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.

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.

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.

Solution to multiple attribute group decision making problems with two decision makers

A kind of multiple attribute group decision making （MAGDM） problem is discussed from the perspective of statistic decision-making. Firstly, on the basis of the stability theory, a new idea is proposed to solve this kind of problem. Secondly, a con- crete method corresponding to this kind of problem is proposed. The main tool of our research is the technique o~ the jackknife method. The main advantage of the new method is that it can identify and determine the reliability degree of the existed decision making information. Finally, a traffic engineering example is given to show the effectiveness of the new method.

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.

Response surface method using grey relational analysis for decision making in weapon system selection

A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.

Fuzzy-logic Method for Global Quality Optimization Problem of the Programmed Action Investment

In order to analyze the planning of a transport linear infrastructure(railway or ordinary road),in order to optimize a relationship work-environment after-work,the study team(engineers,architects,economists,etc),realize a careful prearranged analysis about the characteristic of the site and the large area which are involved by the work project and,once one found all possible alternative solutions,he should compare them through the use of suitable technical,economical and environmental parameters,choosing that one which maximize the global utility of the public investment.In this paper we study a fuzzy-logic method in order to help the decision maker in the analysis of the programmed action public investment.

3D矢量空间和最优最劣法在绿色产品设计决策方法中的应用

为了解决目前绿色产品设计方案中产品基础属性考虑欠缺,以及缺乏可视化比较方法的问题,提出一种基于3D矢量空间和最优最劣法(Best worst method,BWM)的绿色产品设计多属性决策方法。通过功能、外观和可持续3个维度为绿色产品设计的基础属性构建3D矢量空间,并对每个维度扩充其包含的下级属性;利用间隔方法优化的BWM获得三个维度及各维度下级属性的权重分配;通过3D矢量空间求得各备选方案的总体评价得分,实现客观科学的绿色产品设计多属性决策。以电动汽车的绿色产品设计方案为例,验证了所提方法的可行性和有效性。

改进TOPSIS的多属性决策方法

针对逼近理想点排序法(technique for order preference by similarity to ideal solution,TOPSIS)存在的缺陷,提出基于Tanimoto系数和基于对称差的2种改进TOPSIS。改善或解决TOPSIS存在指标相关性问题、特殊样本集合无法比较优劣问题和样本数据动态变化时产生的逆序现象等缺陷;在稳定性、特异性、敏感性和有效性4方面对经典TOPSIS模型、改进Tanimoto模型和改进对称差模型进行对比验证,给出2种改进模型的适用场景。结果表明,2种方法各具有一定的优势。

毕达哥拉斯犹豫模糊集多属性决策研究

针对属性间相互关联,评价信息为毕达哥拉斯犹豫模糊信息的多属性决策问题,首先通过研究犹豫度对决策结果的影响,提出一种新的毕达哥拉斯犹豫模糊集得分函数,解决了现有得分函数中存在的不足。其次,提出一种最小公倍数规范化原则,解决了现有方法容易引入误差的缺陷。最后,针对属性关联的多属性决策问题,基于λ-模糊测度与Choquet积分,提出了一种拓展交互式多准则决策(interative multi-criteria decision-making,TODIM)方法,既解决了属性关联的问题,又通过前景理论反映了决策者的心理行为特征。实例分析与敏感性分析验证了所提算法的正确性与有效性。

多属性决策方法在目标威胁评估中的研究综述

目标威胁评估为指挥决策提供数据支撑,多属性决策方法是目标威胁评估的有效手段。结合多属性决策方法的特点,区分威胁评估指标选择、威胁评估指标描述、威胁评估指标权重确定和目标威胁排序方法4个方面,系统总结了多属性决策方法在战场目标威胁评估中的研究现状,分析了每个方面存在的问题,探讨了未来多属性决策方法在战场目标威胁评估应用中需要重点发展的方向,为后续研究战场目标威胁评估提供参考借鉴。

一种新的区间数多属性决策的集结方法

对于属性权重和决策矩阵元素均为区间数的多属性决策问题,提出了一种新的方案综合属性区间的集结方法。通过给出与区间权重向量相对应的属性有效权重向量的定义及其具体表达形式,改变已有方法需要求解数学规划模型的做法,运用区间数的数乘运算和加法运算集结方案的有效综合属性区间值,并利用一种对区间数排序的方法,比较各方案的有效综合属性区间值来确定方案的优劣。最后,给出了一个数值例子,结果表明方法简单、有效,易于实现。

