摘要
随着科学技术的发展和管理观念的创新,企业越来越意识到,市场竞争已不仅仅是企业与企业之间的竞争,而更多的是供应链与供应链之间的竞争。近些年来,供应链库存系统优化与协调的研究成了供应链研究的热点。本文致力于从新的视角对该问题展开研究,取得了一定的研究成果。现将主要研究内容概括如下：
第1章主要介绍论文的研究背景、基本概念和理论以及相关的国内外研究现状。在对现阶段国内外学者研究成果分析和总结的基础上,结合本论文研究背景,提出了本文的研究内容和方案,规划出论文的体系结构。
第2章首先将模糊随机变量扩展为混合随机变量,并用来描述随机性与糊随性同时存在的复杂不确定需求。然后对多级单周期库存系统在模糊随机和混合随机需求环境下的优化与协调问题作了研究,提出了通过集成库存管理使库存系统整体收益期望值最大化的优化模型和协调合作伙伴利益的数量折扣契约模型,并根据遗传算法理论和计算机模拟技术设计了求解模型的智能算法。最后通过算例对模型进行了仿真分析。
第3章将近年来发展起来的金融风险控制工具——条件风险值,引入具有风险规避特性的供应链优化与协调问题的研究。建立了随机需求下,由具有不同风险规避特性的单个供应商与单个零售商组成的两级供应链,分别基于回购契约和收入共享契约的条件风险值模型和基于条件风险值的最优订购量模型及协调供应链的契约参数模型,并对模型进行了分析,揭示了供应商和零售商的风险规避程度对最优订购量、契约参数及供应链协调的影响。最后通过一个算例进一步验证了研究结论。
第4章提出风险偏爱值和条件风险偏爱值的概念,并引入到具有风险偏爱特性的供应链优化与协调问题的研究。建立了随机需求下由具有不同风险偏爱特性的单个供应商与单个零售商组成的两级供应链的条件风险偏爱值模型和基于条件风险偏爱值的最优订购量模型及协调供应链的最优回购契约模型和收入共享契约模型,并对模型进行了分析,揭示了供应商和零售商的风险偏爱程度对供应链协调、最优订购量、契约参数及供应链合作的稳定性的影响。最后通过一个算例进一步验证了本文的研究结论。
第5章首先提出条件风险好恶值的概念；然后将其引入到具有风险规避者和偏爱者加盟的供应链优化与协调问题的研究,建立了随机需求下由具有不同风险规避和偏爱特性的单个供应商与单个零售商组成的两级供应链的条件风险好恶值模型和基于条件风险值、条件风险偏爱值、条件风险好恶值的最优订购量模型及协调供应链的最优回购契约模型,并对模型进行了分析,揭示了供应商和零售商的风险规避和偏爱程度对最优订购量、回购价格及供应链协调的影响；最后通过一个算例进一步验证了本文的研究结论。
第6章总结了的本文研究成果、结论及进一步的研究方向
本文主要创新性工作的理论意义与实际应用价值在于
(1)在本文提出的混合随机变量理论中,提供了一种描述随机性和模糊性同时存在的复杂不确定性需求的方法,使不确定需求理论的研究得以深入；建立的混合随机需求环境下单周期多级库存系统优化模型和协调契约模型,为实际的多级库存系统优化与协调工作提供了理论与方法指导。
(2)绝大部分供应链优化与协调契约模型,都假定决策者的风险是中性,在实际工作中,这些模型不适用具有风险规避或偏爱特性的供应链决策者,目前用于供应链风险描述的主要方法——期望值方差法,由于计算复杂,结果不能用简单的解析式表达,因而,在实际中难以实施。本文提出的条件风险偏爱值和条件风险好恶值的理论,提供一种较好的一致性风险度量方法；以这些理论为基础建立的供应链优化与协调模型,与期望值方差法相比,由于具有较好的计算特性,模型参数实际意义明确,便于实际实施,因而,为具有不同风险态度的供应链决策者提供了一种方便实用的决策工具。
供应链管理的研究受到了越来越广泛的关注,并引起了日益深入的研究。近年来,我国企业已经将供应链管理作为企业战略管理的一项重要内容来对待,各大专院校与研究机构也将它作为研究活动的一项重要课题来对待。国家自然基金和863计划都将其作为重点研究的对象。在这种情况下,作为供应链管理的一个重要方面,本文的研究不仅具有较强的理论意义,更具有非常重要的现实指导意义。
With the development of science and technology and the innovation of management ideas, enterprises increasingly realize that the competition has not merely happened between enterprises, but mostly between the supply chains. The study on supply chain inventory system optimization and coordination becomes hot spot in recent years. There are a number of papers presented. This paper devoted to the study and analysis of contract models in supply optimization and coordination from a new perspective, the main research contents follows:
On the basis of introducing some principle on caption and some advanced theory and technique in inventory optimization and coordination mechanisms, chapter 1 summarizes the research status of inventory optimization and coordination mechanisms in SCM, then points out the problems that exist in inventory management system. According to these, the objective of the thesis is pointed out, and the research frame is presented
In chapter2, first puts forward the concept of mixture random variable, and used for description of uncertain demand. Then make search for multi-echelon and short period inventory system optimization problem based on fuzzy random or mixture random demand expected value theory. In chapter2 formulate an inventory system optimization model which make whole profit biggest through integrated inventory management and a quantity discount contract model based on coordinating cooperative partner benefit, and put forward an intelligence algorithm based on genetic algorithm combined with computer mixture random variables simulation. Finally, a data simulation analysis is made.
