用模糊综合评价方法选择虚拟企业合作伙伴的研究

提出了采用模糊综合评价的方法解决虚拟企业候选合作伙伴的选择问题,包括用层次分析法确定模糊评价的权系数,建立虚拟企业伙伴选择的模糊评价数学模型.并结合具体应用进行了实例分析,证明了该方法的有效性.     

基于AHP-FCE的供应商选择问题研究与应用

文中在对现有供应商选择方法分析的基础上,利用层次分析法在确定各指标的权重方面以及综合模糊评价法在处理多指标多层次的综合评价问题方面的优点,提出了基于层次分析法和综合模糊评价法相结合的供应商选择方法,并且详细描述了供应商选择的步骤。该方法将定性和定量分析有机地结合起来,能够充分体现评价因素和评价过程的模糊性,减少了个体主观臆断所带来的弊端。经过在钢材采购管理决策支持系统中的应用,证明了该方法符合客观实际,评价结果可信、可靠。     

视频对象分类特征评价与选择方法

视频对象自动分类是智能视频监控的重要技术基础之一.为了提高分类精度,必须选择合适的对象特征.目前常用的视频对象分类方法都缺乏对于分类特征重要性的评价机制.提出一种视频对象分类特征评价与选择方法,该方法基于Adaboost算法的思想,通过对特征贡献进行定量评价实现特征选择.实验将视频对象区分为"单个行人"、"人群"、"车辆"和"骑车的人"四种类别,证明了该方法的合理性和有效性.     

改进的最大相关最小冗余特征选择方法研究

特征选择方法作为重要的数据预处理工作一直受到各个领域的关注。在分析现有的特征选择方法的基础上,针对MRMR方法中存在的冗余度和相关性评价方法单一,不能根据用户需求设置特征维度等问题进行了改进。在冗余度计算过程提出一种新的简单快速的计算方法;在计算权重过程中提出针对不同数据选用不同的特征评价方法;引入新的目标评价函数来进行特征选择。在五个经典的用于生物认证领域的特征数据库（FERET、CASIA、ORL、PIE和扩展的YaleB）上验证了算法的有效性,实验结果充分证明了改进的最大相关最小冗余算法的优势。     

基于互信息的文本分类改进方法研究

传统的LDA主题模型没有考虑词频对主题分类的影响,使得主题分布向高频词倾斜。为了综合考虑词频和主题间的相关性,文中利用互信息能够表达变量间相关性的特点,在互信息基础上改进作为特征选择方法,利用评价函数评价特征词的权重值改进LDA算法分类过程,提高对主题分类贡献度高的特征词的作用。通过在新闻语料库上的分类实验证明了该方法的有效性,同时表明分类的准确率也有所提高。     

基于组件开发的组件选择过程*

组件的选择是影响基于组件开发项目成功的决定性因素之一。目前组件选择存在着四方面问题,即组件选择过程没有定义,组件评价准则的定义没有得到足够重视,实际采用评价组件的方法往往缺乏客观性,理论研究提出的方法往往可操作性差。针对这些问题,提出了一个组件选择过程模型,该模型包含搜寻、筛选、评价和分析四个子过程;最后通过一个应用案例,详细说明了该组件的选择过程。     

数据挖掘在供应商选择中的应用

针对供应链国际化趋势的背景下,传统供应商选择方法已无法实现对供应商进行合理选取要求,以建立一套适合企业的、科学的、合理的供应商评价体系来进行供应商选择为目标,从供应商评价指标体系建立的原则、建立过程及各评价指标的计算方法几方面对BP神经网络分类方法进行介绍,阐述了运用数据挖掘知识从大量的供应商中选择出最适合企业的供应商的方法和过程。     

基于互信息的无监督特征选择

在数据分析中,特征选择可以用来降低特征的冗余,提高分析结果的可理解性和发现高维数据中隐藏的结构.提出了一种基于互信息的无监督的特征选择方法(UFS-MI),在UFS-MI中,使用了一种综合考虑了相关度和冗余度的特征选择标准UmRMR(无监督最小冗余最大相关)来评价特征的重要性.相关度和冗余度分别使用互信息来度量特征与潜在类别变量之间的依赖和特征与特征之间的依赖.UFS-MI同时适用于数值型和非数值型特征.在理论上证明了UFS-MI的有效性,实验结果也表明UFS-MI可以达到与传统的特征选择方法相当甚至更好的性能.     

