基于碳交易的闭环供应链碳减排与定价策略研究

在消费者对低碳产品存在偏好的碳交易市场中,研究两级闭环供应链中的减排与定价决策问题.对于制造商负责回收模式下的回收再制造过程,采用指数分布来刻画废旧产品质量水平的不确定性.假设新产品和再制造品存在竞争关系,建立制造商和零售商间的Stackelberg博弈模型,给出制造商确定减排投资和回收参考价格以及零售商决定两种产品的差别定价策略,通过算例分析回收产品的残值和碳交易价格对最优策略和供应链成员利润的影响.研究表明,为了获得利润最大,当碳交易的市场价格升高时,制造商应加大减排投资,且零售商应采取提高产品零售价的策略.     

考虑供应链风险和绩效的供应商选择的模糊动态非线性多目标规划模型

基于供应链风险和供应链绩效的模糊性和供应商选择问题的动态性,本文考虑供应链风险和供应链绩效作为模糊变量,讨论如何给生产商一个满意的动态多目标供应商选择方案,确定供应链风险和总成本最小,以及供应链绩效最大。然后对该问题提出了一个动态多目标多产品供应商选择模型,该模型是首次同时考虑供应商选择,订单分配,供应链风险和供应链绩效的一个模糊动态非线性多目标规划模型。为了去模糊化和求解该模型,给出了一个风险和绩效的模糊评估法。最后给出一个数值算例验证了该模型的可行性,为决策者选择供应商提供了理论依据。     

基于减排成本共担期权契约的供应链协调

考虑消费者具有低碳产品偏好的情况,研究需求随机且受减排影响的期权契约,建立了由单个制造商和单个零售商组成的供应链模型。该模型中制造商处主导地位,零售商处追随地位,制造商首先提出期权契约,零售商购买期权。求解发现,由于传统双重边际化效应的存在,只有当零售价格等于期权执行价格时,才能达到供应链的协调,这时零售商利润为负,不满足参与约束。为此,从降低期权执行价格的角度,对期权契约进行补充,增加了成本共担条款。研究表明,减排成本共担的期权契约能够实现供应链的协调。最后利用算例验证了结论,计算了制造商和零售商利润及零售商分担的减排成本比例随期权价格和期权执行价格的变化情况,并对减排难度系数的敏感性做了分析。     

“公司+农户”型订单农业供应链“双向补贴”机制研究

基于订单农业特点,构建“公司+农户”型订单农业供应链决策模型。研究发现,订单农业传统价格机制:按“固定价格”收购、按“市场价格”收购、“随行就市,保底收购”,各具优缺点,但均未能很好地协调此类“公司+农户”型订单农业供应链,我国订单农业违约率也是居高不下。为此,提出一种 “双向补贴”价格机制来协调此类订单农业供应链。本研究结果表明,“双向补贴”价格机制能够很好地弥补了按“固定价格”,“市场价格”收购的缺陷,保证了农户和公司获得相对稳定的收入,提高了“公司+农户”型订单农业供应链的稳定性。同时,实施该协调机制后,改善了公司在“随行就市,保底收购”机制下要承担全部风险的缺陷,公司和农户实现了“收益共享,风险同担”。     

基于风险厌恶零售商的双渠道闭环供应链运作策略

在对称信息框架下,针对零售商存在风险厌恶特性的双渠道闭环供应链,基于Stackelberg博弈理论探讨了不同的回收再制造模式下(制造商不回收再制造、制造商独立回收再制造、制造商依托零售商回收再制造)供应链各主体的运作决策。研究发现,在不同回收再制造模式下,制造商与风险厌恶的零售商合作能够获得更多收益。市场波动的增大对供应链各主体并非始终是有害的,随着市场波动的增大,带有风险厌恶的零售商收益不断减小,而风险中性的双渠道制造商收益逐步增大,零售商风险厌恶特性为制造商带来了更多的收益。制造商独立回收再制造以及通过零售商进行回收再制造时,双渠道产品定价均低于不进行任何回收再制造模式下的定价,双渠道需求和利润均高于不进行任何回收再制造模式下的渠道需求和利润,即回收再制造模式不仅为下游顾客带来了更多的消费实惠,同时也为供应链各主体带来了更多的收益。     

