模糊矩阵对策

本文考虑了三种类型的模糊矩阵对策问题，提出了最优解集和对策值对价值标准的连续依赖性，对策双方最优策略的可调和性等概念，得到了一些基本结果。模糊矩阵对策；价值标准；连续依赖性；可调和性     

临界情况下模糊矩阵对策的性质

讨论临界情况下模糊矩阵对策的性抽，对模型问题各种情况给出了临界值c*的定义，证明了当d(f1,f2)＜ε≤c*时，模糊矩阵对策模型问题关于价值函数f1(x)、f2(x)具有连续依赖性和可调和性。     

矩阵对策的公平性研究

众所周知，零和二人有限对策也称为矩阵对策。设做一个矩阵对策的两个局中人都希望对策结果尽可能公平。当两个局中人使用对策解中的策略进行对策时，如果对策结果最公平，那么这个对策解称为最优的。本文证明了最优对策解集的一些性质，然后给出矩阵对策公平度的概念并证明了它的一些有趣的性质。     

0-1对策的完全混合Nash均衡的代数求解法

将求解一般0-1策略对策的完全混合Nash均衡的问题转化为求解根为正的纯小数的高次代数方程组的问题.作为一种特殊而重要的情形,利用Pascal矩阵,Newton矩阵(对角元素为Newton二项式系数的对角矩阵)和Pascal-Newton矩阵(Pascal矩阵和Newton矩阵的逆阵的乘积)将求解对称0-1对策的完全混合Nash均衡的问题转化为求解根为正的纯小数的高次代数方程的问题,并给出第二问题的反问题(由完全混合Nash均衡求解对称0-1对策族)的求解方法.同时,给出了一些算例来说明对应问题的算法.     

支付值为直觉模糊集的矩阵对策的线性规划求解方法

研究支付值为直觉模糊集的矩阵对策的求解方法.提出了支付值为直觉模糊集的矩阵对策的定义,并根据多目标优化的帕雷托最优解的概念定义了直觉模糊矩阵对策解的概念.进一步根据解的定义,证明了求此对策问题的解转化为求线性规划问题的最优解.通过一个数值实例说明了该方法的有效性和实用性.     

一类双层规划问题及其在矩阵对策中的应用

基于建设节约型社会和保护资源环境的需要,提出了一类特殊的双层规划问题,即B规划.给出了B规划的数学模型、有关理论和求解方法.最后还给出了B规划在矩阵对策中的一个应用.我们把局中人设有得失控制值的对策问题称为稳妥型对策.稳妥型矩阵对策可化为B规划问题求解.     

直觉模糊多目标二人零和矩阵对策

研究矩阵对策是深入研究对策理论的一个基本途径和重要手段。根据直觉模糊多目标决策和模糊对策理论,研究了支付值为直觉模糊值的多目标二人零和矩阵对策。首先介绍了基于直觉模糊集的多目标二人零和矩阵对策模型,接着提出了求解直觉模糊多目标二人零和矩阵对策的线性规划方法。最后以数例说明本文提出的方法。结果表明该方法能方便地得到对策的均衡策略和均衡解。     

基于连续同伦的多方对策之Nash均衡点的机械化求解方法

Nash定理证明非合作n人矩阵对策一定有混合平衡解,现有文献多讨论n=2时混合平衡解的求法,一般用优化或逼近的方法.文章给出了一种机械化求解方法,通过构造非合作多人矩阵对策的混合平衡局势所满足的多项式方程组,应用方程组求解软件由此可直接求出多人对策的问题的各种混合平衡解.     

达标度矩阵对策及其协调解

本文在文献「５」的思想基础上，首先论述达标度及达标度矩阵对策的有关定义。同时，在文「７」，「８」的基础上，进一步给出达标度矩阵对策的协调解概念及解结构。然后，具体讨论解的几种协调方法，即容忍旗的协调，极小熵协调和学习协调等。最后给出结论和注。     

一类多步矩阵对策上的计策问题

以有序树为工具,研究了可以描述连环计,诱敌深入等多步矩阵对策上的一类计策模型.在不考虑信息环境的封闭对策系统中,及局中人对每一步矩阵对策的赢得矩阵,两个局中人的策略集合以及局中人的理性等的了解都是局中人的共同知识的假定下,提出了局中人的最优计策链及将计就计等概念,研究了局中人中计和识破计策的固有概率,讨论了局中人在什么情况下最好主动用计,在什么情况下最好从动用计以及求解最优计策等问题.     

