In this paper, we propose an interactive fuzzy programming for two-level nonconvex nonlinear problems based on the use of genetic algorithms that have demonstrated their efficiency in solving the nonconvex nonlinear o...
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In this paper, we propose an interactive fuzzy programming for two-level nonconvex nonlinear problems based on the use of genetic algorithms that have demonstrated their efficiency in solving the nonconvex nonlinear optimization problems. Genetic algorithms have also recently become a widely accepted method for handling optimization, adaptation, and learning. According to the proposed method, fuzzy goals for the objective functions of decision makers at each level are stipulated, after which the decision maker at the upper level subjectively sets the minimum acceptable level of the satisfaction degrees, while considering the ratio of degrees of satisfaction between the levels, and interactively updates, if necessary, the minimum acceptable levels of the decision makers to efficiently obtain a satisfactory solution by establishing a balance of satisfaction degrees between the levels while respecting the motivations of the upper-level decision maker. Finally, we demonstrate the adequacy and efficiency of the proposed method for the solution of two-level nonconvex nonlinear programming problems using a numerical example. (C) 2000 Scripta Technica.
In this paper, we propose interactive fuzzy programming for multi-level 0-1 programming problems with fuzzy parameters through genetic algorithms. Our method can be applied to hierarchical decision problems in which d...
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In this paper, we propose interactive fuzzy programming for multi-level 0-1 programming problems with fuzzy parameters through genetic algorithms. Our method can be applied to hierarchical decision problems in which decision makers have their own objective functions but they can coordinate their decisions, that is, they are essentially cooperative. After determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. An illustrative numerical example for a three-level 0-1 programming problem is provided to demonstrate the feasibility of the proposed method. (C) 2001 Elsevier Science B.V. All rights reserved.
For decision making problems involving uncertainty, both stochastic programming as an optimization method based on the theory of probability and fuzzy programming representing the ambiguity by fuzzy concept have been ...
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For decision making problems involving uncertainty, both stochastic programming as an optimization method based on the theory of probability and fuzzy programming representing the ambiguity by fuzzy concept have been developing in various,ways. In this paper, we focus on multiobjective linear programming problems with random variable coefficients in objective functions and/or constraints. For such problems, as a fusion of these two approaches, after incorporating fuzzy goals of the decision maker for the objective functions, we propose an interactive fuzzy satisficing method for the expectation model to derive a satisficing solution for the decision maker. An illustrative numerical example is provided to demonstrate the feasibility of the proposed method. (C) 2002 Elsevier Science B.V. All rights reserved.
This paper presents a goal programming (GP) procedure for fuzzy multiobjective linear fractional programming (FMOLFP) problems. In the proposed approach, which is motivated by Mohamed (fuzzy Sets and Systems 89 (1997)...
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This paper presents a goal programming (GP) procedure for fuzzy multiobjective linear fractional programming (FMOLFP) problems. In the proposed approach, which is motivated by Mohamed (fuzzy Sets and Systems 89 (1997) 215), GP model for achievement of the highest membership value of each of fuzzy goals defined for the fractional objectives is formulated. In the solution process, the method of variable change on the under- and over-deviational variables of the membership goals associated with the fuzzy goals of the model is introduced to solve the problem efficiently by using linear goal programming (LGP) methodology. The approach is illustrated by two numerical examples. (C) 2002 Elsevier B.V. All rights reserved.
Two novel fuzzy optimization algorithms were proposed to solve one class of fuzzy programming problem with fuzzy coefficients for production scheduling. Unsatisfying function was adopted to replace membership function...
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Two novel fuzzy optimization algorithms were proposed to solve one class of fuzzy programming problem with fuzzy coefficients for production scheduling. Unsatisfying function was adopted to replace membership function, and genetic algorithm was developed, in which the initial population was generated through the hierarchical structure and fuzzy information was incorporated. By the proposed approaches, higher efficiency and better solutions comparing with other fuzzy algorithms is obtained. Finally, the validity of the algorithms is demonstrated by a numerical example on one production scheduling problem.
