Fuzzy multiple attribute decision-making model for synergic knowledge innovation in supply chain

The procedure of supply chain development is the process of continuously congregating knowledge and transforming knowledge.First,the precondition of synergic knowledge innovation in the supply chain is narrated.Then the characteristics of synergic knowledge innovation in the supply chain are analyzed,including complexity,accumulating and evolving process,and the cooperation of members and network integration.Due to the characteristics of multi-factors and uncertainties of the supply chain system,the fuzzy multi-attribution group decision-making model is introduced to solve the involved problem of synergic knowledge innovation in the supply chain.After elaborating on steps of using the fuzzy multiple attribute decision-making(MADM)model,the procedure of decision making for synergic knowledge innovation in the supply chain is explained from an example in the application of a fuzzy MADM model.The fuzzy MADM model,which amalgamates intuition and resolution decision-making can effectively improve the rationality of decision-making for synergic knowledge innovation in the supply chain.

Cotangent Similarity Measure of Consistent Neutrosophic Sets and Application to Multiple Attribute Decision-Making Problems in Neutrosophic Multi-Valued Setting

A neutrosophic multi-valued set(NMVS)is a crucial representation for true,false,and indeterminate multivalued information.Then,a consistent single-valued neutrosophic set(CSVNS)can effectively reflect the mean and consistency degree of true,false,and indeterminate multi-valued sequences and solve the operational issues between different multi-valued sequence lengths in NMVS.However,there has been no research on consistent single-valued neutrosophic similarity measures in the existing literature.This paper proposes cotangent similarity measures and weighted cotangent similarity measures between CSVNSs based on cotangent function in the neutrosophic multi-valued setting.The cosine similarity measures showthe cosine of the angle between two vectors projected into amultidimensional space,rather than their distance.The cotangent similaritymeasures in this study can alleviate several shortcomings of cosine similarity measures in vector space to a certain extent.Then,a decisionmaking approach is presented in viewof the established cotangent similarity measures in the case of NMVSs.Finally,the developed decision-making approach is applied to selection problems of potential cars.The proposed approach has obtained two different results,which have the same sort sequence as the compared literature.The decision results prove its validity and effectiveness.Meantime,it also provides a new manner for neutrosophic multi-valued decision-making issues.

Hybrid multiple attribute decision making model based on entropy

From the viewpoint of entropy, this paper investigates a hybrid multiple attribute decision making problem with precision number, interval number and fuzzy number. It defines a new concept： project entropy and the decision is taken according to the values. The validity and scientific nature of the given is proven.

Aczel-Alsina Weighted Aggregation Operators of Simplified Neutrosophic Numbers and Its Application in Multiple Attribute Decision Making

The simplified neutrosophic number(SNN)can represent uncertain,imprecise,incomplete,and inconsistent information that exists in scientific,technological,and engineering fields.Hence,it is a useful tool for describing truth,falsity,and indeterminacy information in multiple attribute decision-making(MADM)problems.To suit decision makers’preference selection,the operational flexibility of aggregation operators shows its importance in dealing with the flexible decision-making problems in the SNN environment.To solve this problem,this paper develops the Aczel-Alsina aggregation operators of SNNs for MADM problems in view of the Aczel-Alsina operational flexibility.First,we define the Aczel-Alsina operations of SNNs.Then,the Aczel-Alsina aggregation operators of SNNs are presented based on the defined Aczel-Alsina operations of SNNs.Next,a MADM method is established using the proposed aggregation operators under the SNN environment.Lastly,an illustrative example about slope treatment scheme choices is provided to indicate the practicality and efficiency of the established method.By comparison with the existing relative MADM methods,the results show that the established MADM method can overcome the insufficiency of decision flexibility in the existing MADM methods and demonstrate the metric of flexible decision-making.

Novel method for hybrid multiple attribute decision making based on TODIM method

The TODIM(an acronym in Portuguese for interactive and multiple attribute decision making) method is a valuable tool to solve the multiple attribute decision making(MADM) problems considering the behavior of the decision maker(DM), while it cannot be used to handle the problem with unknown weight information on attributes. In this paper, a novel method based on the classical TODIM method is proposed to solve the hybrid MADM problems with unknown weight information on attributes,in which attribute values are represented in four different formats:crisp numbers, interval numbers, triangular fuzzy numbers and trapezoidal fuzzy numbers. Firstly, the positive-ideal alternative and negative-ideal alternative are determined, and the gain and loss matrices are constructed by calculating the gain and loss of each alternative relatived to the ideal alternatives concerning each attribute based on different distance calculation formulas, which may avoid the information missing or information distortion in the process of unifying multiform attribute values into a certain representation form. Secondly, an optimization model based on the maximizing deviation(MD) method, by which the attribute weights can be determined, is established for the TODIM method. Further, the calculation steps to solve the hybrid MADM problems are given. Finally, two numerical examples are presented to illustrate the usefulness of the proposed method, and the results show that the DM's psychological behavior, attribute weights and the transformed information would highly affect the ranking orders of alternatives.

