Using the Method of Maximizing Deviation to Make Decision for M ultiindices

This paper takes the synthesizing evaluation about industrial economic benefits by examples and proposes a new method named maximizing deviation method for multiindices decision. The new method can automatically determine the weight coefficients among the multiindices and also can obtain the exact and reliable evaluation results without subjectivity.

Maximizing deviation method for multiple attribute decision making under q-rung orthopair fuzzy environment

Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment,the evaluation information of alternatives given by decision makers is often fuzzy and uncertain.As a generalization of intuitionistic fuzzy set(IFSs)and Pythagoras fuzzy set(PFSs),q-rung orthopair fuzzy set(q-ROFS)is more suitable for expressing fuzzy and uncertain information.But,in actual multiple attribute decision making(MADM)problems,the weights of DMs and attributes are always completely unknown or partly known,to date,the maximizing deviation method is a good tool to deal with such issues.Thus,combine the q-ROFS and conventional maximizing deviation method,we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper.Firstly,we briefly introduce the basic concept of q-rung orthopair fuzzy sets(q-ROFSs)and q-rung interval-valued orthopair fuzzy sets(q-RIVOFSs).Then,combine the maximizing deviation method with q-rung orthopair fuzzy information,we establish two new decision making models.On this basis,the proposed models are applied to MADM problems with q-rung orthopair fuzzy information.Compared with existing methods,the effectiveness and superiority of the new model are analyzed.This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers(q-ROFNs)and whose attributes are incomplete.

Attributes reduct and decision rules optimization based on maximal tolerance classification in incomplete information systems with fuzzy decisions

A new approach to knowledge acquisition in incomplete information system with fuzzy decisions is proposed. In such incomplete information system, the universe of discourse is classified by the maximal tolerance classes, and fuzzy approximations are defined based on them. Three types of relative reducts of maximal tolerance classes are then proposed, and three types of fuzzy decision rules based on the proposed attribute description are defined. The judgment theorems and approximation discernibility functions with respect to them are presented to compute the relative reduct by using Boolean reasoning techniques, from which we can derive optimal fuzzy decision rules from the systems. At last, three types of relative reducts of the system and their computing methods are given.

Prospect Theory Based Hesitant Fuzzy Multi-Criteria Decision Making for Low Sulphur Fuel of Maritime Transportation

The environmental impact of maritime transport has now become a relevant issue in sustainable policy formulation and has attracted increasing interest from academia.For the sustainable development of maritime transport,International Maritime Organization stipulates that the sulfur content of ship emissions will reach 0.5 from 2020.With the approaching of the stipulated implementation date,shipowners need to adopt scientific methods to make decision on low sulfur fuel.In this study,we applied a prospect theory based hesitant fuzzy multi-criteria decision-making model to obtain the optimal decision of low Sulphur marine fuel.For this purpose,the hesitant fuzzy decision matrix is established to collect expert opinions,the maximizing deviation method is adopted to determine criteria weights.According to calculate the Euclidean distance from the reference points,we obtain the comprehensive prospect values of alternatives.Lastly,a case study is carried out to illustrate the significance and effectiveness of the proposed methodology.The innovation of this study is that it is the first-time adopting prospect theory and hesitate fuzzy sets to multi-criteria decision making for low Sulphur marine fuel,which provides an effective decision model for shipping companies under Low Sulphur regulations,and can also be extended to other industries.

Quantum Model of Decision-Making in Economics

The paper designs a quantum model of decision-making (QMDM) that utilizes neuroscientific evidence. The new model provides both normative and positive implications to economics. First, it enhances the study of decision-making which is an extension of the expected utility theory (EUT) in mathematical economics. Second, we demonstrate how the quantum model mitigates drawbacks of the expected utility theory of today.

不完备异构冲突信息系统中的极大一致联盟区间集族

作为处理不确定性问题的有效工具,三支决策已被广泛应用于冲突分析研究中。然而,现有的三支冲突分析模型大多基于单一类型的冲突信息系统,难以应对实际应用中代理对议题具有多类型评价值和缺失值的情况。同时,已有联盟集的定义通常基于给定代理,即联盟集中的代理与给定代理具有联盟关系,但不一定两两联盟。为了解决这些问题,构建了基于不完备异构冲突信息系统的三支冲突分析模型,并提出了代理两两相关的极大一致联盟区间集族的定义及其构造算法。首先,通过定义代理不同类型评价值的支持度和反对度,将对单个议题单维度多类型评价值的不完备异构冲突信息系统转化为双维度同类型评价值的二维模糊不完备冲突信息系统。其次,通过定义代理之间的乐观与悲观距离函数,构造了基于代理的联盟、冲突、中立区间集。最后,定义了极大一致联盟区间集族,并利用极大团的枚举算法获取极大一致联盟区间集族。

Maximal admissible mode decision delay in terminal guidance

Mode decision-maker is a critical component in the logic-based Integrated Estimation and Guidance(IEG) system. For the best possible estimation and guidance performance, the mode decision delay of the mode decision-maker should be limited to a range as small as possible. This paper presents a numerical method for computing the maximal admissible mode decision delay that varies with time-to-go. Particular attention has been paid to highly maneuvering target interception in terminal guidance. The results of this research offer useful guidelines for the design of the mode decision-maker in IEG systems.

