风险视角的供应链设计优化模型和相关问题评价研究
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摘要
供应链风险管理已经引起理论界和企业界的重视,同时许多供应链风险案例也表明,一旦某种供应链风险真的发生,往往会给供应链造成不可逆转的损失,甚至造成供应链彻底崩溃,因此不考虑供应链风险的供应链设计与优化是有缺陷的。另外因供应链物流系统是供应链成功与否最关键也是最难实现的因素之一,更是其“瓶颈”,所以很大程度上供应链的设计优化效果可通过对其物流系统进行评价得以检验。因此针对风险视角的供应链设计优化模型和相关问题评价展开研究不仅具有较好的理论意义,而且对实践工作还具有一定的指导价值。论文主要创新和结论如下:
⑴借鉴金融工程中条件风险价值理论,分别提出了供应网络条件风险价值、分销网络条件风险价值的概念和计算公式,并用之度量供应网络和分销网络风险水平,算例结果说明该方法不仅能有效度量供应链中各种风险水平,而且能为风险视角的供应链设计优化决策提供必须的依据。另外为准确计算分销网络条件风险价值,给出了一种新的供应链需求点需求量预测模型─系统改进的灰色马尔科夫预测模型,该模型整合了灰色预测模型与马尔科夫模型各自的优点,算例结果说明了改进后的模型能有效提高预测精度。
⑵构建了考虑供应风险水平的供应网络设计两阶段优化模型、考虑需求风险水平的分销网络设计多目标优化模型且能体现供应链核心企业风险偏好。前者解决的是风险损失─供应商选择─购买量组合决策问题;后者解决的是风险损失─分销中心设立─分销中心购买量─分销中心服务对象─分销点购买量组合决策问题,并应用多项式目标优化(PGP)技术来组合目标。这些工作为CVaR与供应链设计优化决策类问题的结合研究作了有益的探索,且算例的优化决策结果也说明了文中构建的模型能有效解决上述组合决策问题。
⑶为提高供应链利益分配结果公平合理性,构造了一种考虑风险承担的供应链利益分配方法─正交投影熵值法。该方法有以下优点:规避了以前一些利益分配计算方法并不都满足特征函数的缺点;具有民主性;解决了多种计算结果不一致问题;解决了大规模的利益分配计算难题;体现了收益与风险成比例的原则。且算例也说明了该方法的有效性。
⑷引用成熟度模型和和谐管理理论评价供应链物流系统成熟度和和谐性。首先将成熟度模型与变权理论结合构造了一种新的供应链物流系统成熟度评价方法─层次变权综合熟度法,这种结合一方面不仅使评价方法更具有科学性,而且增强了方法应用的灵活性,使评价更符合实际情况,另一方面不仅可体现对某些重要影响因素的均衡性要求,而且也可以体现对某些关键因素的激励性要求;且实例说明了该方法的有效性。其次提出了供应链物流系统和谐性概念、和谐性分析要素及释义,并用柯西型隶属度函数计算其和谐度,更重要的是还构建了一种新的和谐性分析工具─D-C层次立体空间;且实例也说明了这些方法不仅能科学、合理地评价其和谐度,而且还能找出其不和谐因素和关键因素。
该论文有图25幅,表48个,参考文献179篇。
The risk management of supply chain has received the emphasis from theory horizon and business community, and many cases of supply chain risk have indicated that once some kinds of risk really happened, it would cause irreversible loss and even thoroughly collapse to supply chain, hence design and optimization of supply chain without considering its risk is deficient. In addition, logistics system is the bottleneck of supply chain and one of the most critical factors that hard to be realized, hence to a great extent, the effects of the optimization of supply chain can be totally examined through evaluating its logistics system. Consequently, extending research of evaluating on optimization model and relevant issues of supply chain is possessed of more than some theory meanings, but some guidance values to practice work. Main conclusions and innovations are as follows:
⑴Proposing respectively concepts and formulas of supply network CVaR(Conditional Value at Risk) and distribution network CVaR by using the theory of CVaR in financial engineering for reference, and then utilizing these two kinds of CVaR to measure the risk level of supply network and distribution network. Results of example indicates that such a method can effectively measure all kinds of risk levels in supply chain and provide necessary evidences for the optimizing decision of supply chain in the perspective of risk. In addition, to precisely calculate the CVaR of distribution network, this paper proposes a kind of new predicting model concerning about the requiring quantity of demand point in supply chain─system improved Grey Markov predicting model, which integrates the respective advantages of Grey Model Prediction(GM(1,1)) and Markov model. Relevant example demonstrates that such an improved model can effectively increase the forecasting exactitude.