翘嘴鳜与斑鳜杂交F_1代食性驯化及主要形态性状的通径分析

对翘嘴鳜(♀)和斑鳜(♂)杂交F1代进行程序性的驯化,挑选出易驯化和不易驯化的2组。采用一维方差分析和主成分分析研究了易驯化和不易驯化杂交鳜的形态差异;对易驯化杂交鳜全长、体长、体宽、体高、吻长、头长、眼径、眼间距、尾长、尾柄高、尾柄长和体质量等12个性状进行了相关分析和通径分析。试验结果显示,所选易驯化杂交鳜F1代体长、体高和眼径3个形态性状对体质量的相关系数均达到极显著水平(P<0.01),对体质量的通径系数亦达到极显著水平(P<0.01),体长对体质量的直接影响最大,通径系数达0.435;所选3个形态性状与体质量的共同决定系数r2=0.949,说明所选性状是影响体质量的主要形态性状;应用逐步多元回归分析建立了以体质量为依变量(Y),体长(X2)、体高(X4)和眼径(X7)为自变量的回归方程:Y=-15.527+0.127 X2+0.344 X4+0.903 X7。试验结果说明,翘嘴鳜和斑鳜杂交F1代存在易驯化和不易驯化个体的食性分化;用体长、体高和眼径估计体质量的多元回归方程为易驯化杂交鳜选择育种提供了理论依据。

一种新的混合型多属性决策方法及在供应商选择中的应用

研究了一种属性权重未知的混合型多属性决策模型。为了简化计算,把区间数和模糊数转化成精确数得到规范的决策矩阵。基于属性的熵,建立了具有柔性的客观权重模型,把客观权重和主观权重线性合成为综合权重。给出了客观权重和综合权重合理性的判定定理。最后的案例说明该法是可行、有效的。

基于信息公理的混合型多属性产品方案评价

研究了指标属性值包含实数、区间数和模糊数的混合型多属性产品方案评价问题,考虑了评价指标设计范围不确定的情况,提出了一种基于信息公理的评价模型,并给出了具体的评价方法和步骤。通过确定每个方案各指标满足功能要求的概率,计算各方案的信息量,以信息量为统一测度比较方案间的优劣程度,实现方案的优劣排序。决策者不必给出各评价指标的权重,也不需要对决策矩阵进行规范化,从而为解决混合型多属性评价优选问题提供了一条新的途径。以汽车起重机综合评价为例,说明了信息公理的混合型多属性评价方法的可行性。

一种基于相似度的混合型多属性决策方法

研究了实数、区间数、语言值和不确定语言值相结合的混合型多属性决策问题。基于逼近理想解的排序方法(TOPSIS方法)确定理想方案,并定义了一种新的相似度,将各类型属性值的相似度计算规范到统一的度量空间,并且指出该相似度的几何意义,说明用该方法描述方案相似程度的合理性。将待选方案与理想方案比较,进行排序择优。最后,给出两个算例,证明了该算法的有效性。

混合型多属性决策的HB-SIR方法

针对权重已知且属性值为精确数、区间数、三角模糊数和梯形模糊数的混合型多属性决策问题,提出了一种新的混合型级别高于方法(hybrid superiority and inferiority ranking,HB-SIR)。该方法依据混合型多属性决策矩阵构建正负理想方案,将混合型多属性决策矩阵转化成标准优势和劣势差异信息矩阵,进而通过高斯准则计算各个方案的优势指数和劣势指数,构建优势矩阵和劣势矩阵,并使用简单加权(simple additive weighting,SAW)方法计算出方案的优势流和劣势流,据此获得方案的部分或完全排序。最后,通过一个算例验证了该方法的有效性。

一种混合型多属性决策问题的TOPSIS方法

研究了精确数、区间数和模糊数指标相结合的混合多属性决策问题,提出了一种基于理想点的多属性决策模型,给出具体的决策方法和过程.各方案的排序是根据其到正理想解的相对贴近度大小进行的,从而为解决混合多属性决策问题提供了一条新的途径.

基于模糊TOPSIS方法的变压器维修策略

变压器维修策略的决策是一种涉及到量化指标和定性分析指标共存的混合多属性指标的决策问题.运用模糊理想解法(fuzzy TOPSIS)建立了变压器维修策略的模糊综合评价分析模型,来解决含有混合多属性指标决策问题.这种方法不仅可以对多台变压器的运行情况进行监视,通过利用计算相对贴近度来确定变压器的运行状态,进而确定变压器的维修策略,而且还可以通过专家系统对1台变压器的多种维修策略进行直接的判断与确定,通过精确的实数型指标值、区间数型的指标值和模糊数的指标值进行分类判断,给出多种维修策略下的取值情况,进而分析比较各个相对贴近度的大小,做出排序,决定选取哪种维修策略.通过实例验证此方法具有良好的决策效果.

