基于偏好的供应链不确定型风险模糊评估方法研究

提供一种供应链不确定型风险新的主观评估方法.本文在分析供应链不确定型风险评估中含有一定偏好特性的基础上,利用模糊理论和风险评估方法建立数学模型并求解,得出供应链风险水平,最后利用实例验证了方法的可行性和准确性.利用模糊理论和风险评估方法是评估供应链不确定型风险的有效方法.     

基于风险网络的大型工程项目风险度量方法研究

风险度量是风险管理的基础,提出适合大型工程项目风险的风险度量方法.针对大型工程项目风险因素、风险信息、风险损失之间的复杂联系,构建大型工程项目风险网络,分别采用贝叶斯网络推理和网络层次分析法获得风险发生概率和风险量的估计,从而提出基于风险网络的大型工程项目风险度量方法.方法将风险损失量和风险损失发生概率进行了明确合理的结合,既可用于度量客观风险,也可用于度量主观风险.最后以槽菁头隧道施工风险管理为例说明该方法的具体应用步骤和效果.     

企业并购中风险的识别与评估研究

为准确识别、度量和降低企业并购风险,在对企业并购因素进行识别和定性分析基础上,建立了一套较全面的企业并购风险多层次评估指标体系,同时利用未确知理论给出了一种适合企业并购特点的未确知测度风险评估模型.模型结构严谨、精细,并通过实例验证了该评估模型的科学有效性.     

未决赔款准备金评估的对数正态模型及其预测分布的Bootstrap实现

目前在我国精算实务中对未决赔款准备金评估的不确定性风险逐渐重视,对不确定性加以度量显得很有必要.在以往关于未决赔款准备金的不确定性研究中,大多集中于预测均方误差.从数值角度看,如果应用随机模拟的方法,能得到未决赔款准备金完整的预测分布,那么就可以由该分布得到各个分位数以及相关的分布度量,对准备金负债评估的准确性和充足性具有重要的参考价值.研究的对数正态模型是未决赔款准备金评估中的分布模型之一,它假设累计赔款单个进展因子服从对数正态分布,进而将参数Bootstrap方法和非参数Bootstrap方法应用于对数正态模型中,得到了未决赔款准备金的预测分布,并通过精算实务中的数值实例加以实证分析.数值实例由当前国际上日益流行的统计软件R加以实现.     

基于联系数的组合赋权电能质量评估

由于电能质量指标的多样性,科学地综合评估电能质量存在一定的困难.针对目前电能质量评价时指标组合赋权中普遍存在的不确定性,把联系数引入组合赋权研究.首先把同一指标的主观赋权值与客观赋权值用区间数表示,再把此区间数转换成集对分析中的联系数,并计算出联系数的模,然后把模作为主观权重和客观权重的相互作用值给指标定权,最后利用不确定系数i开展综合评估初值的不确定性分析,检验其综合评估结果的稳定性,据此确定所评电能质量等级,提高了评估结论的科学性和可靠性.     

基于熵权可拓模型的深大基坑施工风险评估

随着人们对地下空间的不断开发、利用,深大基坑逐渐增多.深大基坑施工技术较为复杂,施工过程中存在的风险因素较多,一旦风险发生损失严重,因此,对深大基坑风险进行评估十分必要.首先,介绍深大基坑风险评估的主要方法及研究不足,通过文献研究及专家调查法识别深大基坑施工过程中存在的主要风险;其次,采用AHP确定评估指标主观权重,采用熵权法确定指标客观权重,根据最小熵原理将主客观权重进行组合,获得最终权重.基于该权重建立深大基坑施工风险评估可拓模型,模型综合考虑了风险发生的概率及带来的损失,将风险定级;最后,结合某地铁站深大基坑进行实例研究,得出深大基坑施工过程中风险等级为u4级,即风险较高的结论,并给出了一些合理建议.     

基于密切值法的组合赋权多属性决策方法研究

分析主观赋权、客观赋权方法在实际应用中的不足,运用密切值法原理,对多属性决策问题的权重确定采用主观赋权法与客观赋权法相结合的组合赋权思路,完善多属性决策问题的决策方法,并举例说明其合理性.     

基于Vague集的领导干部绩效考评

在政府职能的转变过程中,如何评价各级领导的绩效问题一直是选拔任用干部工作的重要内容之一.论文通过对领导干部绩效考评指标体系的分析,遴选了一组一般性的指标,并借助vague集方法对领导干部的绩效进行了评估.评价环节中,以主观评价作为基础,同时引入客观评价法并运用差异性分析技术,以增强主观评价指标的准确性,这一方法的运用为领导干部的绩效考评提供了一种新的思路和方法.     

基于熵值法的区域旅游业经济效益比较分析

为了克服区域旅游业经济效益比较分析中采用主观赋权法所带来的局限性,于是借助于信息工程学中的“熵”概念,利用熵的大小度量各指标在不同区域旅游业之间的差异程度,较为客观地揭示出各指标的重要性,同时也给出了基于熵值法的比较分析实例。     

基于熵权理论的模糊风险评估方法在网络系统中的应用

针对信息系统风险评估中过分依赖主观赋值的现象,提出一种基于熵权理论的模糊风险评估方法,并将其应用于校园网络系统风险评估.构建了校园网络系统风险评估的递阶层次结构模型,结合层次分析法和模糊逻辑法对各风险因素的风险值进行分析,评价系统中值得关注的风险因素.在此基础上通过熵权理论计算整个系统的风险度以评价校园网络系统的总体风险情况,通过实例分析表明该方法可行有效.     

