地空导弹部队阵地选择方案决策模型研究

本文运用模糊数学原理和方法,结合地空导弹部队阵地选择的特点,给出了阵地选择评价因素指标体系,建立了阵地选择方案的二极模糊综合评判模型,并采用层次分析法(AHP)对阵地选择评价因素的权重进行了确定。最后,简单介绍了阵地选择模糊决策软件的设计方法。     

Partner selection in agile supply chains: a fuzzy intelligent approach

Partner selection is a fundamental issue in supply chain management as it contributes significantly to overall supply chain performance. However, such decision-making is problematic due to the need to consider both tangible and intangible factors, which cause vagueness, ambiguity and complexity. This paper proposes a new fuzzy intelligent approach for partner selection in agile supply chains by using fuzzy set theory in combination with radial basis function artificial neural network. Using these two approaches in combination enables the model to classify potential partners in the qualification phase of partner selection efficiently and effectively using very large amounts of both qualitative and quantitative data. The paper includes a worked empirical application of the model with data from 84 representative companies within the Chinese electrical components and equipment industry, to demonstrate its suitability for helping organisational decision-makers in partner selection.     

A qualitative perspective to deriving weights from pairwise comparison matrices

Deriving weights from pairwise comparison matrices (PCM) is a highly researched topic. The analytic hierarchy process (AHP) traditionally uses the eigenvector method for the purpose. Numerous other methods have also been suggested. A distinctive feature of all these methods is that they associate a quantitative meaning to the judgemental information given by the decision-maker. In contrast, the verbal scale used in AHP to capture judgements does not associate such a quantitative meaning. Though this issue of treating judgements qualitatively is recognized in the extant literature on multi-criteria decision making, unfortunately, there is no research effort so far in the AHP literature. Deriving motivation from the application of data envelopment analysis (DEA) for deriving weights, it is proposed in this paper that DEA models developed to deal with a mix of qualitative and quantitative factors can be used to derive weights from PCMs by treating judgements as qualitative factors. The qualitative DEA model is discussed and illustrated in this paper.     

基于修正Russell方法的模糊决策单元的排序

文章首先建立基于修正Russell方法的超效率DEA模型,然后基于模糊数的比较,建立并求解模糊环境下的基于修正Russell方法的超效率DEA模型,从而解决了模糊决策单元的全排序问题。文末的算例将基于修正Russell方法的模糊超效率DEA模型,与基于CCR模型的模糊超效率DEA模型的结果进行了比较分析。     

信息系统外包决策的AHP/PROMETHEE方法

针对信息系统外包项目优选这一重要问题,在已有方法的基础上,结合层次分析法与偏好顺序结构评估法,提出了一种基于这两种方法相结合的信息系统外包项目选择决策方法。以管理、战略、技术、经济、质量与风险6项因素作为评价准则,用层次分析法确定信息系统外包项目选择问题的层次结构与评价准则的权重,用偏好顺序结构评估法确定信息系统外包项目的排序,并通过算例说明该方法的有效性。     

混合指标层次模糊决策法研究

应用层次分析的思想和模糊模式识别方法,在引入模糊一致判断矩阵的基础上,提出了混合指标层次模糊决策方法.方法的主要特点是综合考虑了评价系统中的定性和定量指标,并提出了"表现度"的概念,使之更加客观真实地反映实际状况.然后通过模糊模式识别方法,得到系统的局部和整体发展水平评价.最后通过案例分析,表明该方法在实际运用中是有效的,具有实际应用价值.     

Applying consistent fuzzy preference relations to partnership selection

Partnership selection has been important to the formation of a virtual enterprise. Based on the fuzzy preference programming (FPP) method proposed by Mikhailov [Fuzzy analytical approach to partnership selection in formation of virtual enterprises. Omega 2002;30:393–401], this investigation presents a consistent fuzzy preference relations method to select partners. Human thoughts are full of uncertainty, so the decision-makers cannot make exact pairwise comparisons. The FPP method solves this problem using an interval value instead of Saaty's 1–9 scale. In this study, the FPP method is reviewed, and then the consistent fuzzy preference relations method is elucidated. Finally, the presented method is applied to the example addressed by Mikhailov [Fuzzy analytical approach to partnership selection in formation of virtual enterprises. Omega 2002;30:393–401]. This study reveals that the proposed method yields consistent decision rankings from only n-1$n-1$ pairwise comparisons—the same number as in Mikhailov's research. Briefly, the presented consistent fuzzy preference relations method is an easy and practical way to provide rankings of partnership in making decision.     

