Editorial

Linear programming problems with fuzzy parameters are formulated by fuzzy functions. The ambiguity considered here is not randomness, but fuzziness which is associated with the lack of a sharp transition from membership to nonmembership. Parameters on constraint and objective functions are given by fuzzy numbers. In this paper, our object is the formulation of a fuzzy linear programming problem to obtain a reasonable solution under consideration of the ambiguity of parameters. This fuzzy linear programming problem with fuzzy numbers can be regarded as a model of decision problems where human estimation is influential.     

On the calculation of a membership function for the solution of a fuzzy linear optimization problem

In the present paper the fuzzy linear optimization problem (with fuzzy coefficients in the objective function) is considered. Recent concepts of fuzzy solution to the fuzzy optimization problem based on the level-cut and the set of Pareto optimal solutions of a multiobjective optimization problem are applied. Chanas and Kuchta suggested one approach to determine the membership function values of fuzzy optimal solutions of the fuzzy optimization problem, which is based on calculating the sum of lengths of certain intervals. The purpose of this paper is to determine a method for realizing this idea. We derive explicit formulas for the bounds of these intervals in the case of triangular fuzzy numbers and show that only one interval needs to be considered.     

Similarities in Fuzzy Regression Models

The solutions of a fuzzy regression model are obtained by converting the problem into a linear programming problem. For each level h, h[0, 1), there exists a solution. In this paper, we study the set of all the solutions to the fuzzy regression model that comes from a set of data as a metric space with an appropriate metric on it. We define a similarity ratio that allows us to compare the spaces of solutions of a fuzzy regression model that come from different sets of data. We also give an application using data sets concerning the GNP–money relationship.     

全系数模糊型线性规划的偏差法

讨论并研究了全系数模糊型线性规划问题的一种新的求解方法.利用新定义的模糊数序关系以及考虑到目标值与决策值之间的关系,可将全系数模糊线性规划问题转换成一个新的普通的线性规划问题,进而可求出目标函数值.     

Bi-matrix Games with Fuzzy Goals and Fuzzy

A bi-matrix game with fuzzy goal is shown to be equivalent to a (crisp) non-linear programming problem in which the objective as well as all constraint functions are linear except two constraint functions, which are quadratic. This equivalence is further extended to bi-matrix games with fuzzy pay-offs, as well as to bi-matrix games with fuzzy goals and fuzzy payoffs, whose equilibrium strategies are conceptualized by employing a suitable ranking (defuzzification) function.     

修正的模糊最小一乘线性回归

对文献[1]提出的基于对称三角模糊数的模糊最小一乘线性回归进行修正和扩展,给出模糊最小一乘线性回归模型的三种不同形式,并将其转化为线性规划或非线性规划问题进行求解。最后,给出几个数值实例,通过计算和比较,结果表明三种模糊最小一乘线性回归模型都具有非常好的拟合性。     

Finding an inner estimation of the solution set of a fuzzy linear system

In this paper, we consider the problem of finding an inner estimation of the solution set of a fuzzy linear system with a real-valued coefficient matrix and a fuzzy-valued right-hand side vector. The proposed idea is based on the utilization of interval Gaussian elimination procedure to produce an inner estimation of the solutions set. To this end, firstly we apply interval Gaussian elimination procedure to obtain the solution set of a fuzzy linear system and secondly, by limiting it via solving a crisp linear system, we find an inner estimation of the solutions set, such that it satisfies the related fuzzy linear system. Finally, several numerical examples are given to show the efficiency and ability of our method.     

Bivalent and other solutions of fuzzy relational equations via linguistic hedges

We show that the well-known results regarding solutions of fuzzy relational equations and their systems can easily be generalized to obtain criteria regarding constrained solutions such as solutions which are crisp relations. When the constraint is empty, constrained solutions are ordinary solutions. The generalization is obtained by employing intensifying and relaxing linguistic hedges, conceived in this paper as certain unary functions on the scale of truth degrees. One aim of the paper is to highlight the problem of constrained solutions and to demonstrate that this problem naturally appears when identifying unknown relations. The other is to emphasize the role of linguistic hedges as constraints.     

Fuzzy linear matrix equation

The main aim of this paper is to discuss Fuzzy Linear Matrix Equations (shown as FLME) of the form AXB = C for finding its fuzzy solutions. In this paper, the parametric form of the fuzzy linear system is used. Necessary and sufficient conditions for the existence of the set of fuzzy solutions are derived, and a numerical procedure for calculating the solutions is designed.     

The solution of fuzzy linear systems by non-linear programming: a financial application

Fuzzy linear systems of equations play a major role in various financial applications. In this paper we analyse a particular fuzzy linear system: the derivation of the risk neutral probabilities in a fuzzy binary tree. This system has previously been investigated and different solutions to different forms of the same system have been proposed.     

