基于混合模糊数的TOPSIS方法及产能过剩评价

利用区间数和三角模糊数可将定性指标定量化,从而构建多属性的混合指标体系.在多指标的评价体系中,权重的大小对评价的结果是非常重要的,本文给出了一种融合主观和客观的组合权重TOPSIS法.以七大过剩行业为研究对象,用AHP方法求出主观权重,利用模糊数将一些定性指标定量化,用变异系数法求出客观权重建立以主观、客观指标为约束条件的优化模型,求出组合权重的最优解,并将其应用于TOPSIS评价方法中,分析七大行业在2016-2018年的产能过剩程度,最后给出结果分析及对策建议.     

基于三角模糊熵的经济评价模型及副省级城市的实证研究

根据坚持以人为本,全面、协调、可持续的发展观的科学发展观的内涵,根据经济发展速度、经济发展质量及可持续发展等六个评价准则构建了经济评价指标体系。用客观赋权的熵值法和主观赋权的三角模糊法组合确定指标最优权重,建立了基于组合赋权的经济综合评价模型,并采用中国10个副省级城市的截面数据进行实证分析。本文的创新与特色一是通过对可持续发展和经济结构等准则层的指标评价,反映科学发展观全面协调可持续的基本要求。二是通过利用一个指标与另一个指标分值离差平方和最大原则,使各评价对象的多属性综合评价值尽可能分散、以便更清晰地体现指标对比的差异。改变了现有组合赋权研究中的由于平均赋权而导致指标差异不明显的状况。研究结果表明,根据我国10个典型副省级城市的截面数据、在指标分值离差平方和最大原则下建立优化模型,得到的主、客观权重分别为0.471和0.529。三是通过组合赋权,既保留了熵值法等客观赋权对实际情况的真实反映和对未来因素的推测、又反映了三角模糊等主观赋权所体现的指标属性对评价的重要程度和专家的知识与经验。四是对GDP增长率等适中型指标用偏离最优值的程度评分,解决了现有评价片面认为这些指标越大越好或越小越好的不合理问题。五是根...     

基于模糊熵-熵权法的混合多属性决策方法

针对决策信息以区间数、直觉模糊数和语言变量给出的混合多属性决策问题,提出了基于模糊熵-熵权法的混合多属性决策方法。通过规范化的方法把区间数转化为直觉模糊数,建立了直觉模糊数与语言变量的对应关系,把混合多属性决策信息统一在同一决策框架下;然后利用熵权法确定属性的客观权重区间,通过求解属性信息模糊熵最小的线性规划模型得到属性客观权重;再与主观赋权方法相结合确定属性的组合权重;最后应用相对熵排序法得到方案的最终排序结果。算例分析表明方法的可行性和实用性。     

基于新型区间直觉三角模糊熵的多属性决策方法

在进行区间直觉模糊多属性决策时,有时属性权重是未知的,针对这一问题,提出一种新型区间直觉三角模糊熵的决策方法.首先,给出该新型区间直觉三角模糊熵定义和相关定理,应用该区间直觉三角模糊熵确定属性的权重.然后,基于逼近理想解排序法(TOPSIS)的思想,采用改进的加权欧几里得距离,进行区间直觉模糊群决策,并给出决策步骤.最后,将该方法应用在供应链选择的群决策问题中,通过算例实验验证了该方法的有效性与可行性.     

基于相对熵和可变模糊集理论的战略性新兴产业企业信用评价

针对现有模糊评价方法缺乏动态可变性的不足,将可变模糊集理论引入到战略性新兴产业企业信用评价中;同时,考虑到主观赋权法与客观赋权法各有优缺点,采用基于相对熵的组合赋权法确定指标权重,从而构建了基于相对熵和可变模糊集理论的战略性新兴产业企业信用评价模型.模型克服了现有模糊评价方法的不足,较好的兼顾了赋权的主观偏好和客观信息,提高了信用评价结果的可信度、可靠性与稳健性.以20家战略性新兴产业上市公司为样本,实证分析结果说明了模型的可行性和适用性.     

