multi-level linear programming problem subject to addition-min fuzzy relation inequalities is introduced to characterize a kind of optimization models in BitTorrent-like Peer-to-Peer file sharing systems. Based on som...
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multi-level linear programming problem subject to addition-min fuzzy relation inequalities is introduced to characterize a kind of optimization models in BitTorrent-like Peer-to-Peer file sharing systems. Based on some theorems, which contribute to the resolution of the proposed problem, we develop a novel algorithm to find the unique optimal solution. A practical application example is presented to illustrate the feasibility and efficiency of the algorithm.
In this paper, we consider the multi-level linear programming subject to max-product fuzzy relation equations which is used to characterize a kind of wireless communication EBS model. Based on the theorem of lexicogra...
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ISBN:
(纸本)9783319665146;9783319665139
In this paper, we consider the multi-level linear programming subject to max-product fuzzy relation equations which is used to characterize a kind of wireless communication EBS model. Based on the theorem of lexicography order, we developed a algorithm to find the unique optimal solution. And a numerical example is given to illustrate the feasibility and efficiency of the algorithm.
The earlier Karush-Kuhn-Tucker (KKT) transformation method has been applied to multi-level decentralized programming problems (ML(D)PPs) when the decision variable set was divided into subsets where each decision make...
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The earlier Karush-Kuhn-Tucker (KKT) transformation method has been applied to multi-level decentralized programming problems (ML(D)PPs) when the decision variable set was divided into subsets where each decision maker (DM) of the system controlled only a particular subset but had no control over any decision variables of some other subset. In this paper we give the mathematical formulation and corresponding development of ML(D)PPs by KKT transformation when DMs have absolute control over certain decision variables but some variables may be shared and hence controlled by two or more DMs. (C) 2002 Elsevier Science B.V. All rights reserved.
In many real situations, it is frequently difficult to accurately determine the membership and non-membership degrees related to an element of the set with complete satisfaction because of the ambiguity in the input d...
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In many real situations, it is frequently difficult to accurately determine the membership and non-membership degrees related to an element of the set with complete satisfaction because of the ambiguity in the input data. In instances like these, intuitionistic fuzzy (IF) numbers are crucial. We present a simple approach in this paper to solve the fully intuitionistic fuzzy multi-levellinear fractional programming (FIFMLLFP) problem. By applying the new suggested approach to the problem under consideration, each level of the FIFMLLFP problem is converted into five crisp linear (MLMOLFP) problems, where each crisp problem has an additional bounded variables constraint and the upper problems' optimization variables are treated as parameters. This is done by using an iterative technique for linearizing fractional objectives. We converted the MLMOLFP problem into a multilevelmultiobjective linearprogramming (MLMOLP) problem, in addition to the & epsilon;-constraint method that is used to reduce MLMOLP problem to a single objective linearprogramming problem. The method is demonstrated stepby-step with a numerical example.
In this research, we use the harmonic mean technique to present an interactive strategy for addressing neutrosophic multi-levelmulti-objective linearprogramming (NMMLP) problems. The coefficients of the objective fu...
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In this research, we use the harmonic mean technique to present an interactive strategy for addressing neutrosophic multi-levelmulti-objective linearprogramming (NMMLP) problems. The coefficients of the objective functions of level decision makers and constraints are represented by neutrosophic numbers. By using the interval programming technique, the NMMLP problem is transformed into two crisp MMLP problems, one of these problems is an MMLP problem with all of its coefficients being upper approximations of neutrosophic numbers, while the other is an MMLP problem with all of its coefficients being lower approximations of neutrosophic numbers. The harmonic mean method is then used to combine the many objectives of each crisp problem into a single objective. Then, a preferred solution for NMMLP problems is obtained by solving the single-objective linearprogramming problem. An application of our research problem is how to determine the optimality the cost of multi-objective transportation problem with neutrosophic environment. To demonstrate the proposed strategies, numerical examples are solved.
This paper develops a two-phase fuzzy goal programming (FGP) approach for multi-level linear programming (MLLP) problems in an uncertain environment. A numerical MLLP model is established based on a confidence level. ...
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This paper develops a two-phase fuzzy goal programming (FGP) approach for multi-level linear programming (MLLP) problems in an uncertain environment. A numerical MLLP model is established based on a confidence level. In the first phase, an FGP model is used to find a solution that reaches the overall satisfaction of all decision-makers (DMs), ensuring that the fuzzy goal of each higher-level DM is more satisfied than those of lower-level DMs. Since the higher-level DM has the direct authority to manage the subordinate DM, an adjustment scheme is provided in the second phase for each higher-level DM, who has the opportunity to increase or decrease the satisfaction degree of their fuzzy goal by changing the relative satisfaction of the lower-level DM compared to that of their higher-level DM. A fuzzy variable of the relative satisfaction containing a set of linguistic terms is provided for these adjustments. The adjustment processes are carried out sequentially, from the top to bottom in the hierarchical decision structure. The proposed FGP model in the second phase considers these sequential adjustments. A numerical example and comparisons with existing methods are used to demonstrate the applicability and performance of the proposed approach. (C) 2014 Elsevier B.V. All rights reserved.
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