Some duality results on linear programming problems with symmetric fuzzy numbers

Recently, linear programming problems with symmetric fuzzy numbers (LPSFN) have considered by some authors and have proposed a new method for solving these problems without converting to the classical linear programming problem, where the cost coefficients are symmetric fuzzy numbers (see in [4]). Here we extend their results and first prove the optimality theorem and then define the dual problem of LPSFN problem. Furthermore, we give some duality results as a natural extensions of duality results for linear programming problems with crisp data.     

具有模糊系数的模糊线性规划问题

本文考虑具有模糊系数的模糊线性规划问题中各系数的模糊可能性分布，而用指数（或线性）的隶属函数来描述，然后使用模糊数集上的实值函数，使模糊数在模型均值的意义下对应于一个实数，借此，将原问题公式化为一个普通线性规划。     

线性Fuzzy方程组(A~)(x~)=(b~)的解

重点研究线性Fuzzy方程组Ax=b的解,其中矩阵A和向量5均以有限Fuzzy数为其元素。文中首先指出,使用扩展原理和Fuzzy数运算规则有时会导致Ax=b没有解。本文以实广义逆矩阵为工具,给出了Ax=b的六个解,证明了它们都是R^n上的Fuzzy向量。     

On fuzzy random multiobjective quadratic programming

In this paper, a multiobjective quadratic programming problem having fuzzy random coefficients matrix in the objective and constraints and the decision vector are fuzzy pseudorandom variables is considered. First, we show that the efficient solutions of fuzzy quadratic multiobjective programming problems are resolved into series-optimal-solutions of relative scalar fuzzy quadratic programming. Some theorems are proved to find an optimal solution of the relative scalar quadratic multiobjective programming with fuzzy coefficients, having decision vectors as fuzzy variables. At the end, numerical examples are illustrated in the support of the obtained results.     

Fuzzy linear programming problems as bi-criteria optimization problems

In this paper, we consider fuzzy linear programming (FLP) problems which involve fuzzy numbers only in coefficients of objective function. First, we shall give concepts of optimal solutions to (FLP) problems and investigate their properties. Next, in order to find all optimal solutions, we define three types of bi-criteria optimization problems.     

基于多目标规划法的模糊线性回归分析

讨论输入、输出均为模糊数,回归系数为实数时的模糊线性回归分析。由于模糊最小二乘线性回归容易受异常值的影响,而最小一乘法能有效地降低回归模型的误差。为此,基于最小一乘法,建立多目标规划模型并将其转化为非线性规划问题进行求解,从而实现模糊线性回归模型的参数估计。最后,结合一个数值实例,验证和比较该方法的合理性和优越性。     

Multi-objective multi-item solid transportation problem in fuzzy environment

A multi-objective multi-item solid transportation problem with fuzzy coefficients for the objectives and constraints, is modeled and then solved by two different methods. A defuzzification method based on fuzzy linear programming is applied for fuzzy supplies, demands and conveyance capacities, including the condition that both total supply and conveyance capacity must not fall below the total demand. First, expected values of the fuzzy objective functions are considered to derive crisp values. Another method based on the concept of “minimum of fuzzy number” is applied for the objective functions that yields fuzzy values instead of particular crisp values for the fuzzy objectives. Fuzzy programming technique and global criterion method are applied to derive optimal compromise solutions of multi-objectives. A numerical example is solved using above mentioned methods and corresponding results are compared.     

一类全系数模糊线性规划的求解方法

利用结构元方法定义一种模糊数排序准则,提出将目标函数和约束条件中都含有三角模糊数的全系数模糊线性规划等价转化为经典线性规划的方法,并证明其合理性.与其它方法相比较,该方法证明了得到的解优于已有其它方法的解,并且约束条件少,运算方法简便.将本文的方法运用到数值算例中,进一步表明了提出方法的有效性和广泛性.     

模糊均衡问题的求解及应用

根据实际均衡问题研究的需要,给出了模糊向量、模糊值函数、模糊矩阵等新概念,建立了模糊均衡问题的数学模型,即模糊线性互补问题。在引入新的模糊期望的基础上,研究了其性质,并据此给出了模糊线性互补问题的一种确定型等价式及此类问题的均衡解的概念。用实例说明了所提模型和方法的合理性及应用前景。     

Numerical solution of fuzzy differential equations under generalized differentiability

In this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. Utilizing the Generalized Characterization Theorem, we investigate the problem of finding a numerical approximation of solutions. Then we show that any suitable numerical method for ODEs can be applied to solve numerically fuzzy differential equations under generalized differentiability. The generalized Euler approximation method is implemented and its error analysis, which guarantees pointwise convergence, is given. The method’s applicability is illustrated by solving a linear first-order fuzzy differential equation.