产需不确定下面向资金约束供应商的供应链融资策略研究

以包含一个供应商和一个分销商的供应链为研究对象,其中分销商面临市场需求不确定性,供应商存在资金约束且面临产出不确定性。 提出期望利率的概念,研究银行贷款期望利率一定的情况下,供应链银行融资最优策略。 构建了供应链预付款融资机制,在此基础上研究预付款模式下供应链的融资与生产订购的最优策略,并讨论了预付款期望利率的可行范围。 研究表明,预付款融资模式下,分销商愿意以低于银行贷款利率的期望利率向供应商提供预付款; 存在预付款期望利率可行区间,实现预付款协调模式下供应链系统的帕累托改进。     

展厅现象下电子零售商与传统零售商的价格竞争

针对双渠道中存在消费者先通过实体店体验产品,而转移电子渠道购买的展厅现象,运用消费者效用理论,建立不同购买方式下电子零售商和传统零售商的定价决策模型,通过对不同情形下最优决策的比较分析,进一步研究展厅现象如何影响电子零售商和传统零售商的定价和利润。研究表明:三种购买方式同时存在时,展厅现象将加剧传统零售商与电子零售商的价格竞争,导致双方利润受损,但当电子渠道接受度较高或是较低且实体店体验对电子渠道接受度的影响较大时,电子零售商可以利用展厅现象提高其销售价格并获利。     

Bayesian Nonparametric Modeling for Multivariate Ordinal Regression

Univariate or multivariate ordinal responses are often assumed to arise from a latent continuous parametric distribution, with covariate effects that enter linearly. We introduce a Bayesian nonparametric modeling approach for univariate and multivariate ordinal regression, which is based on mixture modeling for the joint distribution of latent responses and covariates. The modeling framework enables highly flexible inference for ordinal regression relationships, avoiding assumptions of linearity or additivity in the covariate effects. In standard parametric ordinal regression models, computational challenges arise from identifiability constraints and estimation of parameters requiring nonstandard inferential techniques. A key feature of the nonparametric model is that it achieves inferential flexibility, while avoiding these difficulties. In particular, we establish full support of the nonparametric mixture model under fixed cut-off points that relate through discretization the latent continuous responses with the ordinal responses. The practical utility of the modeling approach is illustrated through application to two datasets from econometrics, an example involving regression relationships for ozone concentration, and a multirater agreement problem. Supplementary materials with technical details on theoretical results and on computation are available online.     

On compact vector formats in the solution of the chemical master equation with backward differentiation

A stochastic chemical system with multiple types of molecules interacting through reaction channels can be modeled as a continuous‐time Markov chain with a countably infinite multidimensional state space. Starting from an initial probability distribution, the time evolution of the probability distribution associated with this continuous‐time Markov chain is described by a system of ordinary differential equations, known as the chemical master equation (CME). This paper shows how one can solve the CME using backward differentiation. In doing this, a novel approach to truncate the state space at each time step using a prediction vector is proposed. The infinitesimal generator matrix associated with the truncated state space is represented compactly, and exactly, using a sum of Kronecker products of matrices associated with molecules. This exact representation is already compact and does not require a low‐rank approximation in the hierarchical Tucker decomposition (HTD) format. During transient analysis, compact solution vectors in HTD format are employed with the exact, compact, and truncated generated matrices in Kronecker form, and the linear systems are solved with the Jacobi method using fixed or adaptive rank control strategies on the compact vectors. Results of simulation on benchmark models are compared with those of the proposed solver and another version, which works with compact vectors and highly accurate low‐rank approximations of the truncated generator matrices in quantized tensor train format and solves the linear systems with the density matrix renormalization group method. Results indicate that there is a reason to solve the CME numerically, and adaptive rank control strategies on compact vectors in HTD format improve time and memory requirements significantly.     

Non-commutative Markov chains and multi-analytic operators

We study a model of repeated interaction between quantum systems which can be thought of as a non-commutative Markov chain. It is shown that there exists an outgoing Cuntz scattering system associated to this model which induces an input-output formalism with a transfer function corresponding to a multi-analytic operator, in the sense of multivariate operator theory. Finally we show that observability for this system is closely related to the scattering theory of non-commutative Markov chains.