In this paper, assuming cooperative behavior of the decision makers, two-level linear programming problems involving random variables in constraints are considered. Using the concept of simple recourse, the formulated...
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In this paper, assuming cooperative behavior of the decision makers, two-level linear programming problems involving random variables in constraints are considered. Using the concept of simple recourse, the formulated stochastic two-level simple recourse problems are transformed into deterministic two-levelprogramming ones. Taking into account vagueness of judgments of the decision makers, interactive fuzzy programming is presented. In the proposed interactive method, after determining the fuzzy goals of the decision makers at both levels, a satisfactory solution is derived efficiently by updating the satisfactory degree of the decision maker at the upper level with considerations of overall satisfactory balance between both levels. An illustrative numerical example is provided to demonstrate the feasibility and efficiency of the proposed method. (C) 2014 Elsevier Inc. All rights reserved.
In this article, assuming non-cooperative behaviour of the decision makers, solution methods for decision making problems in hierarchical organizations under fuzzy random environments are presented. Taking into accoun...
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In this article, assuming non-cooperative behaviour of the decision makers, solution methods for decision making problems in hierarchical organizations under fuzzy random environments are presented. Taking into account hte vagueness of judgments by decision makers, fuzzy goals are introduced into the formulated fuzzy random two-level linear programming problems. Considering the possibility and necessity measures that each objective function fulfils the corresponding fuzzy goal, the fuzzy random two-level linear programming problems to minimize each objective function with fuzzy random variables are transformed into stochastic two-levelprogramming problems to maximize the degree of possibility and necessity that each fuzzy goal is fulfilled. Through the fractile criterion optimization model, or Kataoka's model in stochastic programming, the transformed stochastic two-levelprogramming problems can be reduced to deterministic two-levelprogramming problems. For the transformed problems, extended concepts of Stackelberg solutions are introduced and computational methods are also presented. A numerical example is provided to illustrate the proposed methods.
This paper considers Stackelberg solutions for decision making problems in hierarchical organizations under fuzzy random environments. Taking into account vagueness of judgments of decision makers, fuzzy goals are int...
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This paper considers Stackelberg solutions for decision making problems in hierarchical organizations under fuzzy random environments. Taking into account vagueness of judgments of decision makers, fuzzy goals are introduced into the formulated fuzzy random two-level linear programming problems. On the basis of the possibility and necessity measures that each objective function fulfills the corresponding fuzzy goal, together with the introduction of probability maximization criterion in stochastic programming, we propose new two-level fuzzy random decision making models which maximize the probabilities that the degrees of possibility and necessity are greater than or equal to certain values. Through the proposed models, it is shown that the original two-level linear programming problems with fuzzy random variables can be transformed into deterministic two-levellinear fractional programming problems. For the transformed problems, extended concepts of Stackelberg solutions are defined and computational methods are also presented. A numerical example is provided to illustrate the proposed methods. (C) 2011 Elsevier B.V. All rights reserved.
This paper considers computational methods for obtaining Stackelberg solutions to random fuzzy two-level linear programming problems. Assuming that the decision makers concerns about the probabilities that their own o...
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This paper considers computational methods for obtaining Stackelberg solutions to random fuzzy two-level linear programming problems. Assuming that the decision makers concerns about the probabilities that their own objective function values are smaller than or equal to certain target values, fuzzy goals of the decision makers for the probabilities are introduced. Using the possibility-based probability model to maximize the degrees of possibility with respect to the attained probability, the original random fuzzy two-levelprogramming problems are reduced to deterministic ones. Extended concepts of Stackelberg solutions are introduced and computational methods are also presented. A numerical example is provided to illustrate the proposed method. (C) 2012 Elsevier Ltd. All rights reserved.
This paper considers Stackelberg solutions for two-level linear programming problems under fuzzy random environments. To deal with the formulated fuzzy random two-level linear programming problem, an alpha-stochastic ...
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This paper considers Stackelberg solutions for two-level linear programming problems under fuzzy random environments. To deal with the formulated fuzzy random two-level linear programming problem, an alpha-stochastic two-level linear programming problem is defined through the introduction of alpha-level sets of fuzzy random variables. Taking into account vagueness of judgments of decision makers, fuzzy goals are introduced and the alpha-stochastic two-level linear programming problem is transformed into the problem to maximize the satisfaction degree for each fuzzy goal. Through fractile criterion optimization in stochastic programming, the transformed stochastic two-levelprogramming problem can be reduced to a deterministic two-levelprogramming problem. An extended concept of Stackelberg solution is introduced and a numerical example is provided to illustrate the proposed method.
In this paper, we focus on two-level linear programming problems involving random variable coefficients in objective functions and constraints. According to the concept of chance constrained programming, the two-level...
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In this paper, we focus on two-level linear programming problems involving random variable coefficients in objective functions and constraints. According to the concept of chance constrained programming, the two-level stochastic linearprogramming problems are transformed into deterministic ones through the expectation optimization model and the variance minimization model. After introducing fuzzy goals for objective functions, interactive fuzzy programming to derive a satisfactory solution for decision makers is presented as a fusion of stochastic approach and fuzzy one. An illustrative numerical example is provided to demonstrate the feasibility of the proposed method.
The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Cons...
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ISBN:
(纸本)9780819469144
The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-levellinear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.
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