多属性决策中的线性组合赋权方法研究

权向量的确定是多属性决策中一个重要问题,线性组合赋权方法是解决该问题的一个有效途径。对线性组合赋权的求解问题进行了一般性的描述,并根据求解所用信息的不同将求解方法分为四类,阐述了每类方法常用的求解思路和原则,进一步分析了不同类别方法的特点。对求解方法进行分类,有利于对不同求解方法本质和特性的了解,可以为不同组合赋权方法的应用提供参考。

比较法确定多属性决策问题属性权重的灵敏度分析

属性权重的确定将直接影响多属性决策的求解结果,灵敏度分析可以判断决策结论的稳定性。针对比较法所得属性权重进行方案排序,利用经典的线性规划方法,将属性线性相关约束分解为两类物理意义更清晰的属性相关形式表示的约束条件,求解维持既定方案排序的权重变化区间,得出对既定决策排序结果最敏感的属性,从而辅助决策者做出更加合理的决策。计算实例表明,该方法具有可操作性和实用性。

基于前景理论的电网建设项目组合多属性决策方法

电网建设项目组合的投资决策属于多属性决策问题。现有投资决策方法一般将评价指标体系的属性用确定值描述,并对单个项目进行评估得到待选项目集。事实上,有些属性并不适合用确定值来描述;另一方面,有些项目之间存在相关性,这样按单个项目来确定待选项目集就未必合适。在此背景下,首先发展了针对确定型、区间型、概率型和模糊型4种数据类型指标的收益/损失及其概率的计算方法。为计及决策过程中决策者的心理因素和风险倾向的影响,将前景理论引入电网建设项目组合的投资决策之中。然后,基于差异化思想选择指标权重,并利用VIKOR这种多准则决策分析方法确定最优项目组合,避免了传统线性加权法用优质指标补偿劣质指标,从而可能导致所得到的最优项目组合中包含劣质指标的情况。最后,以某省级电力公司的电网建设项目组合的投资决策问题为例,说明了所述方法的可行性和有效性。

考虑决策者心理行为的区间数多属性决策方法

针对考虑决策者心理行为的区间数多属性决策问题,提出一种决策分析方法.首先,针对决策者参照依赖的心理行为特征,依据前景理论计算每个方案在各属性下的评价值相对于参照点的益损值,并构建益损决策矩阵;然后,考虑决策者损失规避的心理行为特征,基于TODIM方法的基本思想,计算决策者对每个方案的益损值的总体感知价值,并依据总体感知价值的大小对所有方案进行排序.最后,通过一个算例说明了该方法的可行性和有效性.

具有区间数的多属性决策问题的分析方法

为了解决带有不确定性区间数的多属性决策问题，首先给出了一个决策分析模型；然后针对决策方案的综合评价值，提出了关于区间数的两种排序方法；最后给出了实例计算．

TOPSIS偏序法

对多属性决策中的TOPSIS法提出一种改进方法 ,使之可用来产生备选方案的偏序 ,而不是传统的全序结果 .阐述了这种改进方法的合理性 .将TOPSIS法及改进方法编写成了方便使用的MATLAB程序 .

缝洞型碳酸盐岩储层地震属性优化方法及应用

针对塔里木盆地缝洞型碳酸盐岩储层各向异性特征显著、纵横向非均质性强的特点,本文在分析多元逐步判别法和核主成分分析法的基础上,将两种算法有机结合起来用于地震属性的优化,并以塔中45井区为试验区,建立了该区缝洞型碳酸盐岩储层的预测模型。实际应用中,剔除模型中对判别结果不敏感的属性,使各属性变量互不相关,很好地处理了地震属性之间的非线性问题,确保计算结果的稳定性;对模型进行回判检验,总符合率达到90.57%,表明所建模型的可靠性,可为地震属性优化与缝洞型碳酸盐岩储层预测研究提供一种有效的方法。

动态多指标决策问题的投影寻踪模型

针对动态多指标决策中指标和时段的权重确定问题,提出了基于投影寻踪(PP)的理想点法新模型(PP IPM模型)。该模型利用决策矩阵样本的内部信息,把方案的三维决策矩阵综合成一维投影值,投影值越大表示该方案越优,根据投影值的大小就可对各方案进行综合排序决策。建议用实码加速遗传算法进行PP IPM的建模,简化了PP技术的实现过程,克服了目前PP技术计算过程复杂、编程实现困难的缺点。实例计算的结果说明,直接由决策矩阵样本数据驱动的PP IPM模型用于动态多指标决策问题简便可行,适用性和可操作性强,具有推广应用价值。