区间灰色不确定语言多属性群决策方法

针对属性值为区间灰色不确定语言信息的多属性群决策问题,在定义区间灰色不确定语言变量及其运算规则的基础上,给出了3种几何加权集结算子,由区间灰色不确定语言几何加权算子集结各决策者给出的决策矩阵得到群体决策矩阵。在属性权重已知的情形下,基于该算子集结单个决策者给出的属性权重向量得到群体属性权重向量;在属性权重完全未知的情形下,采用信息熵法确定属性权重向量。采用区间灰色不确定语言混合几何加权算子集结各属性评价信息,得到各方案的综合评价值,基于区间灰色不确定语言变量大小比较的方法得到方案排序结果。算例分析表明了该方法的有效性与可行性。     

基于正态分布区间数的信息不完全的群决策方法

针对属性值为正态分布区间数而属件权重信息不完全的多属性群决策问题,定义了一些新的集成算子,即正态分布区间数的加权算术平均(NDINWAA)算子、正态分布区间数的有序加权平均(NDINOWA)算子和正态分布区间数的混合加权平均(NDINHA)算子,进而提出一种幕于正态分布区间数的信息不完全的多属性群决策方法.该方法利用NDINWAA算了和NDINHA算子对正态分布区间数属性值进行集成,利用正态分布区间数属性值的方差,通过建立优化模型确定最优属性权重,利用期望-方差准则对方案进行排序并择优.实例分析表明了该方法的可行性和有效性.     

基于可信度的基本不确定区间犹豫模糊广义TODIM应急群决策方法

针对应急决策环境所存在的信息不完备、认知不足等问题,区间犹豫模糊集能充分表达决策者在信息评价时的犹豫性和模糊性,但随着研究的深入,发现其存在无法保证信息质量的缺陷.为此,提出更符合实际决策需求、信息表达更加灵活的基本不确定区间犹豫模糊集,其为包含区间犹豫模糊集和确定度的二维信息集.在此基础上,定义基本不确定区间犹豫模糊加权平均算子、犹豫度及可信度,提出基于可信度的专家权重调整方法和属性权重确定方法,充分考虑了决策专家提供评价信息的可靠程度.最后,将广义TODIM方法拓展到基本不确定区间犹豫模糊环境,通过应急决策案例验证所提方法的可行性,并利用灵敏度分析和对比分析验证该方法的稳定性和有效性.     

采用区间数排序的采矿方法优选模型及其应用

针对采矿方法优选多属性决策中评价指标权重值难以确定和区间数排序难的问题,通过统计分析大量专家评价指标及其权重值,提出了基于专家经验统计的评价指标区间数权重值确定法;定义了有限个区间数排序时的目标区间数,解析了基于高斯平面直角坐标系的区间数与目标区间数二维关系.在此基础上,基于平面几何和极限的原理,定义了可实现对有限个区间数及同中轴区间数排序的区间数优势度函数,进而给出了该基于二维信息的区间数排序方法在多属性决策中的应用步骤.最后,通过采矿方法优选多属性决策实例验证了该方法的可行性和有效性.     

基于改进熵和新得分函数的区间直觉模糊多属性决策

针对决策信息为区间直觉模糊数且属性权重完全未知的多属性决策问题, 提出基于改进的区间直觉模糊熵和新得分函数的决策方法. 首先, 利用改进的区间直觉模糊熵确定属性权重; 然后, 利用区间直觉模糊加权算术平均算子集成信息, 得到各备选方案的综合属性值, 进而指出现有得分函数存在排序失效或排序不符合实际的不足, 同时给出一个新的得分函数, 并以此对方案进行排序; 最后, 通过实例表明了所提出方法的有效性.

     

基于区间相似度的动态服务协商模型

针对服务协商中信息的不对称性、协商环境的动态性以及QoS属性的不确定性和模糊性,提出基于区间相似度的动态服务协商模型。利用区间相似度和区间估计预测对方的协商策略,以此制定己方的最优反策略。算例分析表明,在动态服务协商环境下,该模型比静态协商模型更贴近现实的协商行为,能有效提高协商效率。     

属性和专家客观权重未知的区间数群决策方法

针对偏好信息为区间数形式、属性和专家客观权重未知的多属性群决策问题,提出通过属性评价值之间偏离程度的熵值分析和建立目标最小化的非线性规划模型确定属性客观权重,并结合属性主观权重获得属性综合权重;通过灰色关联法分析专家综合评价和群体综合评价之间一致性程度确定专家客观权重,并利用自适应迭代法求得稳定的专家权重;构造了一个新的区间数比较的可能度公式,并基于此公式,给出了方案排序问题的解决方法。通过算例分析及与其他方法对比,验证了所提出方法的可行性和有效性。最后,分析了相关参数对决策结果的影响。     

