Solving a full fuzzy linear programming using lexicography method and fuzzy approximate solution

This paper discusses full fuzzy linear programming (FFLP) problems of which all parameters and variable are triangular fuzzy numbers. We use the concept of the symmetric triangular fuzzy number and introduce an approach to defuzzify a general fuzzy quantity. For such a problem, first, the fuzzy triangular number is approximated to its nearest symmetric triangular number, with the assumption that all decision variables are symmetric triangular. An optimal solution to the above-mentioned problem is a symmetric fuzzy solution. Every FLP models turned into two crisp complex linear problems; first a problem is designed in which the center objective value will be calculated and since the center of a fuzzy number is preferred to (its) margin. With a special ranking on fuzzy numbers, the FFLP transform to multi objective linear programming (MOLP) where all variables and parameters are crisp.     

On the nearest parametric approximation of a fuzzy number—Revisited

The problem of finding the nearest parametric approximation of a fuzzy number with respect to the average Euclidean distance is completely solved. Properties of translation invariance, scale invariance, additivity, preservation of expected value, value and ambiguity of this new approximation operator are studied and an algorithm for computing it is provided.     

Optimal stopping under ambiguity in continuous time

We develop a theory of optimal stopping problems under ambiguity in continuous time. Using results from (backward) stochastic calculus, we characterize the value function as the smallest (nonlinear) supermartingale dominating the payoff process. For Markovian models, we derive an adjusted Hamilton–Jacobi–Bellman equation involving a nonlinear drift term that stems from the agent’s ambiguity aversion. We show how to use these general results for search problems and American options.     

On the Calculus of Limiting Subjets on Riemannian Manifolds

In this paper fuzzy calculus rules for subjets of order two on finite dimensional Riemannian manifolds are obtained. Then a second order singular subjet derived from a sequence of efficient subsets of symmetric matrices is introduced. Employing fuzzy calculus rules for subjets of order two and various qualification assumptions based on a second order singular subjet, calculus rules for limiting subjets on a finite dimensional Riemannian manifold are obtianed.     

Metric properties of the nearest extended parametric fuzzy number and applications

We propose the notion of extended parametric fuzzy number, which generalizes the extended trapezoidal fuzzy number and parametric fuzzy number, discussed in some recent papers. The metric properties of the nearest extended parametric fuzzy number of a fuzzy number, proved in the present article, help us to obtain the property of continuity for the parametric approximation operator and to simplify the solving of the problems of parametric approximations under conditions.     

Intuitionistic fuzzy linear regression analysis

Linear regression analysis in an intuitionistic fuzzy environment using intuitionistic fuzzy linear models with symmetric triangular intuitionistic fuzzy number (STriIFN) coefficients is introduced. The goal of this regression is to find the coefficients of a proposed model for all given input–output data sets. The coefficients of an intuitionistic fuzzy regression (IFR) model are found by solving a linear programming problem (LPP). The objective function of the LPP is to minimize the total fuzziness of the IFR model which is related to the width of IF coefficients. An illustrative example is also presented to depict the solution procedure of the IFR problem by using STriIFNs.     

Forecasting portfolio returns using weighted fuzzy time series methods

We propose using weighted fuzzy time series (FTS) methods to forecast the future performance of returns on portfolios. We model the uncertain parameters of the fuzzy portfolio selection models using a possibilistic interval-valued mean approach, and approximate the uncertain future return on a given portfolio by means of a trapezoidal fuzzy number. Introducing some modifications into the classical models of fuzzy time series, based on weighted operators, enables us to generate trapezoidal numbers as forecasts of the future performance of the portfolio returns. This fuzzy forecast makes it possible to approximate both the expected return and the risk of the investment through the value and ambiguity of a fuzzy number.We incorporate our proposals into classical fuzzy time series methods and analyze their effectiveness compared with classical weighted fuzzy time series models, using historical returns on assets from the Spanish stock market. When our weighted FTS proposals are used to point-wise forecast portfolio returns the one-step ahead accuracy is improved, also with respect to non-fuzzy forecasting methods.     

定义在复数上的复模糊值函数

把所有的关于y轴对称的模糊数都定义为零模糊数,则两个相同的模糊数的差为零,利用~ar-+~ar+这样一个数值来描述模糊数的序关系,就可以得到关于纵向对称的模糊数都是等同的.在此基础之上对实模糊数的模糊距离及极限进行了研究.并研究了复模糊数的距离与复模糊数列的极限以及复模糊值函数的极限.将研究的复模糊值函数是定义在复数集C上取值于F(C)(所有的复模糊数的集合)中的复模糊数的函数.在新的序关系意义下讨论复模糊值函数的极限,并讨论复模糊值函数的收敛性质及Cauchy收敛判别法等.     

Narayana polynomials and Hall–Littlewood symmetric functions

We show that Narayana polynomials are a specialization of row Hall–Littlewood symmetric functions. Using λ-ring calculus, we generalize to Narayana polynomials the formulas of Koshy and Jonah for Catalan numbers.     