In chapter3, we introduce the financial risk control tool the——conditional value-at-risk to study risk-averse supply chains optimization and coordination mechanisms problem. First, for a two-echelon supply chain with a risk-averse supplier and risk-averse retailer, we construct the conditional value-at-risk model, the optimal ordering quantity model, the returns contract model and the Revenue-sharing contract model based on Cvar under random demand. Then, we analyze the model and reveal the impact of risk aversion on supply chains coordination, the optimal ordering quantity and the contract parameter decisions. In chapter2, we have also given numerical results to verify the conclusions presented in this paper
In chapter4, we put forward the conception of value-at-risk-taking and conditional value-at-risk-taking, and introduce it to study risk-taking supply chains optimization and coordination mechanisms problem. First, for a two-echelon supply chain with a risk-taking supplier and risk-taking retailer, we construct the conditional value-at-risk-taking model, the optimal ordering quantity model and the returns contract model and the Revenue-sharing contract model based on CVaRT under random demand. Then, we analyze the model and reveal the impact of risk-taking on supply chains coordination, the optimal ordering quantity, the contract parameter decisions, and cooperation stabilization. We have also given numerical results to verify the conclusions presented in this paper
In chapter5, we introduce conditional value-at-risk and conditional value-at-risk-taking to study risk-averse and risk-taking supply chains optimization and coordination mechanisms problem. First, for a two-echelon supply chain with a risk-averse(or risk-taking) supplier and risk-taking (or risk-averse) retailer, we construct the conditional value-at-risk and conditional value-at-risk-taking model, the optimal ordering quantity model and the returns contract model based on CVaR or CVaRT under random demand. Then, we analyze the model and reveal the impact of risk aversion on supply chains coordination, the optimal ordering quantity and the returns price decisions. Finally, we have also given numerical results to verify the conclusions presented in this paper
The theoretical meaning of innovative working and the practical value of this paper are as follows:
(1) This paper comes up with the theory of mixture random variable, which provides a method to describe the complex uncertain demand of coexistence of randomization and fuzziness and make the research on uncertain demand theory intensive. The multi-echelon and short period inventory system optimization model under mixture random demand and the coordinate contract model it established provide the theoretical and methodological guide for the practical multi-echelon inventory system optimization and coordination.
(2) Most of the supply chain optimization and coordination contract model assumed that the decision maker is risk-neutral with the evaluation criterion of profit maximization or cost minimization.. However, in practice these models don't apply to the decision makers with risk-averse and risk-taking. Currently, the main method to describe supply chain risk is mean-variance approach. But the calculation is complex and the result cannot be formulated by a simple formula. Therefore, it's hard to practice. The conditional value-at-risk-taking-averse theory presented in this paper provides a good Coherent risk-measuring method. The random demand based on these theories, the conditional value-at-risk-taking-averse model having two-echelon supply chain with a risk-taking supplier and risk-taking retailer and optimized ordering model based on conditional value-at-risk-taking-averse model, returns contract model and the revenue-sharing contract model, compared with the mean-variance approach because of the good the computation characteristic and the definite practical meaning of parameter, it can be practiced conveniently, so it provides a convenient and practical decision-making tool for the decision makers with different risk attitudes towards supply chain.
Supply Chain Management (SCM) had attracted much attention and had been widely and deeply studied in recent years, the enterprises of our country treat supply chain management as an important content of enterprise strategy management. Colleges, universities and research institutions also treat it as an important project. It appears in the significant projects of National Nature Science Fund and "863/planning". Under such circumstances, as an important aspect of supply chain management, this paper has both theoretical meaning and guiding realistically significance.
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