Decision Aid Model for Private-owned Electric Vehicles Participating in Frequency Regulation Ancillary Service Market

To reduce the difficulty and enhance the enthusiasm of private-owned electric vehicles(EVs) in participating in frequency regulation ancillary service market(FRASM), a decision aid model(DAM) is proposed. This paper presents three options for EV participating in FRASM, i. e., the base mode(BM), unidirectional charging mode(UCM), and bidirectional charging/discharging mode(BCDM), based on a reasonable simplification of users' participating willingness. In BM, individual EVs will not be involved in FRASM, and DAM will assist users to set the optimal charging schemes based on travel plans under the time-of-use(TOU) price. UCM and BCDM are two modes in which EVs can take part in FRASM. DAM can assist EV users to create their quotation plan, which includes hourly upper and lower reserve capabilities and regulation market mileage prices. In UCM and BCDM, the difference is that only the charging rate can be adjusted in the UCM, and the EVs in BCDM can not only charge but also discharge if necessary. DAM can estimate the expected revenue of all three modes, and EV users can make the final decision based on their preferences. Simulation results indicate that all the three modes of DAM can reduce the cost, while BCDM can get the maximum expected revenue.

基于离差最大化的决策者权重的确定方法

基于离差最大化思想提出了一种确定多属性群决策中决策者权重的新方法。先根据群决策者对方案属性的客观评价值计算出属性的权重,然后根据各方案的综合属性值,基于离差最大化法给出决策者的权重,进而给出多方案间的排序。该方法充分发挥了离差最大法的客观赋权性,并且能够激励决策者对已知方案进行客观合理评价。最后将该方法应用于某化工建设项目环境影响技术评估,实例表明该方法的可行性和有效性。

基于典型相关分析的变化检测中变化阈值的确定

以东营市为例 ,把基于典型相关分析的方法运用于多时相遥感影像的变化检测中。对于变化阈值的确定 ,采用了一种基于贝叶斯理论的最小错误率的方法。这种方法实质上是一种非监督分类的方法 ,即不需要地面实况数据或其它先验知识 ,直接对典型相关处理后的差值图像进行分析计算得到阈值 ,使变化检测的错误率达到最小。实验结果证明了这种方法的有效性。

云物流模式下基于最大覆盖配送中心的选址—分配问题研究

为了实现物流资源利用率的提高和物流成本的降低,根据"云"的思想,建立了云物流下基于最大覆盖的选址—分配的多目标非线性决策模型,该模型的目标是配送中心的选址优化和整体需求覆盖最大化。设计了基于遗传和粒子群的组合式启发式算法,对算法的性能进行了Benchmark测试。通过大量算例和对比分析,验证了模型和算法的有效性和稳定性。

基于熵权与离差最大化的多属性群决策方法

对多属性决策用离差最大化方法,对决策者权重用熵权法确定,并用该方法对建设项目风险进行评价。

四种客观权重确定方法在粮虫可拓分类中的应用比较

储粮害虫的数字特征多,特征之间混合度比较大,可用可拓决策分析来解决其分类问题。在粮虫的可拓分类中,需要自动确定特征的客观权重,以避免传统的专家经验法在确定权重方面所带来的人为因素的影响。该文提出了模糊决策矩阵和均值决策矩阵2种构建决策矩阵的方法。将最大离差法、类间标准差法、CRITIC法和熵值法4种确定客观权重的方法分别应用到粮虫的分类中,并通过基于经典域和节域不同构建方法的2种可拓分类器进行了分析和比较。对粮仓中危害严重的9类粮虫进行了自动分类,结果表明基于模糊决策矩阵的最大离差法权重是粮虫可拓分类的最佳方案,识别率达到93%。