Some new results in linear programs with trapezoidal fuzzy numbers: Finite convergence of the Ganesan and Veeramani’s method and a fuzzy revised simplex method

In a recent paper, Ganesan and Veermani [K. Ganesan, P. Veeramani, Fuzzy linear programs with trapezoidal fuzzy numbers, Ann. Oper. Res. 143 (2006) 305–315] considered a kind of linear programming involving symmetric trapezoidal fuzzy numbers without converting them to the crisp linear programming problems and then proved fuzzy analogues of some important theorems of linear programming that lead to a new method for solving fuzzy linear programming (FLP) problems. In this paper, we obtain some another new results for FLP problems. In fact, we show that if an FLP problem has a fuzzy feasible solution, it also has a fuzzy basic feasible solution and if an FLP problem has an optimal fuzzy solution, it has an optimal fuzzy basic solution too. We also prove that in the absence of degeneracy, the method proposed by Ganesan and Veermani stops in a finite number of iterations. Then, we propose a revised kind of their method that is more efficient and robust in practice. Finally, we give a new method to obtain an initial fuzzy basic feasible solution for solving FLP problems.     

Comments on some versions of intuitionistic fuzzy propositional calculus due to K. Atanassov and G. Gargov

We show that the versions of intuitionistic fuzzy propositional calculus given in Definitions 6 and 7 in Atanassov and Gargov (Fuzzy Sets and Systems 95 (1998) 39–52) do not satisfy modus ponens. Furthermore, we show that the version of intuitionistic fuzzy propositional calculus given in Definition 8 by Atanassov and Gargov is incorrect.     

Approximation of fuzzy numbers by trapezoidal fuzzy numbers preserving the expected interval

The problem to find the nearest trapezoidal approximation of a fuzzy number with respect to a well-known metric, which preserves the expected interval of the fuzzy number, is completely solved. The previously proposed approximation operators are improved so as to always obtain a trapezoidal fuzzy number. Properties of this new trapezoidal approximation operator are studied.     

The possibilistic moments of fuzzy numbers and their applications

This paper, introduces the nearest weighted interval and point approximations of a fuzzy number, and then suggests weighted possibilistic moments about these points of fuzzy numbers. The possibilistic moments play an important role in fuzzy sets and systems, specifically in physics, mathematics and statistics. We provide the definition of the moments of fuzzy numbers as well as the definition of moments in probability theory; some of their applications are mentioned.     

基于因果聚类的模糊预测的择近选择

本文给出了对称三角模糊数的 Hausdauff度量的简明表示形式 ,从而解决了基于因果聚类的模糊预测的择近选择问题 .     

Limit properties and derivative operations in the metric space of intuitionistic fuzzy numbers

Intuitionistic fuzzy numbers (IFNs) are a useful tool to depict the uncertain information in real life. Based on IFNs, the intuitionistic fuzzy calculus (IFC) has been put forward recently. To further develop the IFC theory, in this paper, we investigate the limit properties of IFCs, and study the intuitionistic fuzzy infinitesimals and their orders. We also discuss the continuity, the derivatives and the differentials of intuitionistic fuzzy functions in detail, and reveal their relationships. Additionally, we define the metric space of the IFNs, based on which, a series of desirable results are obtained. These results are similar to the ones in the classical calculus.     

A fuzzy language

With the aim of designing and implementing programming languages that take into account the fuzzy paradigm we will modify the classical lambda calculus by adding a degree to each term and by redefining the b-reduction. Thus, for the new calculus to verify the Church–Rosser property, the degree computed with can be made through a function that is a t-norm or an s-conorm. With this new tool we design a nondeterminist language that satisfies fuzzy data programming requirements, and an example of its behaviour is shown.     

On standard models of fuzzy region connection calculus

The Region Connection Calculus (RCC) is perhaps the most influential topological relation calculus. Based on the first-order logic, the RCC, however, does not fully meet the needs of applications where the vagueness of entities or relations is important and not ignorable. This paper introduces standard models for the fuzzy region connection calculus (RCC) proposed by Schockaert et al. (2008) [18]. Each of such a standard fuzzy RCC model is induced by a standard RCC model in a natural way. We prove that each standard fuzzy RCC model is canonical in the sense that any satisfiable set of fuzzy RCC8 constraints have a solution in it. A polynomial realization algorithm is also provided. As a side product, we show similar sets of fuzzy constraints have similar solutions if both are satisfiable. This allows us to approximate fuzzy RCC constraints that have arbitrary bounds by those have bounds with finite precision.     

基于结构元的模糊值函数的一般表示方法

文[1]提出了模糊结构元的概念,并给出了模糊数与模糊值函数的模糊结构元表示,以及一类由模糊结构元线性生成的模糊值函数的微分和积分(黎曼意义下的)的表达形式。本文在文[1]的基础上进一步给出了由模糊结构元生成的模糊值函数的一般表达形式,并得到了一般表达形式下的模糊值函数的连续性和微分、黎曼积分的定义,它们与传统模糊分析中相应定义是等价的。     

Nonsmooth analysis on smooth manifolds

We study infinitesimal properties of nonsmooth (nondifferentiable) functions on smooth manifolds. The eigenvalue function of a matrix on the manifold of symmetric matrices gives a natural example of such a nonsmooth function.

A subdifferential calculus for lower semicontinuous functions is developed here for studying constrained optimization problems, nonclassical problems of calculus of variations, and generalized solutions of first-order partial differential equations on manifolds. We also establish criteria for monotonicity and invariance of functions and sets with respect to solutions of differential inclusions.

     

The middle-parametric representation of fuzzy numbers and applications to fuzzy interpolation

In this paper we introduce the middle-parametric representation of a fuzzy number presenting some of the advantages in the use of this representation. A special attention is focused on the subset of symmetric fuzzy numbers presenting the special properties of their arithmetic. The approach on symmetric fuzzy numbers is sustained by the applications of these kinds of fuzzy numbers in fuzzy linear programming and by the presence of the symmetric Gaussian type fuzzy numbers in the theory of errors. As potential applications of the middle-parametric representation, some fuzzy interpolation problems are considered.