基于模糊群决策的智能仪器故障诊断专家系统

本文介绍了采用专家系统解决智能仪器故障诊断的方法。针对智能仪器的故障特点,采用规则推理和事例推理相结合的混合推理技术。在规则推理中,提出了分层搜索的诊断思路,并且在不同搜索层次中,各规则优先权的确定采用基于模糊多属性群决策的方法。针对这种推理方法,采用数据库技术实现了知识库的设计,并用VS.net软件开发出了一套高效率智能仪器故障诊断专家系统。该系统在实际使用中表现出比第一个版本更高的诊断效率。

城市突发事件的应急设施选址群决策方法

针对应急设施选址中存在的一类不同决策部门存在不同权重且属性值为精确数、三角模糊数和语言值的混合型多属性群决策问题,提出了一种基于TOPSIS和距离测度的应急设施选址群决策方法。该方法可直接集结评价信息,避免了数据类型转换和量纲统一所造成的信息损失,同时基于距离测度方法确定决策部门和属性的客观权重,将其客观权重和主观权重线性合成为综合权重。最后,通过具体的应急设施选址案例验证方法的可行性和有效性。

混合型多属性群决策的油田节能项目优选模型——基于Vague集TOPSIS方法的研究

油田属于高耗能企业,加大油田节能降耗工作的实施力度不仅需要降低能耗,节约能源,还需要降低生产成本,提高油田的竞争力。实施节能项目是油田挖掘节能潜力,降低能源消耗和生产成本的重要途径,也是油田节能工作的具体表现。为合理选择节能项目和节能方法,提高油田节能效益,以油田节能项目为研究对象,结合其多属性、不确定和群决策等特点,同时考虑到专家群体对属性主观赋权的偏好和决策者对决策重要性认识的偏好,以及决策存在未知信息等因素,结合专家和决策者的特点以及油田节能工作的具体要求,构建油田节能项目的混合型多属性决策模型,提出一种考虑专家评价习惯和决策者对决策重要性认识的权重确定方法。通过将该方法应用于油田节能项目优选模型的应用实例中,为油田节能项目选出最优方案。结果表明,基于Vague集TOPSIS方法的混合型多属性群决策的油田节能项目优选模型切实可行,更符合油田节能工作的实际要求,为油田节能项目优选提供了新思路。

混合多属性决策问题中的权重研究

针对属性值以精确数、区间数、直觉梯形模糊数给出的混合多属性决策问题,提出一种基于属性的可靠性、属性对决策的影响度和决策者对属性的重视程度这三个维度给权重赋值的方法。首先对属性的可靠性进行定义,并计算出属性的可靠性;接着根据属性内部差异最大化求出属性对决策的影响度;随后利用直觉梯形模糊数之间的距离求出决策者对属性的重视程度,并用投影模型将这三个维度进行集成,得到最终的权重值。该方法能够使权重的获取更加全面,最后利用算例证明了本文方法的可行性。

基于D-U空间的混合型多属性决策方法

针对混合型决策中不同类型属性值无法有效保留其不确定信息的问题,根据不确定原理,将联系数的D-U空间理论引入到混合型多属性决策问题中,提出一种基于D-U空间的混合型多属性决策方法。将确定性与不确定视为一个整体,提出不同类型属性值在D-U空间中的映射转换法则,使得不同类型属性值在空间中得以统一量化,并明确属性中的不确定信息,避免不确定信息丢失而造成的决策偏差。在决策过程中,通过计算空间中属性向量的模和幅角的值进行方案选择,以描述各方案的稳定性,使排序准则具有直观的意义。通过2个算例验证了该方法的适用性和实用性。

混合非结构MAGDM的决策导向一致性检验方法

为有效应对现有群决策一致性检验方法的系列弊端,针对群决策的决策导向多元、决策方案众多、决策属性异构、决策信息多样等特征,在引入票权概念解析群决策一致性判定复杂性、刻画非结构多属性群决策合意信息表征假设情景的基础上,通过对常规混合非结构多属性群决策(MAGDM)问题进行公理化描述,并依据从方案层面到属性层面的整体决策信息判定策略,给出决策导向层面的整体判断信息一致性检验方法、多轮次非一致性决策信息调整策略及信息集结方法。案例应用结果表明提出的方法有效、可行。

基于混合多属性决策的TRIZ集成创新方法评价

从TRIZ集成创新方法分析和解决矛盾问题的角度,结合TRIZ理论的39个工程参数,构建了TRIZ集成创新方法的综合评价指标。对区间数相离度和可能度偏差最大化多属性决策的方法进行了改进,将区间型数据与精确型数据相统一,建立了混合数据指标的评价模型,并说明了算法步骤,解决了TRIZ集成创新方法的混合多属性评价与决策问题。通过算例说明了混合多属性决策在产品设计创新方法中的评价与选择过程。

境外煤矿投资项目混合多指标灰靶决策研究

煤矿投资尤其是境外煤矿投资决策,是一个极其复杂的问题。其中涉及的因素繁多,且影响程度难以准确确定。针对境外煤矿投资决策决策问题,建立了混合多指标灰靶决策模型,将决策过程中的不确定数据用区间数表示,将定性指标用三角模糊数表示,建立混合指标椭球灰靶。通过计算拟投项目的靶心距,得出最靠近靶心的最优项目决策。鉴于,煤矿开挖形式不同,所涉及的影响因素差别很大,所以,以井工开采为研究对象,进行投资决策分析,此方法同时适用于露天开采。