In this paper, the concept of possibility is further considered, fuzzy optimal value of the linear programming with fuzzy numbers is given, and the continuity theorems of optimal value in parametric linear programming...
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In this paper, the concept of possibility is further considered, fuzzy optimal value of the linear programming with fuzzy numbers is given, and the continuity theorems of optimal value in parametric linear programming are proposed.
In this paper fuzzy programming technique is used to solve a multi-objective geometric programming problem as a vector minimum problem. A fuzzy membership function is defined for the multi-objective geometric programm...
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In this paper fuzzy programming technique is used to solve a multi-objective geometric programming problem as a vector minimum problem. A fuzzy membership function is defined for the multi-objective geometric programming problem. Two numerical examples are presented to illustrate the method.
Methods for solving possibilistic linear programming problems in the class of upper-semicontinuous quasiconcave distributions which model the sets of possible values of their parameters are examined. The connection be...
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Methods for solving possibilistic linear programming problems in the class of upper-semicontinuous quasiconcave distributions which model the sets of possible values of their parameters are examined. The connection between possibilistic and interval linear programming is established.
Linear programming with fuzzy random variable coefficients is introduced by discussing a practical engineering problem. In order to study the solution of the linear programming with fuzzy random variable coefficients,...
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Linear programming with fuzzy random variable coefficients is introduced by discussing a practical engineering problem. In order to study the solution of the linear programming with fuzzy random variable coefficients, we discuss the simplex algorithm for linear programming with random variable coefficients. Furthermore, the solution and distribution problem of this new fuzzy random programming are studied.
This paper studies the solution method and distribution problems for two kinds of linear programming with fuzzy random variable coefficients. Some concepts of solutions (for example, the fuzzy (pseudo-) random optimiz...
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This paper studies the solution method and distribution problems for two kinds of linear programming with fuzzy random variable coefficients. Some concepts of solutions (for example, the fuzzy (pseudo-) random optimization solution) are introduced for these new programming problems. We prove some equivalent theorems that transform the fuzzy random programming problems into a series of random programming problems. By using the simplex method of linear programming with random variable coefficients, we give the solution method of linear programming with fuzzy random variable coefficients. The formulas of probability distribution function, projective distribution function and expectation on these new programmings are presented.
This paper deals with a fuzzy programming language, used in implementation of fuzzy intelligent systems. Borrowing from both high- and low-order languages, HALO (High A- nd Low Order) integrates the symbolic programmi...
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This paper deals with a fuzzy programming language, used in implementation of fuzzy intelligent systems. Borrowing from both high- and low-order languages, HALO (High A- nd Low Order) integrates the symbolic programming and order-independent structure of expert systems with the control structures and procedural abstraction of Pascal. The HALO language is based on possibility theory and consequently, is well-suited to expert system development. HALO, probably best described as a 'fuzzy Pascal', is simple to learn and use yet is powerful enough for complex artificial intelligence applications requiring structure, modularity, process control, and uncertainty management.
Zimmermann's fuzzy approach to the compromise solution concept in the multi-objective linear programming problem is considered. It is shown that given a class of membership functions of fuzzy goals assigned to obj...
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Zimmermann's fuzzy approach to the compromise solution concept in the multi-objective linear programming problem is considered. It is shown that given a class of membership functions of fuzzy goals assigned to objective functions in the problem, wider than primarily proposed by Zimmermann, the use of classical linear programming methods to solve and analyse the problem is also possible. As a result of application of the method based on the parametric programming technique, one can obtain a fuzzy solution of the problem. This solution is a certain fuzzy subset of the set of weakly efficient solutions of the problem. The solution which belongs to this set to the highest degree is a maximizing one (in Bellman and Zadeh's terminology). It may also be obtained by use of the usual non-parametric simplex method.
The multifactorial function is a very important new concept which can be used to many aspects in fuzzy sets theory. It appeared firstly in [5] where it was used to define fuzzy perturbation function and where the stab...
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The multifactorial function is a very important new concept which can be used to many aspects in fuzzy sets theory. It appeared firstly in [5] where it was used to define fuzzy perturbation function and where the stability for the solutions of fuzzy relation equations by using fuzzy perturbation was studied. In [6], by means of multifactorial functions, multifactorial fuzzy sets and the multifactorial degree of nearness, which are two new concepts too, were given, and they were used to multifactorial pattern recognition and clustering analysis with fuzzy characteristics. In fact, generally speaking, most of the mathematical models dependent on several factors should use multifactorial functions. Especially, fuzzy decision-making, fuzzy games, fuzzy programming and fuzzy linear programming with several objective functions should. Here we study properties of multifactorial functions, how to generate a new multifactorial function, and we introduce in detail its applications in fuzzy pattern recognition, fuzzy decision-making, fuzzy clustering, fuzzy games and fuzzy programming, etc.
The multicriterial compromise problem is tackled by a fuzzy linear programming construct based on given aspirations. The aspiration vector is interpreted as a managerially relevant profile in objective space. The key ...
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The multicriterial compromise problem is tackled by a fuzzy linear programming construct based on given aspirations. The aspiration vector is interpreted as a managerially relevant profile in objective space. The key issue is to find an efficient compromise which corresponds to the aspiration profile as closely as possible. [ABSTRACT FROM AUTHOR]
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