⑵Constructing a two-stage optimization model of supply network design with considering supply risk level, and a model called multiple targets optimization model of distribution network planning, which can reflect the risk preferences of core enterprises in supply chain. The former is designed to solve the issue regarding to combining decision on risk loss-selection of supplier- purchasing quantity; the latter aims to solving the combining decision on risk loss-establishment of distribution center-purchasing quantity of distribution center-servicing objects of distribution center-purchasing quantity of distribution outlet and then utilize Polynomial Goal Programming(PGP) to combine these targets. These work made a profitable exploration for research on the combination of CVaR and decisions on supply chain design and optimization. Further, the optimization results of example also illustrated that models constructed above could effectively solve such combining decision issues.
⑶To ensure that the result of distributing benefits is fair and reasonable, the author constructs a new distributing method—Orthogonal Projection and Value method that concerns risk-bearing. This method possesses advantages as follows: being able to avoid the defects that some formerly calculating method about profit-distribution cannot satisfy the characteristic functions; being possessed of some democratic nature; being able to solve the problem about the discrepancy of various calculating results; being able to resolve large-scale complicate calculating problems; embodying sufficiently the principle that profit is proportionate to risk. Further, example cited illustrates the effectiveness of this method.
⑷Evaluating the maturity degree and harmony of logistical system by citing the maturity degree model and harmonious management theory. In the first place, based on the maturity degree model of supply chain logistics system and variable weight theory, this paper constructs a kind of new method for evaluating the maturity of supply chain logistic system called Hierarchically Variable Weight Synthesizing Maturity Degree model that combines maturity model and variable weight theory to endow this evaluation method itself with scientificity and enhance the flexibility of method application, which makes the evaluation of supply chain logistics system more consistent with reality. On the other hand, this combination can not only embody the balancing requirements for some important influencing factors, but also some stimulating requirements for some critical factors. The effectiveness of this method is illustrated by factual examples. Secondly, this paper proposes the concept, analyzing elements and paraphrase of harmony of supply chain logistics system, and then calculates the harmony degree by membership function of cauchy type. More importantly, it also constructs a new kind of multi-level harmony analysis tool, namely stereo-space of D-C level, and examples also illustrates that these methods can not only scientifically and reasonably evaluate the harmony degree of supply chain logistics system, but also help find its unharmonious and critical factors.
There are 25 figures, 48 tables and 179 references in this paper.
⑴借鉴金融工程中条件风险价值理论,分别提出了供应网络条件风险价值、分销网络条件风险价值的概念和计算公式,并用之度量供应网络和分销网络风险水平,算例结果说明该方法不仅能有效度量供应链中各种风险水平,而且能为风险视角的供应链设计优化决策提供必须的依据。另外为准确计算分销网络条件风险价值,给出了一种新的供应链需求点需求量预测模型─系统改进的灰色马尔科夫预测模型,该模型整合了灰色预测模型与马尔科夫模型各自的优点,算例结果说明了改进后的模型能有效提高预测精度。
⑵构建了考虑供应风险水平的供应网络设计两阶段优化模型、考虑需求风险水平的分销网络设计多目标优化模型且能体现供应链核心企业风险偏好。前者解决的是风险损失─供应商选择─购买量组合决策问题;后者解决的是风险损失─分销中心设立─分销中心购买量─分销中心服务对象─分销点购买量组合决策问题,并应用多项式目标优化(PGP)技术来组合目标。这些工作为CVaR与供应链设计优化决策类问题的结合研究作了有益的探索,且算例的优化决策结果也说明了文中构建的模型能有效解决上述组合决策问题。
⑶为提高供应链利益分配结果公平合理性,构造了一种考虑风险承担的供应链利益分配方法─正交投影熵值法。该方法有以下优点:规避了以前一些利益分配计算方法并不都满足特征函数的缺点;具有民主性;解决了多种计算结果不一致问题;解决了大规模的利益分配计算难题;体现了收益与风险成比例的原则。且算例也说明了该方法的有效性。
⑷引用成熟度模型和和谐管理理论评价供应链物流系统成熟度和和谐性。首先将成熟度模型与变权理论结合构造了一种新的供应链物流系统成熟度评价方法─层次变权综合熟度法,这种结合一方面不仅使评价方法更具有科学性,而且增强了方法应用的灵活性,使评价更符合实际情况,另一方面不仅可体现对某些重要影响因素的均衡性要求,而且也可以体现对某些关键因素的激励性要求;且实例说明了该方法的有效性。其次提出了供应链物流系统和谐性概念、和谐性分析要素及释义,并用柯西型隶属度函数计算其和谐度,更重要的是还构建了一种新的和谐性分析工具─D-C层次立体空间;且实例也说明了这些方法不仅能科学、合理地评价其和谐度,而且还能找出其不和谐因素和关键因素。
该论文有图25幅,表48个,参考文献179篇。
The risk management of supply chain has received the emphasis from theory horizon and business community, and many cases of supply chain risk have indicated that once some kinds of risk really happened, it would cause irreversible loss and even thoroughly collapse to supply chain, hence design and optimization of supply chain without considering its risk is deficient. In addition, logistics system is the bottleneck of supply chain and one of the most critical factors that hard to be realized, hence to a great extent, the effects of the optimization of supply chain can be totally examined through evaluating its logistics system. Consequently, extending research of evaluating on optimization model and relevant issues of supply chain is possessed of more than some theory meanings, but some guidance values to practice work. Main conclusions and innovations are as follows:
⑴Proposing respectively concepts and formulas of supply network CVaR(Conditional Value at Risk) and distribution network CVaR by using the theory of CVaR in financial engineering for reference, and then utilizing these two kinds of CVaR to measure the risk level of supply network and distribution network. Results of example indicates that such a method can effectively measure all kinds of risk levels in supply chain and provide necessary evidences for the optimizing decision of supply chain in the perspective of risk. In addition, to precisely calculate the CVaR of distribution network, this paper proposes a kind of new predicting model concerning about the requiring quantity of demand point in supply chain─system improved Grey Markov predicting model, which integrates the respective advantages of Grey Model Prediction(GM(1,1)) and Markov model. Relevant example demonstrates that such an improved model can effectively increase the forecasting exactitude.
⑵Constructing a two-stage optimization model of supply network design with considering supply risk level, and a model called multiple targets optimization model of distribution network planning, which can reflect the risk preferences of core enterprises in supply chain. The former is designed to solve the issue regarding to combining decision on risk loss-selection of supplier- purchasing quantity; the latter aims to solving the combining decision on risk loss-establishment of distribution center-purchasing quantity of distribution center-servicing objects of distribution center-purchasing quantity of distribution outlet and then utilize Polynomial Goal Programming(PGP) to combine these targets. These work made a profitable exploration for research on the combination of CVaR and decisions on supply chain design and optimization. Further, the optimization results of example also illustrated that models constructed above could effectively solve such combining decision issues.
⑶To ensure that the result of distributing benefits is fair and reasonable, the author constructs a new distributing method—Orthogonal Projection and Value method that concerns risk-bearing. This method possesses advantages as follows: being able to avoid the defects that some formerly calculating method about profit-distribution cannot satisfy the characteristic functions; being possessed of some democratic nature; being able to solve the problem about the discrepancy of various calculating results; being able to resolve large-scale complicate calculating problems; embodying sufficiently the principle that profit is proportionate to risk. Further, example cited illustrates the effectiveness of this method.
⑷Evaluating the maturity degree and harmony of logistical system by citing the maturity degree model and harmonious management theory. In the first place, based on the maturity degree model of supply chain logistics system and variable weight theory, this paper constructs a kind of new method for evaluating the maturity of supply chain logistic system called Hierarchically Variable Weight Synthesizing Maturity Degree model that combines maturity model and variable weight theory to endow this evaluation method itself with scientificity and enhance the flexibility of method application, which makes the evaluation of supply chain logistics system more consistent with reality. On the other hand, this combination can not only embody the balancing requirements for some important influencing factors, but also some stimulating requirements for some critical factors. The effectiveness of this method is illustrated by factual examples. Secondly, this paper proposes the concept, analyzing elements and paraphrase of harmony of supply chain logistics system, and then calculates the harmony degree by membership function of cauchy type. More importantly, it also constructs a new kind of multi-level harmony analysis tool, namely stereo-space of D-C level, and examples also illustrates that these methods can not only scientifically and reasonably evaluate the harmony degree of supply chain logistics system, but also help find its unharmonious and critical factors.
There are 25 figures, 48 tables and 179 references in this paper.
引文
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