The paper focuses on the construction of supportvector machines when the outputs of training points are trianglefuzzy *** we transform fuzzy classification problemto chance constrained programming with fuzzy decision,...
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The paper focuses on the construction of supportvector machines when the outputs of training points are trianglefuzzy *** we transform fuzzy classification problemto chance constrained programming with fuzzy decision,andsolve this programming using fuzzy simulation basedevolutionary *** on this,we proposed the fuzzyLinear Support Vector Machines(FLSVM).It can deal withclassification problem with fuzzy information *** the end,the definition of fuzzy support vector set is given,which candeclare the characters of FLSVM.
Portfolio selection is a usual multiobjective problem. This paper will try to deal with the optimum portfolio for a private investor, taking into account three criteria: return, risk and liquidity. These objectives, i...
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Portfolio selection is a usual multiobjective problem. This paper will try to deal with the optimum portfolio for a private investor, taking into account three criteria: return, risk and liquidity. These objectives, in general, are not crisp from the point of view of the investor, so we will deal with them in fuzzy terms. The problem formulation is a goal programming (G.P.) one, where the goals and the constraints are fuzzy. We will apply a fuzzy G.P. approach to the above problem to obtain a solution. Then, we will offer the investor help in handling the results. (C) 2001 Elsevier Science B.V. All rights reserved.
In this paper we propose a fuzzy extension of the analytic network process (ANP) that uses uncertain human preferences as input information in the decision-making process. Instead of the classical Eigenvector prioriti...
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In this paper we propose a fuzzy extension of the analytic network process (ANP) that uses uncertain human preferences as input information in the decision-making process. Instead of the classical Eigenvector prioritization method, employed in the prioritization stage of the ANP, a new fuzzy preference programming method, which obtains crisp priorities from inconsistent interval and fuzzy judgments is applied. The resulting fuzzy ANP enhances the potential of the ANP for dealing with imprecise and uncertain human comparison judgments. It allows for multiple representations of uncertain human preferences, as crisp, interval, and fuzzy judgments and can find a solution from incomplete sets of pairwise comparisons. An important feature of the proposed method is that it measures the inconsistency of the uncertain human preferences by an appropriate consistency index. A prototype decision support system realizing the proposed method is developed, and its performance is illustrated by examples.
The credibility measure of fuzzy event is a relatively new concept related to fuzzy variable. This paper aims at demonstrating how this concept can be used for managing fuzzy scheduling on flow-shop problems. Three ty...
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ISBN:
(纸本)0780378105
The credibility measure of fuzzy event is a relatively new concept related to fuzzy variable. This paper aims at demonstrating how this concept can be used for managing fuzzy scheduling on flow-shop problems. Three types of fuzzy flow-shop scheduling models are presented. A hybrid intelligent algorithm is then designed to solve the proposed fuzzy flow-shop scheduling models. Computation experiments are provided to illustrate its effectiveness.
The objective of this paper is to propose an alternative approach that can be directly used by marketers in order to evaluate an offer with or without the involvement of potential customers. In order to deal with such...
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ISBN:
(纸本)0780379527
The objective of this paper is to propose an alternative approach that can be directly used by marketers in order to evaluate an offer with or without the involvement of potential customers. In order to deal with such an uncertain multi-criteria evaluation problem, a modification of the Analytic Hierarchy Process (AHP) is proposed, based on a fuzzy Preference programming method. This method takes into account customer's uncertain or irrational behavior by dealing with inconsistencies and derives crisp priorities from inconsistent interval pairwise comparison matrices. It is based on interval representations of the comparison judgments, as the prioritization problem is formulated as a fuzzy programming problem for obtaining an optimal crisp priority vector that maximizes the overall degree of satisfaction of the decision-maker.
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