网络外部性下质量决策与零售商经营目标选择

在网络外部性市场环境下,为研究制造商质量决策和零售商经营目标策略选择之间的影响机理,构建了制造商质量决策和单零售商群体的演化博弈模型,分析了网络外部性和可变质量成本系数对零售商经营目标选择、制造商质量决策、以及节点企业利润的影响.研究发现,1)当制造商只拥有部分市场决策权力时,其质量决策将受到零售商的经营目标策略调整的影响,而零售商经营目标的策略调整则取决于网络外部性大小.当网络外部性较小时,零售商的经营目标将演化稳定为利润最大化,此时制造商将制定较低的产品质量水平;当网络外部性处在中等水平时,零售商的经营目标将演化稳定为利润最大化和收入最大化的混合目标策略,此时制造商将制定中等产品质量水平;当网络外部性较大时,零售商的经营目标将演化稳定为收入最大化,此时制造商将制定高产品质量水平.2)当网络外部性处在中等水平时,其与可变质量成本对零售商经营目标的选择呈现出交叉影响效应,随着可变质量成本的减小,零售商经营目标策略将从利润最大化策略向混合策略,或者混合策略向收入最大化策略演变.3)网络外部性对制造商产品质量的影响效果与可变质量成本和零售商经营目标选择有关,网络外部性效应的增加并不总是使得产品的质量降低.

基于风险价值约束的贷款组合效用最大化优化模型

资产组合优化是使投资者期望效用最大化的决策。文中用风险价值(VaR)来控制风险,根据在贷款组合有效边界上银行效用最大化的目标分配各项贷款,建立了基于VaR约束的贷款组合效用最大化优化模型。主要创新与特色:①通过贷款组合效用最大配给贷款符合贷款优化的目的,解决了决策模型与决策目的相一致的问题;②当银行决策者或决策群体对风险的偏好在VaR允许范围内时,现有研究的效用最大化决策模型是本模型的特例;③在控制贷款组合VaR的前提下,实现贷款组合效用最大化。当效用最大的贷款组合在VaR控制的边界内时,此组合即为最优组合。当效用最大的贷款组合在VaR控制的边界外时,贷款组合有效边界上效用最大的组合就是最优组合。

一种基于灰色关联度的多属性群决策方法

基于灰色关联度的思想提出了一种群决策方法。该方法根据各专家给出的决策矩阵,利用灰色关联度的思想确定专家权重,得出群决策矩阵,基于偏差最大化的思想计算属性权重,计算各方案的综合关联度,据此确定方案的排序。算例表明了利用此方法得出的方案综合关联度之间相对差距较大,提高了决策的科学性和有效性。指出了徐选华等人提出的算例中的错误,予以纠正。

基于最大比合并空间分集判决反馈盲均衡算法

信道的多径传播和衰落特性常在接收端引起码间干扰,严重影响了通信质量。为了减少码间干扰,提高通信质量,在分析空间分集技术和判决反馈盲均衡性能的基础上,提出了一种基于最大比合并空间分集的判决反馈盲均衡算法(MRC-DFE),该算法利用了空间分集来减少衰落的影响,利用判决反馈盲均衡器来克服码间干扰,具有收敛速度快、均方误差小的特点。计算机仿真结果,验证了该算法的有效性。

离差最大化时基于交叉评价的多属性决策方法

针对属性权重完全未知,且评价系统内既有客观数据、又有主观因素的多属性决策问题,提出一种基于离差最大化和交叉评价的模糊多属性决策方法。该方法首先定义了最小交叉效率、最大交叉效率等概念,将量化指标用交叉评价方法进行处理;然后采用模糊综合评价方法评价非量化指标,并基于离差最大化思想确定权重;最后将模糊化处理之后的量化指标与非量化指标一起进行最终评价,建立离差最大化条件下基于交叉评价的模糊多属性决策模型。最后通过算例验证了方法的可行性及有效性。

NSGA-II算法的改进及其在风火机组多目标动态组合优化中的应用

为了解决风火机组动态组合优化问题,重点针对时间耦合的动态特性及混合整数变量的求解,提出改进的基于非支配排序的遗传算法NSGA-Ⅱ(non-dominated sorting genetic algorithm-Ⅱ),引入节能减排理念,建立以CO2与SO2排放量及机组燃煤、启停费用最低的多目标函数。采用双层优化策略分别对启停离散量和负荷分配连续量进行寻优求解,引入模糊最大满意度决策法对Pareto解集进行决策,并嵌套在每次动态求解过程中。通过对某含风电场的10机组算例进行仿真,其结果表明了该方法的可行性和有效性。

运用离差最大化方法进行多指标决策与排序

本文以工业经济效益的综合评价和排序为应用背景，提出了一种多指标决策与排序的新方法——离差最大化方法。该方法能够自动确定各评价指标间的加权系数，且概念清楚、涵义明确，排序结果准确、可信，不具有主观随意性。