Reliability analysis of man–machine systems using fuzzy cognitive mapping with genetic tuning

This article offers a method for analyzing the reliability of a man–machine system (MMS) and ranking of influencing factors based on a fuzzy cognitive map (FCM). The ranking of influencing factors is analogous to the ranking of system elements the probabilistic theory of reliability. To approximate the dependence of “influencing factors—reliability,” the relationship of variable increments is used, which ensures the sensitivity of the reliability level to variations in the levels of influencing factors. The novelty of the method lies in the fact that the expert values of the weights of the FCM graph edges (arcs) are adjusted based on the results of observations using a genetic algorithm. The algorithm's chromosomes are generated from the intervals of acceptable values of edge weights, and the selection criterion is the sum of squares of deviations of the reliability simulation results from observations. The method is illustrated by the example of a multifactor analysis of the reliability of the “driver–car–road” system. It is shown that the FCM adjustment reduces the discrepancy between the reliability forecast and observations almost in half. Possible applications of the method can be complex systems with vaguely defined structures whose reliability depends very much on interrelated factors measured expertly.     

A fuzzy logic evaluation system for commercial loan analysis

This paper introduces an application of fuzzy logic to commercial loan analysis. It describes the fuzzy sets and linguistic variables that contribute to the financial evaluation. It also presents a computer-based Fuzzy Logic Evaluation System consisting of the components Specify Fuzzy Sets, Edit Rules, and Evaluator. The Evaluator performs fuzzification, evaluation, and defuzzification activities. Using company-specific and industry financial data, the current version of the system appraises a company's credit, capital, and capacity performance. A specific example for efficiency analysis illustrates the system constructs.     

基于AHP-标准离差的人的全面发展评价模型及其实证研究

通过人的全面发展评价指标的筛选和理性分析,构建了人的全面发展综合评价指标体系。用客观赋权的标准离差法和主观赋权的AHP法的组合确定指标最优权重,建立了基于科学发展观的人的全面发展综合评价模型,并对中国十五期间人的全面发展状况进行实证分析。     

Application of hybrid framework to facilitate lean six sigma implementation: a manufacturing company case experience

This study aims to propose a hybrid framework for lean six sigma (LSS) based on the prioritisation of barriers and solution approaches, to facilitate hassles free applications for handling the challenges of wastes reduction and quality improvement. The study identifies 27 LSS barriers and 22 solution approaches through literature review and utilises feedback from industry experts. For framework, study uses fuzzy AHP-PROMETHEE to prioritise LSS barriers and solution approaches. Incorporating fuzzy sets in analytical hierarchy process (AHP) ensures the optimality of barrier weights. Whereas, preference ranking organisation method for enrichment of evaluations (PROMETHEE) helps in pairwise comparisons of solution approaches with respect to each LSS barrier, facilitating fair judgements. This research guides regarding the development of framework and checks its suitability and robustness through case application of an Indian manufacturing organisation. Authors expect that researchers and practitioners will find study useful for LSS and multi criteria decision making(MCDM) domains.     

居民旅游影响感知的模糊综合评价

为研究旅游对旅游目的地的影响,将模糊综合评价的方法应用到居民旅游影响感知的研究之中,设计居民旅游影响感知的评价指标体系,采用层次分析法确定指标权重,经过聚集各指标模糊矩阵和去模糊的过程,对居民的旅游感知进行测量,并以九寨沟居民对旅游影响的感知为例对该方法给予说明。     

Prioritising indicators in improving supply chain performance using fuzzy AHP: insights from the case example of four Indian manufacturing companies

Abstract

In this contribution, we aim to prioritise the indicators to enhance the organisational supply chain’s (SC) effectiveness from an industrial perspective. It will help industries to develop strategies for managing the SC effectively and ensuring improvement in performance continuously. To achieve this, this work proposes to use a two-phase research methodology. First, 36 SC performance improvement indicators are recognised from a literature survey and from field and industrial expert’s inputs. Secondly, a structural model is proposed using the fuzzy analytical hierarchy process (AHP) to prioritise the indicators strategically to improve the SC performance. The fuzzy AHP method helps determine the priority of concerns of the identified indicators under fuzzy surroundings. Inputs in this research are taken from four ancillary Indian plastic manufacturing firms. Research findings indicate that collaborations and information exchange dimension indicators obtained the highest priority in improving SC performance. The model proposed is considered very useful for the SC managers/practitioners/decision-makers to understand better and distinguish the essential SC performance improvement indicators and to take systematic decisions specifically to improve the performance of business in a SC context. Sensitivity analysis was conducted to examine the priority ranking of the indicators.     