基于模糊理论的改进TOPSIS法在工程项目评标中的应用

评标过程会涉及到大量的定性分析,定性分析过程中受到专家的经验知识和主观判断的影响较大,因而所确定的指标权重和指标值带有较强的主观模糊性,易造成评标决策的失误.基于模糊数能量化主观模糊性并融合到指标权重与指标值中,采用模糊理论对TOPSIS法进行改进,评价指标权重和指标值均用梯形模糊数表示,建立基于模糊TOPSIS法的评标模型.结果表明,依据CC值不仅可以对投标人排序,而且还能客观的反应出投标人自身的优劣,避免了劣中选优的情况发生.最后通过示例对提议模型的应用过程及可行性进行了说明.     

基于综合权重的理想模糊物元多属性决策法及应用

研究了属性指标具有不相容性和模糊性及其指标的权重完全未知的模糊多属性决策问题.分析了目前广泛采用的模糊物元分析法以及仅有主观赋权法或客观赋权法确定其指标权重的缺点.根据物元可拓理论和理想解法的思想,定义了理想模糊物元和负理想模糊物元的概念.利用兼顾主观偏好和客观信息的综合权重赋值法,提出了基于综合权重的理想模糊物元多属性决策方法.该法既能充分利用指标本身所包含的客观信息,又能充分发挥决策者的主观能动性.实例研究结果表明该法能反映出决策方案间的细微差别,能对决策方案的优劣做出更准确有效的评价.     

基于灰色关联度—TOPSIS的县域经济社会发展综合评价研究

选择经济发展,社会发展,资源、生态环境三个层面,构建了体现科学发展观要求的县域经济社会发展综合评价指标体系.用客观赋权的熵值法确定各指标权重,结合灰色关联度和TOPSIS建立了综合评价模型,并对烟台市8个县市的经济社会发展状况进行实证分析.     

基于ANP与模糊TOPSIS-CRITIC方法的不确定多属性决策模型

随着多属性决策问题的日益流行,处理决策问题的复杂程度也逐渐增加,针对其中权重不确定,难以量化各影响因素主观权重与客观权重以及指标排序不精确的问题,提出了一种将网络层次分析法(ANP)与模糊指标相关性的指标权重确定法(CRITIC)、逼近理想解排序法(TOPSIS)相结合的不确定多属性决策模型首先,在分别使用ANP方法和CRITIC法确定各影响因素的主观、客观权重的基础上计算指标的综合权重,然后应用模糊TOPSIS方法对备选方案进行贴进度排序最后,通过一个实例将计算结果同其他三种决策方法进行对比分析,验证了所提出的ANP与模糊TOPSIS-CRITIC方法的可靠性和有效性.     

基于不完全权重信息下模糊多属性决策的供应链合作伙伴选择

针对属性权重完全未知或只有部分权重信息且属性值为三角模糊数的供应链合作伙伴选择问题,给出了一种模糊多属性决策方法.提出了一种基于置信度的定性指标的量化方法,通过求解最优化决策模型确定属性的权重,然后根据各方案到模糊理想点的相对贴近度的大小选择最优的合作伙伴.     

多属性决策的组合赋权法

鉴于多属性决策问题中主观赋权法和客观赋权法各有其自身固有的特点，本文依据优化理论提出一种集成方法确定属性权重，该方法既充分利用客观信息，又反映决策者的主观偏好，从而使确定的属性权重更加合理、实用．     

基于改进模糊综合评判的分销商评价研究

随着制造业逐渐向买方市场转变,供应链分销管理成为企业发展的驱动力之一。分销商在该环节发挥着关键作用,选择和管理分销商的前提是对其进行科学的评价。在回顾分销商评价方法的基础上,提出了基于模糊综合评判的分销商评价模型。针对传统模糊综合评判在指标赋权方面的不足,采用组合赋权法加以改进,首先对多种指标权数计算结果进行事前检验,根据检验结果确定最佳组合方式,然后通过事后检验保证组合权数的合理性。指标权数确定后,再经过因素集与评判集的确定、单因素评判、综合评判等阶段对分销商进行评价。最后将改进方法与传统方法进行了比较分析,并以某大型家电企业为例,验证了该方法能更为合理地解决分销商评价问题。     

