【作者】 蔡丽丽；

【导师】 宋福根；

【作者基本信息】 东华大学 ， 管理科学与工程， 2008， 博士

【摘要】 市场经济条件下,经济形势瞬息万变,企业间的竞争日趋激烈,供应链管理研究正方兴未艾。欲使企业在激烈的竞争中求生存、谋发展,不仅要求企业在自身的研发、销售、生产和采购等诸多方面寻求突破,更要求企业在供应链管理上挖掘潜力,降低企业经营成本、提高企业经济效益和市场竞争力。供应链采购位于企业供应链管理源头,统计表明,采购成本在企业、尤其是在制造型企业的经营成本中占有很大的比重。因此,基于供应链管理基本原理,依据市场销售和产品生产需要,正确制订企业物料需求计划,科学进行供应商评价与选择,优化物料订购决策方案,对完善企业经营决策,降低企业经营风险,提高企业经济效益和市场竞争力有着十分重要的现实意义。本文就基于供应链管理的物料需求计划制订、供应商评价与选择和物料订货优化决策等进行了深入的研究,并将其融合成为一个有机的过程和整体,在此基础上,结合仿真技术,完成了采购优化决策支持系统的分析、设计与实施,主要研究内容有:(1)全面论述了基于供应链的采购建模与优化策略研究背景,系统总结了供应链及采购建模和优化策略的国内外研究现状,在此基础上介绍了本文的研究意义、研究内容、研究方法以及创新点。(2)深入研究了供应链管理的基本思想和特点,阐述了采购管理与决策的内涵、发展及其演化过程,区别了供应链采购与传统采购的不同点,并重点论述了采购管理与决策在供应链中的重要地位和作用,进而提出了基于联合计划、预测与补货(CPFR)的供应链采购优化策略。(3)从两个方面——采购流程和采购内容进行了采购优化策略的研究。对基于供应链的采购流程进行了分析,在信息共享的基础上,优化采购流程、减少中间环节。同时提出了物料需求、供应商评价与选择和订货优化决策三方面综合考虑的采购内容优化,重点分析了交叉的多产品多时段物料需求确定。(4)在评述供应商评价与选择内容和指标的基础上,将统计学习理论中的前沿方法——支持向量机运用到采购内容优化的供应商评价与选择中,简化了大量数据的运算过程,通过算例的仿真,进一步说明了该方法的实际可操作性和优越性。(5)在确定物料需求和供应商的基础上,为订货优化决策建立模型,通过模型的优化,确定采购批量,减少成本。并采用模糊多目标规划建模,研究了多供应商时的订货量分配决策。(6)运用系统仿真技术,将物料需求、供应商评价与选择和订货优化决策三者贯通,自主开发了一套可灵活运用的采购优化决策支持系统。通过研究,论文主要在以下四个方面实现了创新:一是基于供应链管理思想的新视角,贯通物料需求、供应商评价与选择、订货优化策略等主要采购管理与决策内容间的内在联系。二是将统计学习理论中的前沿方法——支持向量机应用在供应商评价与选择中,简化了供应商选择的过程,提高了供应商评价与选择的效率。三是在订货优化决策中运用模糊多目标决策方法确定多供应商间的订货量分配情况,降低采购风险,优化订货分配策略。四是把采购优化策略理论与现代信息技术相结合,运用ASP.NET和SQL Server技术,设计实施了基于供应链的采购优化决策支持系统。更多还原

【Abstract】 Under market-economy conditions,the economic situation changes rapidly,the competition between enterprises is quite fury and the research of supply chain management is in the ascendant.In order to survive and develop in the fierce competition,enterprises have to seek breakthrough in R&D,marketing,production and purchase,they also have to exploit their potential in supply chain management to reduce business cost and increase enterprises’ profit and market competitive strength.Supply chain purchase is the headstream of enterprise’s supply chain management.The statistics shows purchase cost in enterprises takes a large proportion,especially in the operation cost of manufacturing industry.Therefore,based on the fundamental principle of supply chain management, according to marketing and product requirement,to draw up right material requirement planning,evaluate and selecte suppliers scientifically and optimize material order decision-making have very important practical significances for enterprises to consummate operation decision,reduce business risks,boost economy benefit and enforece market competitive strength.This paper makes an intensive study of material requirement planning,supplier evaluation and selection and order optimization decision-making.It integrates all these aspects into a whole organic process.On this basis,we apply simulation technology to carry out the analysis,design and implementation of purchase optimization decision support system.The main research works are as follows:(1) Presenting a survey on background and status of relevant research in purchase modeling and optimization strategy based on supply chain.Additional,offering an introduction on the significance,contents,methods and innovations of this research.(2) Making further research in the basic ideology and characteristics of supply chain management,and introducing the conception,development and evolvement of purchase management and decision.We also distinguish the differences between traditional purchase and purchase based on supply chain.We analyze the important status and function of purchase management and decision in supply chain and put forward supply chain purchase optimization strategy based on CPFR.(3) Making a study on the strategy for purchase optimization from the two aspects of purchase flow and purchase content.We analyze purchase flow based on supply chain,on the basis of information sharing,we optimize purchase flow and reduce needless midterm links.At the same time,we synthetically consider purchase content optimization from three aspects material requirement,supplier evaluation and selection and order optimization decision-making.We emphasize crossed multi-product and multi-period material requirement.(4) Based on the criterion of supplier evaluation and selection,we apply support vector machine(SVM) to solve supplier evaluation and selection for purchase optimization. This method predigests operation process of a great deal data.A case study shows practical maneuverability and advantage of this method.(5) After determining the suppliers and material requirement,we build up purchase order optimization models to fix purchase batch and reduce cost.In addition,we use fuzzy multi-object programming to analyze multi-supplier order distribution.(6) Finally,by making use of system simulation technology,we independently develop a purchase optimization decision support system with a high degree of flexibility. This system integrates three aspects of material requirement,supplier evaluation and selection and order optimization decision-making.Based on above research,this paper has four innovations:Firstly,this paper finds a new perspective in supply chain management theory,and perforates the links among three aspects in purchase management and decision content: material requirement,supplier evaluation and selection and order optimization strategy.Secondly,this paper applies the advancing method SVM to supplier evaluation and selection;thus predigests the process of supplier selection and improves the efficiency of supplier evaluation and selection.Thirdly,this paper builds up fuzzy multi-object programming method to determine multi-supplier order distribution which could reduce purchase risk and optimize order distribution strategy.Finally,this paper combines purchase optimization strategy theory and modernrn information technology,designs and implements purchase optimization decision support system based on supply chain using ASP.NET and SQL Server.更多还原