一种提高推荐多样性的概率选择模型

传统的推荐算法多以优化推荐列表的精确度为目标,而忽略了推荐算法的另一个重要指标——多样性。提出了一种新的提高推荐列表多样性的方法。该方法将列表生成步骤转换为N次概率选择过程,每次概率选择通过两个步骤完成:类型选择与项目选择。在类型选择中,引入项目的类型信息,根据用户对不同项目类型的喜好计算概率矩阵,并依照该概率矩阵选择一个类型;在项目选择中,根据项目的预测评分、项目的历史流行度、项目的推荐流行度3个因素重新计算项目的最终得分,选择得分最高的项目推荐给用户。通过阈值TR来调节多样性与精确度之间的折中。最后,通过对比实验证明了该方法的有效性。     

噪声环境下精英克隆选择算法的收敛性分析

利用随机过程相关理论对加性噪声环境下精英策略克隆选择算法(ECSA)的全局收敛性进行了研究. 首先采用有序对的状态表示方法构造精英克隆选择算法在噪声环境中的Markov链; 然后将算法种群中最佳亲和度函数的进化过程转化为下鞅, 利用鞅理论证明了种群最佳亲和度函数的全局收敛性; 最后通过分析加性噪声环境下精英克隆选择算法的状态转移概率的特性, 证明了精英克隆选择算法在加性噪声环境下最终能以概率1 收敛到全局最优解.     

Structured methodology for supplier selection and evaluation in a supply chain

Supply chain management (SCM) is one of the most important competitive strategies used by modern enterprises. The main aim of supply chain management is to integrate various suppliers to satisfy market demand. Meanwhile, supplier selection and evaluation plays an important role in establishing an effective supply chain. Traditional supplier selection and evaluation methods focus on the requirements of single enterprises, and fail to consider the entire supply chain. Therefore, this study proposes a structured methodology for supplier selection and evaluation based on the supply chain integration architecture.In developing the methodology for supplier selection and evaluation in a supply chain, enterprise competitive strategy is first identified using strengths weaknesses opportunities threats (SWOT) analysis. Based on the competitive strategy, the criteria and indicators of supplier selection are chosen to establish the supplier selection framework. Subsequently, potential suppliers are screened through data envelopment analysis (DEA). Technique for order preference by similarity to ideal solution (TOPSIS), a multi-attribute decision-making (MADA) method is adapted to rank potential suppliers. Finally, the Taiwanese textile industry is used to illustrate the application and feasibility of the proposed methodology.This study facilitates the improvement of collaborator relationships and the management of potential suppliers to help increase product development capability and quality, reduce product lifecycle time and cost, and thus increase product marketability.     

基于优化神经网络的云计算环境下供应链伙伴选择

针对云计算环境下供应链伙伴的动态性,提出一种基于优化神经网络的云计算环境下供应链伙伴选择模型.首先构建计算环境下供应链伙伴评价指标体系,并采用层次分析法计算每一个指标的权值,然后采用神经网络对采集的企业评估训练样本进行学习,并采用遗传算法对神经网络参数进行优化价,建立企业综合评估模型,最后进行了仿真模拟实验.结果表明,本文模型可以准确描述供应链伙伴的动态性,能够对云计算环境下的供应链伙伴进行全面、公正的评价.     

A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information

Both academic and corporate interest in sustainable supply chains has increased in recent years. Supplier selection process is one of the key operational tasks for sustainable supply chain management. This paper examines the problem of identifying an effective model based on sustainability principles for supplier selection operations in supply chains. Due to its multi-criteria nature, the sustainable supplier evaluation process requires an appropriate multi-criteria analysis and solution approach. The approach should also consider that decision makers might face situations such as time pressure, lack of expertise in related issue, etc., during the evaluation process. The paper develops a novel approach based on fuzzy analytic network process within multi-person decision-making schema under incomplete preference relations. The method not only makes sufficient evaluations using the provided preference information, but also maintains the consistency level of the evaluations. Finally, the paper analyzes the sustainability of a number of suppliers in a real-life problem to demonstrate the validity of the proposed evaluation model.     

A model of a decision support system based on case-based reasoning for third-party logistics evaluation

The social demands for third‐party logistics (3PL) are further developing the model of supply chain management. The analysis of an effective approach for 3PL service supplier evaluation is given in terms of its direct relation to the operational efficiency and benefit of the service‐demanding enterprise as well as its supply chain management. An analysis of the traditional academic theoretical results and practical methods for 3PL supplier selection indicates the deficiencies of this approach. In this paper, a case‐based reasoning model framework is postulated for a 3PL evaluation and selection system. This work further expands upon the theoretical basis of this system and its reasoning process by discussing the advantages and practical value of this framework.     

