测度链上的柯西不等式

研究了测度链上的柯西不等式,给出测度链上柯西不等式的具体形式.此外,还对测度链上的柯西不等式作了推广.     

因果链上因果效应的关系及推断

探讨因果链上总因果效应与局部因果效应的关系及因果效应的可识别性. 给出了在因果链上因果效应的传递关系. 根据这个关系, 给出了通过控制因果链上中间因素消除混杂偏倚的方法.     

链可迁映射

本文讨论紧致度量空间 X 上的链可迁自映射 f,主要证明了:1.f 不是链可迁的充要条件是存在非空开集 U,使(?)X 且 f((?))(?)U。2.若满射 f 的ω极限集含于 f 的一个链分支(链混合分支)之中,则 f 在 X 上是链可迁(链混合)的。3.若 X=S~1或 I(=[0,1]),f 是链可迁的且具有伪轨道跟踪性质,则 f 敏感依赖于初始条件且在 X 上的强混沌的。4.若X=S~1或 I 且 f 为满射,如 Γ((f)=(?)(ω(x,f)∩α(x,f))含于 f 的一个链分支(链混合分支)之中,则 f 在 X 上是链可迁(链混合)的,若Γ(f)连通,则 f 在 X 上链混合的。     

时间测度链上带有时滞的中立型动力方程的伪概周期解[英文]

本文研究时间测度链上伪概周期函数的性质.利用时间测度链上指数型二分性性质以及Banach不动点定理,我们得到时间测度链上带有时滞的中立型动力方程的伪概周期解存在性与唯一性的充分条件.并举例说明我们的结论     

四元Heisenberg群上的链和R-圆及其性质

定义了四元双曲空间上的链和R-圆,并给出了链在垂直投影下的性质.证明了经过Heisenberg群上固定两点的链的唯一性,R-球的qc-水平性,并给出了R-圆与纯虚R-圆之间的关系.     

加厚曲面中环链的交叉点数

研究加厚曲面中标架环链的交叉点数,利用Kauffman尖括号拆接模定义标架环链在其上的跨度,从而得到标架环链交叉点数的下界.     

时间测度链上n阶非线性中立型时滞动力方程的振动性

研究时间测度链上的一类n阶非线性中立型时滞动力方程的振动性.利用时间测度链上的有关理论和不等式技巧,获得该类方程振动的判别准则,这些准则不仅是新的,而且在时间测度链上统一了高阶非线性中立型时滞微分方程和差分方程的振动性质,最后举例说明了本文主要结果的应用.     

拍卖机制设计在区块链中的应用与挑战

区块链是新一代信息技术的重要组成部分,是分布式网络、加密技术、智能合约等多种技术集成的新型数据库软件。过去的十多年,区块链技术在全球范围内产生广泛影响。如今的区块链技术,已从最初的关注于解决货币和支付的去中心化问题,转入到解决市场的去中心化问题。智能合约的出现使得基于区块链技术的去中心化金融进入高速发展状态,也涌现出区块链环境下的各类拍卖场景。本文首次从机制设计角度,以区块链交易费机制,非同质化代币(Non-Fungible Token,NFT)拍卖和矿工可提取价值(Miner-Extractable Value,MEV)交易位置拍卖为主要对象,总结和剖析近些年来区块链上特有的拍卖机制;并针对区块链特性,提出区块链上拍卖机制设计所面临的挑战和未来亟待解决的问题。     

拓扑群作用下度量空间中链回归点集的研究

仿造度量空间中链回归点的定义,给出了拓扑群作用下度量空间中G-链回归点的概念,并将度量空间中链回归点的一些结论,推广到拓扑群作用下度量空间中,得到如下结果:1)同胚伪等价映射f的G-链回点集等于它的逆映射f~(-1)的G-链回归点集;2)伪等价映射f的G-链回点集和G-链等价集对G强不变;3)同胚等价映射f的G-链回点集f对强不变.4)等价映射f限制在它的G-链回归点集上形成的G-链回归点集就是等价映射f在度量G-空间X上形成的G-链回归点集.这些结果丰富了拓扑群作用下度量空间中G-链回归点的理论.     

树上二重非齐次马氏链随机转移概率的极限性质

研究树上二重非齐次马氏链随机转移概率的调和平均极限性质,作为推论,得到了树上非齐次马氏链以及非齐次马氏链上的随机转移概率调和平均极限性质.     

The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.     

Marginal AMP chain graphs

We present a new family of models that is based on graphs that may have undirected, directed and bidirected edges. We name these new models marginal AMP (MAMP) chain graphs because each of them is Markov equivalent to some AMP chain graph under marginalization of some of its nodes. However, MAMP chain graphs do not only subsume AMP chain graphs but also multivariate regression chain graphs. We describe global and pairwise Markov properties for MAMP chain graphs and prove their equivalence for compositional graphoids. We also characterize when two MAMP chain graphs are Markov equivalent.For Gaussian probability distributions, we also show that every MAMP chain graph is Markov equivalent to some directed and acyclic graph with deterministic nodes under marginalization and conditioning on some of its nodes. This is important because it implies that the independence model represented by a MAMP chain graph can be accounted for by some data generating process that is partially observed and has selection bias. Finally, we modify MAMP chain graphs so that they are closed under marginalization for Gaussian probability distributions. This is a desirable feature because it guarantees parsimonious models under marginalization.     