区间数动态多属性决策的VIKOR扩展方法

针对各决策阶段的时间权重以及属性权重已知,属性值以区间数形式给出的动态多属性决策问题,提出一种新的决策方法.该方法依据传统多准则妥协解排序法(VIKOR)的基本思路,结合区间数的运算规则,计算各阶段各方案的评价值,进而引入不确定动态加权平均(UDWA)算子进行集成,以获取各方案整体评价值的区间数.借助于区间数两两比较的可能度公式和模糊互补判断矩阵公式,对其进行比较,从而得到整个方案集的排序.最后以第3方逆向物流服务商的选择为实例进行分析,所得结果表明了该方法的可行性和有效性.     

基于区间粗糙算子的粗糙随机多准则决策方法

定义了区间粗糙随机变量、区间粗糙数的运算法则以及期望值和区间粗糙集结算子（WIRDAA）.针对准则权重信息不完全,准则值为区间粗糙随机变量的粗糙随机多准则决策问题,提出一种基于WIRDAA算子的决策方法.该方法首先计算出变量的期望值矩阵,利用距离最小化建立模型求解出准则权重;然后利用WIRDAA算子求出各方案的综合评价值,通过比较得到方案集的排序;最后通过实例表明了所提出方法的有效性和可行性.     

用区间直觉模糊集方法对属性权重未知的群求解其多属性决策

本文首先提出群区间直觉模糊有序加权几何(groupinterval-valuedintuitionistic fuzzy orderedweighted geometric,GIVIFOWG)算子和群区间直觉模糊有序加权平均(group interval-valued intuitionistic fuzzy ordered weighted averaging,GIVIFOWA)算子.利用GIVIFOWG算子或GIVIFOWA算子聚集群的决策矩阵以获得方案在属性上的综合区间直觉模糊决策矩阵(collectiveinterval-valuedintuitionistic fuzzy decision-matrix,CIVIFDM).然后定义了一个考虑犹豫度的区间直觉模糊熵(interval-valuedintuitionistic fuzzyentropy,IVIFE);通过熵衡量每个属性所含的信息来求解属性权重.最后,提出基于可能度的接近理想解的区间排序法(interval technique for order preference by similarity to an ideal solution,ITOPSIS)和区间得分函数法.在ITOPSIS法中,依据区间距离公式计算候选方案和理想方案的属性加权区间距离,进而采用ITOPSIS准则对各方案进行排序;在区间得分函数法中,算出CIVIFDM中各方案的得分值以及精确值,然后利用区间得分准则对各方案进行排序.实验结果验证了决策方法的有效性和可行性.     

A dynamic spectrum management strategy based on cooperative bargaining framework

This work proposes a dynamic and fair spectrum management strategy to be adopted by a service provider (SP). Here, we consider a scenario where multiple access networks (ANs) of different (not necessarily competing) technologies are owned by a single SP. We envisage that an SP employs an entity, called local spectrum controller (LSC), which manages a common pool of spectrum and is responsible for distributing the spectrum to individual ANs in a fair manner. Since the available spectrum is inadequate to satisfy the aggregate demand from all ANs simultaneously, LSC has to employ a dynamic spectrum allocation strategy. We have modeled the problem as an n-player cooperative bargaining game and have solved the problem with the help of solution techniques namely, Nash bargaining solution (NBS), Kalai-Smorodinsky bargaining solution (KSBS) and modified Thomson bargaining solution (MTBS). We have presented two novel heuristics to compute KSBS and MTBS. Moreover, a suitable utility function for the AN with respect to its received spectrum have been presented. We have also identified possible objectives of LSC (i.e., SP), namely minimizing overall dissatisfaction (MOD) of heterogeneous network, maintaining equality of distribution (MED) and maximizing proportional fairness (MPF). Finally, we have compared performances of above solutions with max–min fairness solution and Shapley value solution with respect to the above objectives of LSC.     

基于议价机制的网格资源交易算法

资源管理是网格技术研究的核心任务之一。针对网格资源异构性、动态性、自治性等特点提出了基于议价机制的网格资源交易算法。分析了网格资源管理的市场模型,指出市场模型中各角色的特点,提出了网格资源管理的议价模型。针对这种模型,提出了基于议价时限和价格变化率的网格资源交易算法,并根据平衡策略给出了该算法的描述。     

基于议价机制的网格资源交易算法

资源管理是网格技术研究的核心任务之一。针对网格资源异构性、动态性、自治性等特点提出了基于议价机制的网格资源交易算法。分析了网格资源管理的市场模型，指出市场模型中各角色的特点，提出了网格资源管理的议价模型。针对这种模型，提出了基于议价时限和价格变化率的网格资源交易算法，并根据平衡策略给出了该算法的描述。     

自动议价系统中的让步策略算法设计*

建立了一个多策略混合的让步模型,可以很好地模拟出人类在议价活动中策略的多变性.此外,还给出了该模型的实现算法及系统的议价协议.     