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。     

Stochastic utility-efficient programming of organic dairy farms

Opportunities to make sequential decisions and adjust activities as a season progresses and more information becomes available characterise the farm management process. In this paper, we present a discrete stochastic two-stage utility-efficient programming model of organic dairy farms, which includes risk aversion in the decision maker’s objective function as well as both embedded risk (stochastic programming with recourse) and non-embedded risk (stochastic programming without recourse). Historical farm accountancy data and subjective judgements were combined to assess the nature of the uncertainty that affects the possible consequences of the decisions. The programming model was used within a stochastic dominance framework to examine optimal strategies in organic dairy systems in Norway.     

Three steps multiobjective decision process for software release planning

This paper deals with how to determine which features should be included in the software to be developed. Metaheuristic techniques have been applied to this problem and can help software developers when they face contradictory goals. We show how the knowledge and experience of human experts can be enriched by these techniques, with the idea of obtaining a better requirements selection than that produced by expert judgment alone. This objective is achieved by embedding metaheuristics techniques into a requirements management tool that takes advantage of them during the execution of the development stages of any software development project. © 2015 Wiley Periodicals, Inc. Complexity 21: 250–262, 2016     

Securitization, structuring and pricing of longevity risk

Pricing and risk management for longevity risk have increasingly become major challenges for life insurers and pension funds around the world. Risk transfer to financial markets, with their major capacity for efficient risk pooling, is an area of significant development for a successful longevity product market. The structuring and pricing of longevity risk using modern securitization methods, common in financial markets, have yet to be successfully implemented for longevity risk management. There are many issues that remain unresolved for ensuring the successful development of a longevity risk market. This paper considers the securitization of longevity risk focusing on the structuring and pricing of a longevity bond using techniques developed for the financial markets, particularly for mortgages and credit risk. A model based on Australian mortality data and calibrated to insurance risk linked market data is used to assess the structure and market consistent pricing of a longevity bond. Age dependence in the securitized risks is shown to be a critical factor in structuring and pricing longevity linked securitizations.     

基于多属性群决策的软件可靠性模型选择方案

基于模型评价准则的属性值和专家经验的偏好信息进行软件可靠性增长模型的选择,可归结为多属性群决策问题.模型评价准则的主观专家偏好可利用层次分析方法将其量化得到其主观排序权重;基于失效数据的模型评价准则的计算数据可利用熵权法获得客观排序权重.综合两种权重可得到既能反映专家经验又能综合实际软件可靠性测试数据的模型评价方案.实例分析表明该方案具有合理性和可行性.     

Methods for the external validation of contiuous system simulation models:a review

External validation is an integral part of the process of simulation model development. Many methods of external validation of continuous system simulation models have been proposed and, inevitably, the approach selected in any given application is highly dependent upon the purpose of the model and the associated accuracy requirements. Although the process of external validation has subjective aspects, formalisation of methods in some safety-critical fields of application has provided a basis for the development of objective measures of model performance. Such measures can be applied in other application areas and allow the whole process of assessing model credibility to be put on a firmer foundation. This paper reviews available methods, discusses practical issues that can arise in the application of these validation techniques and gives a brief account of some validation problems in selected application areas.     

Imprecise probabilities for representing ignorance about a parameter

This paper distinguishes between objective probability—or chance—and subjective probability. Most statistical methods in machine learning are based on the hypothesis that there is a random experiment from which we get a set of observations. This random experiment could be identified with a chance or objective probability, but these probabilities depend on some unknown parameters. Our knowledge of these parameters is not objective and in order to learn about them, we must assess some epistemic probabilities about their values. In some cases, our objective knowledge about these parameters is vacuous, so the question is: What epistemic probabilities should be assumed? In this paper we argue for the assumption of non-vacuous (a proper subset of [0, 1]) interval probabilities. There are several reasons for this; some are based on the betting interpretation of epistemic probabilities while others are based on the learning capabilities under the vacuous representation. The implications of the selection of epistemic probabilities in different concepts as conditioning and learning are studied. It is shown that in order to maintain some reasonable learning capabilities we have to assume more informative prior models than those frequently used in the literature, such as the imprecise Dirichlet model.     

Indirect assessment of the bivariate survival function

Estimating the bivariate survival function has been a major goal of many researchers. For that purpose many methods and techniques have been published. However, most of these techniques and methods rely heavily on bivariate failure data. There are situations in which failure time data are difficult to obtain and thus there is a growing need to assess the bivariate survival function for such cases. In this paper we propose two techniques for generating families of bivariate processes for describing several variables that can be used to indirectly assess the bivariate survival function. An estimation procedure is provided and a simulation study is conducted to evaluate the performance of our proposed estimator.     

An integrated approach for risk response development in project planning

The risk response development phase is a major phase in the project risk management process. We present a model that integrates project work contents, risk events, and risk reduction actions and their effects into a comprehensive framework. The model allows the representation of the overlapping effects of multiple risk reduction actions and of the impacts of secondary risk events, and supports the evaluation of the total risk exposure of the project under various combinations of risk reduction actions. The model can be treated with optimisation techniques in order to generate the most cost-effective combination of risk reduction actions. In this work we describe the model, outline a solution procedure and illustrate its application with an example taken from the software industry.