A slack-based measure of efficiency in context-dependent data envelopment analysis

Data envelopment analysis (DEA) has been proven as an excellent data-oriented performance evaluation method when multiple inputs and outputs are present in a set of peer decision-making units (DMUs). In the DEA literature, a context-dependent DEA is developed to provide finer evaluation results by examining the efficiency of DMUs in specific performance levels based upon radial DEA efficiency scores. In DEA, non-zero input and output slacks are very likely to present after the radial efficiency score improvement. Often, these non-zero slack values represent a substantial amount of inefficiency. Therefore, in order to fully measure the inefficiency in DMU's performance, it is very important to also consider the inefficiency represented by the non-zero slacks in the context-dependent DEA. This study proposes a slack-based context-dependent DEA which allows a full evaluation of inefficiency in a DMUs performance. By using slack-based efficiency measure, we obtain different frontier levels and more appropriate performance benchmarks for inefficient DMUs.     

我国海外石油开发利用的国家风险评估

在对我国海外石油开发利用国家风险因素进行分析的基础上,运用模糊综合评判法构建海外石油开发利用风险评估模型,并基于层次分析法对相关风险指标体系进行权重确定;同时,选取了我国海外石油开发利用涉及的一些典型地区或国家进行石油开发利用风险评估。研究发现:政治风险是影响海外石油开发利用的非常重要风险因素;我国在中东地区进行石油开发利用的风险最大,其次是西非、北非以及俄罗斯地区。     

Partner selection for reverse logistics centres in green supply chains: a fuzzy artificial immune optimisation approach

The design of reverse logistics networks has now emerged as a major issue for manufacturers, not only in developed countries where legislation and societal pressures are strong, but also in developing countries where the adoption of reverse logistics practices may offer a competitive advantage. This paper presents a new model for partner selection for reverse logistic centres in green supply chains. The model offers three advantages. Firstly, it enables economic, environment and social factors to be considered simultaneously. Secondly, by integrating fuzzy set theory and artificial immune optimisation technology, it enables both quantitative and qualitative criteria to be considered simultaneously throughout the whole decision-making process. Thirdly, it extends the flat criteria structure for partner selection evaluation for reverse logistics centres to the more suitable hierarchy structure. The applicability of the model is demonstrated by means of an empirical application based on data from a Chinese electronic equipment and instruments manufacturing company.     

存在保证域的模糊非径向偏好DEA模型——基于中科院24个研究所的实证分析

数据包络分析（DEA）是一种非参数化的方法,用于评价具有类似输入和输出的决策单元的效率。传统的非径向DEA模型假设输入和输出数据均为准确值,且对权重变量不加以限制,本文构建了存在保证域的模糊非径向偏好DEA模型,并给出了一种基于模糊数截集的模型求解方法,有效地解决了输入和输出全部或部分为模糊数的决策单元评价问题。最后给出了一个中科院研究所效率评价的实例说明了方法的有效性。     

Assessing the performance of business colleges in Taiwan using data envelopment analysis and student based value-added performance indicators

The purpose of this study is to construct a student-based performance evaluation model for business schools in Taiwan. College graduates’ starting wage and their multiple abilities cultivated in school are used as performance indicators. The value-added forms of these indicators are employed to assess the pure impact of school on graduate's performance. To prevent impractical indicator weights, we incorporate job market recruiters’ weights from an AHP survey into the assurance region data envelopment analysis (AR-DEA) for empirical analysis. Empirical results show that the public schools on average outperform the private schools. However, there are still some private schools that perform better than the public ones. Besides, in regard to the discriminatory power and the distribution of output weights, the proposed AR-DEA is better than DEA in measuring the performance of the business colleges in Taiwan.     

超效率DEA模型的模糊扩展

在输入、输出数据为模糊数而效率值为准确值的模糊DEA模型中,会出现有两个以上有效单元,从而无法对所有决策单元进行全排序的情形。本文利用模糊数的基于α-截集的比较规则,建立了模糊条件下的超效率DEA模型,有效地解决了模糊决策单元的全排序问题。文末给出了一个实例。     

Pitfalls of decomposition weights in the additive multi-stage DEA model

This paper examines limitations of the multi-stage DEA (data envelopment analysis) model in the literature. We focus on the DEA model with additive efficiency decomposition. We create taxonomy for the multi-stage DEA models and show when the decomposition weights can be non-increasing. When the decomposition weight for a stage is deemed reflective of the stage׳s relative importance, this property then implies that upstream stages (regardless the stage efficiency scores) in the model will obtain higher priority in efficiency decomposition. We also find that the non-increasing weights can affect the evaluation of overall and stage efficiency scores. We illustrate our findings through an empirical data set.