A Dynamic Model of Collective Bargaining

We use high-low search algorithms to compute equilibria in a multi-period model of collective bargaining. In this model, a group of workers bargains collectively with a firm which knows the per period incremental value v of each worker. The workers don't know their individual values, but use high-low search to learn them, given the known distribution of values in the group. In the first period the workers make a common wage demand w₁ and then the firm chooses a cutoff level y for the workers they will hire (i.e., those with v y). Since y is observable through numbers hired, workers may update their beliefs about their values, based on whether or not they were hired. In later periods workers with common beliefs make common wage demands. The main question addressed in the paper is how the firm can choose the hiring cutoff level to hinder the workers' learning process. We find (Theorem 1) that the firm's equilibrium strategy is to (i) hire some workers at a loss, and also (ii) to forego some profitable hirings. However (Theorem 2) the equilibrium outcome involves only the first kind of strategic loss by the firm. We also find (Theorem 3) that the firm's profit is less than when the worker optimizes against a predictable myopic firm (which chooses y=w₁). Thus the firm would wish to commit to the myopic hiring strategy if it were possible.     

Multi-Issue Negotiation Processes by Evolutionary Simulation, Validation and Social Extensions

We describe a system for bilateral negotiations in which artificial agents aregenerated by an evolutionary algorithm (EA). The negotiations are governed bya finite-horizon version of the alternating-offers protocol. Several issuesare negotiated simulataneously. We first analyse and validate the outcomes ofthe evolutionary system, using the game-theoretic subgame-perfect equilibriumas a benchmark. We then present two extensions of the negotiation model. Inthe first extension agents take into account the fairness of the obtainedpayoff. We find that when the fairness norm is consistently applied during thenegotiation, agents reach symmetric outcomes which are robust and ratherinsensitive to the actual fairness settings. In the second extension we modela competitive market situation where agents have multiple bargainingopportunities before reaching the final agreement. Symmetric outcomes are nowalso obtained, even when the number of bargaining opportunities is small. Wefurthermore study the influence of search or negotiation costs in this game.     

动态协商对策的诱导平衡*

本文动态对策协商的问题，提出了动态对策问题在协商 解处的诱导平衡的概念，研究了诱导平衡存在的必要条件和充分条件，并分析了线性二次型动态对策问题的诱导平衡。     

One-way ANOVA based on interval information

This paper deals with extending the one-way analysis of variance (ANOVA) to the case where the observed data are represented by closed intervals rather than real numbers. In this approach, first a notion of interval random variable is introduced. Especially, a normal distribution with interval parameters is introduced to investigate hypotheses about the equality of interval means or test the homogeneity of interval variances assumption. Moreover, the least significant difference (LSD method) for investigating multiple comparison of interval means is developed when the null hypothesis about the equality of means is rejected. Then, at a given interval significance level, an index is applied to compare the interval test statistic and the related interval critical value as a criterion to accept or reject the null interval hypothesis of interest. Finally, the method of decision-making leads to some degrees to accept or reject the interval hypotheses. An applied example will be used to show the performance of this method.     

一种基于合作博弈论的自动驾驶车道变更模型

提出一个新颖的车道变更模型,采用合作博弈方法激励车辆参与合作。首次将合作博弈理论应用到车道变更领域,设计用于两车变道的纳什讨价还价变道模型,然后扩展为三车的合作博弈变道模型,并求出变道模型的纳什讨价还价解和夏普利值。为了进一步激励车辆参与合作,在收益分配方案中加入支付补偿部分来实现整体收益的可转移性,从而取得模型的解。实验结果表明,采用合作博弈后车辆的整体收益得到了大幅增加,同时每个参与车辆的个人收益也增加了。     

基于混合报价策略的自动议价系统设计

随着电子商务的不断发展,通过网络进行商品交易的人在不断增多,拍卖、竞标等交易方式近年来得到了迅速发展,Internet和WWW也已成为零售业的非常重要的渠道。但在这些电子化的交易过程中,买、卖双方通常还是要亲自参与交易过程,商品交易的自动化程度还远远不够。文章对目前具有议价功能的典型系统进行了简单回顾,并根据目前研究中所存在的问题,提出了一个基于混合报价策略的自动议价系统模型。文中还给出了混合报价策略的定义及其实验测试结果。