Fuzzy multi-objective programming for supplier selection and risk modeling: A possibility approach

Selection of supply chain partners is an important decision involving multiple criteria and risk factors. This paper proposes a fuzzy multi-objective programming model to decide on supplier selection taking risk factors into consideration. We model a supply chain consisting of three levels and use simulated historical quantitative and qualitative data. We propose a possibility approach to solve the fuzzy multi-objective programming model. Possibility multi-objective programming models are obtained by applying possibility measures of fuzzy events into fuzzy multi-objective programming models. Results indicate when qualitative criteria are considered in supplier selection, the probability of a certain supplier being selected is affected.     

A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes

This work presents a new fuzzy multiple attributes decision-making (FMADM) approach, i.e., fuzzy simple additive weighting system (FSAWS), for solving facility location selection problems by using objective/subjective attributes under group decision-making (GDM) conditions. The proposed system integrates fuzzy set theory (FST), the factor rating system (FRS) and simple additive weighting (SAW) to evaluate facility locations alternatives. The FSAWS is applied to deal with both qualitative and quantitative dimensions. The FSAWS process considers the importance of each decision-maker, and the total scores for alternative locations are then derived by homo/heterogeneous group of decision-makers. Finally, a numerical example illustrates the procedure of the proposed FSAWS.     

Evaluating and selecting the supplier in detergent production industry using hierarchical fuzzy TOPSIS

Supply chain management has increasingly attracted attention as a systematic approach to integrate the supply chain in order to planning and controlling the materials and information from suppliers to customers. One of the most important issues in supply chain management is selection of the appropriate supplier which has significant effect on purchasing cost decrease and increase in the organization’s competition ability. Selection of the best supplier is naturally complex with no definite structure, and dependent on the type of suppliers’ activity. In the process of decision making about suppliers and many qualitative and quantitative performance indicators such as quality, price, flexibility, and due date should be considered. Then, the supplier selection problem is a multi-criteria decision making problem where numerous methods have been proposed to solve this problem so far. In the current paper, four suppliers of imported raw material “Tripolyphosphate (TPP)” (primary material to produce the detergent powder with a case study in Iran) are evaluated based on 25 effective criteria using the hierarchical fuzzy TOPSIS (HFTOPSIS) approach.     

Environmental supply chain network design using multi-objective fuzzy mathematical programming

The concern about environmental impact of business activities has spurred an interest in designing environmentally conscious supply chains. This paper proposes a multi-objective fuzzy mathematical programming model for designing an environmental supply chain under inherent uncertainty of input data in such problem. The proposed model is able to consider the minimization of multiple environmental impacts beside the traditional cost minimization objective to make a fair balance between them. A life cycle assessment-based (LCA-based) method is applied to assess and quantify the environmental impact of different options for supply chain network configuration. Also, to solve the proposed multi-objective fuzzy optimization model, an interactive fuzzy solution approach is developed. A real industrial case is used to demonstrate the significance and applicability of the developed fuzzy optimization model as well as the usefulness of the proposed solution approach.     

Group decision making based on novel fuzzy modified TOPSIS method

The aim of this paper is to present a novel fuzzy modified technique of order preference by a similarity to ideal solution (TOPSIS) method by a group of experts, which can select the best alternative by considering both conflicting quantitative and qualitative evaluation criteria in real-life applications. The proposed method satisfies the condition of being the closest to the fuzzy positive ideal solution and also being the farthest from the fuzzy negative ideal solution with multi-judges and multi-criteria. The performance rating values of alternatives versus conflicting criteria as well as the weights of criteria are described by linguistic variables and are transformed into triangular fuzzy numbers. Then a new collective index is introduced to discriminate among alternatives in the evaluation process with respect to subjective judgment and objective information. This paper shows that the proposed fuzzy modified TOPSIS method is a suitable decision making tool for the manufacturing decisions with two examples for the robot selection and rapid prototyping process selection.