A type of new conserved quantity deduced from Mei symmetry for Appell equations in a holonomic system with unilateral constraints

A type of new conserved quantity deduced from Mei symmetry of Appell equations for a holonomic system with unilateral constraints is investigated.The expressions of new structural equation and new conserved quantity deduced from Mei symmetry of Appell equations for a holonomic system with unilateral constraints expressed by Appell functions are obtained.An example is given to illustrate the application of the results.     

Self-calibration of a fringe projection system using epipolar constraint

A new self-calibration method for a fringe-projection based 3D measurement system is proposed. To determine homologous points in the proposed camera/projector configuration, the phase map is converted to the u, v coordinates in the projected image. The projector can conceptually be regarded as camera acting in a reversed mode. Taking the epipolar constraint into account, this approach can allow self-calibration of the fringe projection system. Considering the effect of noise, we propose a nonlinear self-calibrating model. The experimental results show the effectiveness of this approach.     

On the Freezing of Variables in Random Constraint Satisfaction Problems

The set of solutions of random constraint satisfaction problems (zero energy groundstates of mean-field diluted spin glasses) undergoes several structural phase transitions as the amount of constraints is increased. This set first breaks down into a large number of well separated clusters. At the freezing transition, which is in general distinct from the clustering one, some variables (spins) take the same value in all solutions of a given cluster. In this paper we introduce and study a message passing procedure that allows to compute, for generic constraint satisfaction problems, the sizes of the rearrangements induced in response to the modification of a variable. These sizes diverge at the freezing transition, with a critical behavior which is also investigated in details. We apply the generic formalism in particular to the random satisfiability of boolean formulas and to the coloring of random graphs. The computation is first performed in random tree ensembles, for which we underline a connection with percolation models and with the reconstruction problem of information theory. The validity of these results for the original random ensembles is then discussed in the framework of the cavity method.     

基于光学测棒的立体视觉坐标测量系统的研究

提出了一种基丁测量与校准功能合一的光学测棒的立体视觉坐标测最系统.采用光学测棒作为成像目标,通过任意放置的两台摄像机获取测棒上的发光特征点的图像实现被测物体三维坐标的测量,同时利用测量数据定期对两台摄像机外部方位参数进行校准.深入研究了两台摄像机内部参数和外部方位参数校准过程中的校准件和校准算法的设计,以及系统测量建模等关键技术,提出了相应的解决方案,减小了摄像机内外参数校准及测量模型对测量结果的影响,提高系统的测量精度.实验结果表明.该系统的最大测量误差为0.11 mm.     

与地理环境相关的中国铁路客运网拓扑结构

以中国铁路车站作为“节点”,每辆列车经过的相邻两个停靠车站之间连接一条“边”,构成有方向有权重的中国铁路客运网.首先研究了该网络的拓扑结构,包括连接度、聚集系数、最短路径和强度,结果表明中国铁路客运网的连接度分布,强度分布都是介于指数分布和幂率分布之间,是一个具有小世界性质的阶层网络.修建铁路需考虑人口分布,行政区域等因素.铁路固定设施成本高,修建完成后很难做变动,因此需考虑诸多空间地理环境对中国铁路客运网的影响,如站点的连接度和站点的相连站点之间的平均行驶距离之间的关系、车站的分布密度与人口密度的关系, 关键词： 铁路客运网 拓扑统计 小世界 地理环境     

一类稀疏约束非线性规划的约束规格

研究一类带有闭凸集约束的稀疏约束非线性规划问题,这类问题在变量选择、模式识别、投资组合等领域具有广泛的应用.首先引进了限制性Slater约束规格的概念,证明了该约束规格强于限制性M-F约束规格,然后在此约束规格成立的条件下,分析了其局部最优解成立的充分和必要条件.最后,对约束集合的两种具体形式,指出限制性Slater约束规格必满足,并给出了一阶必要性条件的具体表达形式.     

预付款融资下期权契约的协调研究

本文研究零售商占主导、供应商自有资金有限的二级供应链如何通过契约实现协调的问题。在预付款融资的基础上加入期权契约方法,构建用于预付款融资的期权契约模型,并求解出该模型下所能协调供应链的契约参数与此时零售商供应商双方的最优决策系统。研究表明当供应商自有资金大于等于某临界值时通过预付款融资下的期权契约可实现供应链协调。若小于则无法通过该契约协调,并且供应商自有资金约束越大,零售商最优订购数量越多,同时供应商的最优生产数量随着自有资金的减少而减少,供应链的参与者及整个供应链的利润也随着供应商自有资金的减少单调递减;另外,相比于无融资下的期权契约,预付款模式能提高零售商、供应商以及整个供应链的收益。     

BFGS‐like updates of constraint preconditioners for sequences of KKT linear systems in quadratic programming

We focus on efficient preconditioning techniques for sequences of Karush‐Kuhn‐Tucker (KKT) linear systems arising from the interior point (IP) solution of large convex quadratic programming problems. Constraint preconditioners (CPs), although very effective in accelerating Krylov methods in the solution of KKT systems, have a very high computational cost in some instances, because their factorization may be the most time‐consuming task at each IP iteration. We overcome this problem by computing the CP from scratch only at selected IP iterations and by updating the last computed CP at the remaining iterations, via suitable low‐rank modifications based on a BFGS‐like formula. This work extends the limited‐memory preconditioners (LMPs) for symmetric positive definite matrices proposed by Gratton, Sartenaer and Tshimanga in 2011, by exploiting specific features of KKT systems and CPs. We prove that the updated preconditioners still belong to the class of exact CPs, thus allowing the use of the conjugate gradient method. Furthermore, they have the property of increasing the number of unit eigenvalues of the preconditioned matrix as compared with the generally used CPs. Numerical experiments are reported, which show the effectiveness of our updating technique when the cost for the factorization of the CP is high.     

Optimal insurance in the presence of insurer’s loss limit

In this paper we consider the optimal insurance problem when the insurer has a loss limit constraint. Under the assumptions that the insurance price depends only on the policy’s actuarial value, and the insured seeks to maximize the expected utility of his terminal wealth, we show that coverage above a deductible up to a cap is the optimal contract, and the relaxation of insurer’s loss limit will increase the insured’s expected utility.When the insurance price is given by the expected value principle, we show that a positive loading factor is a sufficient and necessary condition for the deductible to be positive. Moreover, with the expected value principle, we show that the optimal deductible derived in our model is not greater (lower) than that derived in Arrow’s model if the insured’s preference displays increasing (decreasing) absolute risk aversion. Therefore, when the insured has an IARA (DARA) utility function, compared to Arrow model, the insurance policy derived in our model provides more (less) coverage for small losses, and less coverage for large losses.Furthermore, we prove that the optimal insurance derived in our model is an inferior (normal) good for the insured with a DARA (IARA) utility function, consistent with the finding in the previous literature. Being inferior, the insurance can also be a Giffen good. Under the assumption that the insured’s initial wealth is greater than a certain level, we show that the insurance is not a Giffen good if the coefficient of the insured’s relative risk aversion is lower than 1.     

Rationalized Haar approach for nonlinear constrained optimal control problems

This paper presents a numerical method for solving nonlinear optimal control problems including state and control inequality constraints. The method is based upon rationalized Haar functions. The differential and integral expressions which arise in the system dynamics, the performance index and the boundary conditions are converted into some algebraic equations which can be solved for the unknown coefficients. Illustrative examples are included to demonstrate the validity and applicability of the technique.