Alfa-cut based linear programming methodology for constrained matrix games with payoffs of trapezoidal fuzzy numbers

The purpose of this paper is to develop an effective methodology for solving constrained matrix games with payoffs of trapezoidal fuzzy numbers (TrFNs), which are a type of two-person non-cooperative games with payoffs expressed by TrFNs and players’ strategies being constrained. In this methodology, it is proven that any Alfa-constrained matrix game has an interval-type value and hereby any constrained matrix game with payoffs of TrFNs has a TrFN-type value. The auxiliary linear programming models are derived to compute the interval-type value of any Alfa-constrained matrix game and players’ optimal strategies. Thereby the TrFN-type value of any constrained matrix game with payoffs of TrFNs can be directly obtained through solving the derived four linear programming models with data taken from only 1-cut and 0-cut of TrFN-type payoffs. Validity and applicability of the models and method proposed in this paper are demonstrated with a numerical example of the market share game problem.     

多重因素约束下的网格检查对策问题研究

基于物品数量及每列容量等限制因素,构造局中人的可行策略集合;考虑隐藏成本,处罚规则与检查成功概率等因素,构造相应的支付函数,建立多重因素约束下的网格检查对策模型.根据矩阵对策性质,将对策论问题转化为非线性整数规划问题,利用H(o|¨)lder不等式获得实数条件下的规划问题的解,然后转化为整数解,得到特定条件下的模型的对策值及局中人的最优混合策略.最后,给出一个实例,说明上述模型的实用性及方法的有效性.     

灰色双矩阵博弈模型及其均衡解

在支付矩阵和约束条件都是灰色的情况下,给出灰双矩阵博弈的一般形式,并且定义了灰双矩阵博弈的均衡解,证明灰双矩阵博弈的均衡解可由求解一个非线性规划问题得到.     

Matrix Games with Fuzzy Goals and Fuzzy Linear Programming Duality

A two person zero-sum matrix game with fuzzy goals is shown to be equivalent to a primal-dual pair of fuzzy linear programming problems. Further certain difficulties with similar studies reported in the literature are also discussed.     

The Concept of Proper Solution in Linear Programming

In this paper, we study the optimal solutions of a dual pair of linear programming problems that correspond to the proper equilibria of their associated matrix game. We give conditions ensuring the existence of such solutions, show that they are especially robust under perturbation of right-hand-side terms, and describe a procedure to obtain them.     

A fast approach to compute fuzzy values of matrix games with payoffs of triangular fuzzy numbers

The aim of this paper is to develop an effective method for solving matrix games with payoffs of triangular fuzzy numbers (TFNs) which are arbitrary. In this method, it always assures that players’ gain-floor and loss-ceiling have a common TFN-type fuzzy value and hereby any matrix game with payoffs of TFNs has a TFN-type fuzzy value. Based on duality theorem of linear programming (LP) and the representation theorem for fuzzy sets, the mean and the lower and upper limits of the TFN-type fuzzy value are easily computed through solving the derived LP models with data taken from 1-cut set and 0-cut set of fuzzy payoffs. Hereby the TFN-type fuzzy value of any matrix game with payoffs of TFNs can be explicitly obtained. Moreover, we can easily compute the upper and lower bounds of any Alfa-cut set of the TFN-type fuzzy value for any matrix game with payoffs of TFNs and players’ optimal mixed strategies through solving the derived LP models at any specified confidence level Alfa. The proposed method in this paper is demonstrated with a numerical example and compared with other methods to show the validity, applicability and superiority.     

Vector linear programming in zero-sum multicriteria matrix games

In this paper, a multiple-objective linear problem is derived from a zero-sum multicriteria matrix game. It is shown that the set of efficient solutions of this problem coincides with the set of Paretooptimal security strategies (POSS) for one of the players in the original game. This approach emphasizes the existing similarities between the scalar and multicriteria matrix games, because in both cases linear programming can be used to solve the problems. It also leads to different scalarizations which are alternative ways to obtain the set of all POSS. The concept of ideal strategy for a player is introduced, and it is established that a pair of Pareto saddle-point strategies exists if both players have ideal strategies. Several examples are included to illustrate the results in the paper.     

On computational methods for solutions of multiobjective linear production programming games

In this paper we consider a production model in which multiple decision makers pool resources to produce finished goods. Such a production model, which is assumed to be linear, can be formulated as a multiobjective linear programming problem. It is shown that a multi-commodity game arises from the multiobjective linear production programming problem with multiple decision makers and such a game is referred to as a multiobjective linear production programming game. The characteristic sets in the game can be obtained by finding the set of all the Pareto extreme points of the multiobjective programming problem. It is proven that the core of the game is not empty, and points in the core are computed by using the duality theory of multiobjective linear programming problems. Moreover, the least core and the nucleolus of the game are examined. Finally, we consider a situation that decision makers first optimize their multiobjective linear production programming problem and then they examine allocation of profits and/or costs. Computational methods are developed and illustrative numerical examples are given.     

Fuzzy matrix games via a fuzzy relation approach

A generalized model for a two person zero sum matrix game with fuzzy goals and fuzzy payoffs via fuzzy relation approach is introduced, and it is shown to be equivalent to two semi-infinite optimization problems. Further, in certain special cases, it is observed that the two semi-infinite optimization problems reduce to (finite) linear programming problems which are dual to each other either in the fuzzy sense or in the crisp sense.