In this paper we introduce the latticized linear programming problem subject to max product fuzzy relation inequalities with application in the optimization management model of wireless communication emission base sta...
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In this paper we introduce the latticized linear programming problem subject to max product fuzzy relation inequalities with application in the optimization management model of wireless communication emission base stations. Resolution of max-product fuzzy relation inequalities is studied by comparing with that of the corresponding max-product fuzzy relation equations. A solution matrix approach is developed for solving the proposed problem without finding all the (quasi-) minimal solutions of the constraint. For carrying out the solution matrix approach, we provide a step-by-step algorithm illustrated by a numerical example. (C) 2016 Elsevier Inc. All rights reserved.
P2P network can be reduced into a system of fuzzy relation inequalities with addition-min composition. In this paper we introduce multi-variable-term latticized linear programming subject to this system. Firstly, we i...
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ISBN:
(纸本)9783319462066;9783319462059
P2P network can be reduced into a system of fuzzy relation inequalities with addition-min composition. In this paper we introduce multi-variable-term latticized linear programming subject to this system. Firstly, we introduce some properties on the minimal solution of the system. Next we define the minimal intervals of the system. Meanwhile, We prove that the optimal solution of the programming is the minimal solution of the system. Finally, we get algorithm for the programming by translating it into some linearprogramming problems with minimal intervals constraint. An example is given to show the efficiency and feasibility of the algorithm.
Recently, the latticized linear programming problems subjected to max-min and max-product fuzzy relational inequalities (FRI) have been studied extensively and have been utilized in many interesting applications. In t...
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Recently, the latticized linear programming problems subjected to max-min and max-product fuzzy relational inequalities (FRI) have been studied extensively and have been utilized in many interesting applications. In this paper, we introduce a new generalization of the latticized optimization problems whose objective is a non-linear function defined by an arbitrary continuous s-norm (t-conorm), and whose constraints are formed as an FRI defined by an arbitrary continuous t-norm. Firstly, the feasible region of the problem is completely characterized and two necessary and sufficient conditions are proposed to determine the feasibility of the problem. Also, a general method is proposed for finding the exact optimal solutions of the non-linear model. Then, to accelerate the general method, five simplification techniques are provided that reduce the work of computing an optimal solution. Additionally, a polynomial-time method is presented for solving general latticizedlinear optimization problems subjected to the continuous FRI. Moreover, an application of the proposed non-linear model is described where the objective function and the FRI are defined by the well-known Lukasiewicz s-norm and product t-norm, respectively. Finally, a numerical example is provided to illustrate the proposed algorithm.
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