Perturbation models

A Markov chain (with a discrete state space and a continuous parameter) is perturbed by forcing a chain to return to “permissible” states whenever it happens to enter “forbidden” states, with returns governed by a replacement distribution.The compensation method is employed to obtain the distribution for the modified chain, in terms of the original chain and the perturbation mechanism.Emphasis is placed on ergodic chains, and interpretation of results in terms of perturbation theory of semi-groups and the ergodic potential theory (based on the fundamental matrix of a chain) is mentioned.     

基于广告、技术、奖励的二级供应链效益最大化研究

研究了做广告、引进先进技术、奖励员工对供应链效益影响问题.针对单个制造商与单个零售商组成的二级供应链,基于弹性需求,在促销-价格敏感需求、质量-敏感需求与奖励-敏感成本条件下构建模型.以整个供应链的利润之和最大,且制造商与零售商利润之差的平方和最小为目标.首先,通过Lagrange数乘法求解,判断对应的Hesse矩阵.其次,确定了广告、技术与奖励员工的最佳投入量,实现供应链效益最大化,提高供应链的经济效益.同时,也通过收益共享,实现供应链的协调性,优化供应链产业结构.最后运用数值实验来具体说明各因素对供应链最大效益的影响.     

碳减排政策下多周期供应链网络均衡决策

为研究碳减排政策对多周期供应链网络均衡决策的影响,分析了供应链网络结构中各层的最优条件,建立了多周期碳减排供应链网络均衡模型.首先将其转化为等价的变分不等式问题,然后利用变分不等式的投影收缩算法进行求解.并通过模型仿真分析了在不同周期下不同碳限额、单位碳排放量对供应链网络均衡的影响结果发现企业在环境绩效和经济绩效之间存在冲突,适当的控制碳税和调整产品的单位碳排放量可以缓解这种冲突.同时,政府对于碳限额的值过于宽松,对于碳减排的实施起不到明显作用.     

依状态独立的随机环境中的马氏链

本主要讨论了依状态独立的随机环境中的马氏链，并严格地证明了依状态独立的随机环境中的马氏链，如果在环境不退化的一般情形下，不是时齐马氏链，而环境退化必然是马氏链这个结论。     

Singular hyperbolicity of star flows on surfaces

In this paper, we prove that every star flow on the closed surface has finitely many chain recurrent classes. Furthermore, it is singular hyperbolic if every non-trivial singular chain component is a graph. As a consequence, every star flow on the 2-sphere or the projective plane is singular hyperbolic.     

Asymptotic analysis of option pricing in a Markov modulated market

We address asymptotic analysis of option pricing in a regime switching market where the risk free interest rate, growth rate and the volatility of the stocks depend on a finite state Markov chain. We study two variations of the chain namely, when the chain is moving very fast compared to the underlying asset price and when it is moving very slow. Using quadratic hedging and asymptotic expansion, we derive corrections on the locally risk minimizing option price.     

What are causes of cash flow bullwhip effect in centralized and decentralized supply chains?

Bullwhip effect in supply chain is a phenomenon which can emerge in both inventory levels and replenishment orders. Bullwhip effect causes variations in cash conversion cycle (CCC) across cash flow of supply chain. As a result, it can lead to inefficiencies such as cash flow bullwhip (CFB). Due to negative impact of CFB on cash flow of supply chain, it can lead to a decrease in efficiency of supply chain management (SCM). That is why supply chain modeling is a proper start point for effective management and control of the CFB. This paper aims to analyze concurrent impact of causes of inventory bullwhip effect and effect of their interactions on CFB based on generalized OUT policy from aspect of CCC variance. To this end, first we develop system dynamics structure of beer distribution game as simulation model which includes multi-stage supply chain under both centralized and decentralized supply chains. Then, in order to develop CFB function, we design experiments in developed simulation model using response surface methodology (RSM). Results demonstrate that if each chain member uses generalized OUT policy as replenishment model, there still exists CFB in both chains and CFB largely stems from rationing and shortage gaming in both centralized and decentralized supply chain. In addition, when information on ordering parameters are not shared among members, parameters of downstream stage (i.e. retailer) are more important than parameters of upstream stage (i.e. manufacturer) in reducing CFB function.     

A finite model of mobility

The Markov chains with stationary transition probabilities have not proved satisfactory as a model of human mobility. A modification of this simple model is the ‘duration specific’ chain incorporating the axiom of cumulative inertia: the longer a person has been in a state the less likely he is to leave it. Such a process is a Markov chain with a denumerably infinite number of states, specifying both location and duration of time in the location. Here we suggest that a finite upper bound be placed on duration, thus making the process into a finite state Markov chain. Analytic representations of the equilibrium distribution of the process are obtained under two conditions: (a) the maximum duration is an absorbing state, for all locations; and (b) the maximum duration is non‐absorbing. In the former case the chain is absorbing, in the latter it is regular.