GA和SVM在供应链绩效评价中的应用

研究了基于遗传算法和支持向量机的供应链绩效评价问题。将供应链绩效评价问题用遗传算法进行特征选择并同时对支持向量机参数进行了优化。研究表明该方法能提取出影响供应链绩效的重要属性,减小供应链评价模型的复杂度。应用实例表明基于遗传算法和支持向量机的评价结果从整体上要优于标准支持向量机的评价结果。     

AHP的改进算法及其在供应链中的应用

针对层次分析法（AHP）在群组决策应用中的不足,例如当AHP算法实际应用时,对其残缺矩阵、专家权重不同以及可信度等情况考虑不足,故将多目标决策中的可能满意度引入相容性检验与改进,提出了基于可能满意度的判断矩阵相容性修正及排序的改进AHP算法。接着分析影响节点企业选择的诸多因素,提出了两层评价指标体系。在此基础上应用改进的AHP算法建立节点企业选择模型。最后所采用一个实际的案例来验证所提算法的有效性和模型的可行性。     

Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process

The basic concept in axiomatic design (AD) is the existence of design axioms. First of these axioms is the independence axiom and the second one is the information axiom. Information axiom proposes the selection of the best alternative that has minimum information. Analytic hierarchy process (AHP) is another multi-attribute method which is a decision-making method for selecting the best among a set of alternatives, given some criteria. The method has been extensively applied, especially in large-scale problems where many criteria must be considered and where the evaluation of alternatives is mostly subjective. Multi-attribute transportation company selection is a very important activity for effective supply chain. Selection of the best company under determined criteria (such as cost, time, damage/loss, flexibility and documentation ability) using both multi-attribute AD and AHP will be realized in this study. The fuzzy multi-attribute AD approach is also developed and it is compared by one of fuzzy AHP methods in the literature. The selection process has been accomplished by aiding a software that includes crisp AD and fuzzy AD.     

Logistics tool selection with two-phase fuzzy multi criteria decision making: A case study for personal digital assistant selection

Efficient logistics and supply chain management are enabled through the use of efficient information technologies (IT). The mobile logistics tools represent the IT interface in the supply chain. This paper aims to aid decision makers to identify the most appropriate mobile logistics tools and to achieve this aim, several evaluation criteria are identified to evaluate logistics tools, and a fuzzy axiomatic design (FAD) based group decision-making method is adopted to perform the evaluation in two phases. In the first phase of pre-assessment, alternatives that cannot meet basic requirements and the defined threshold are eliminated. In the second phase of selection, the remaining alternatives are more meticulously evaluated. Criteria weights are determined using fuzzy analytic hierarchy process (AHP) and another fuzzy multi-criteria decision-making (MCDM) technique, namely fuzzy technique for order preference by similarity to ideal solution (TOPSIS), is applied in the second phase to compare the outcome of FAD. A case study is provided in order to demonstrate the potential of the proposed methodology. Personal digital assistants (PDAs) with integrated barcode scanner that are available in the Turkish market are evaluated.     

面向敏捷供应链的知识服务选择模型研究

为了实现敏捷供应链知识服务体系,针对知识服务组合中的服务选择问题,提出一种结合敏捷供应链特点和整数规划方法的知识服务选择模型。该模型考虑知识用户需求的QoS全局约束,采用线性加权方法将知识用户多目标转化为单目标。应用Matlab优化工具中的bintprog求解器进行模型实例求解,结果表明模型最终求解能满足用户的实际需求,对敏捷供应链知识服务选择方法和服务组合研究有一定的借鉴性。     

供应商协同能力评价指标体系研究

供应链协同已经成为供应链集团在与其他集团之间日趋激烈的竞争中创造竞争优势的势在必行的现代管理战略,供应商选择对供应链协同至关重要。通过控制进化种群划分与进化过程,利用压缩变异与Gauss变异设计一种组合变异方式,进而提出改进的模糊C-均值聚类遗传算法（IFCMGA）;在初步确定面向供应链协同的供应商评价指标后,利用IFCMGA算法对供应商协同能力评价指标进行分类,构建了面向供应链协同的供应商评价指标体系。结合模糊层次分析法与重要指标筛选法进行指标分析和筛选以及指标体系重构,以为供应商评价与选择提供科学决策依据。