
In this paper, a method is proposed for solving multi-objective linear fractional programming (MOLFP) problem. Here, the MOLFP problem is transformed into an equivalent multi-objective linearprogramming (MOLP) problem. Using the first-order Taylor's series approximation, the MOLFP problem is reduced to single-objective linearprogramming (LP) problem. Finally, the solution of MOLFP problem is obtained by solving the resultant LP problem. The proposed procedure is verified with the existing methods through the numerical examples.
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.
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.
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