我院专业建设中急需解决的几个问题

加强专业建设是提高高职教育教学质量和办学效益的一项重要举措,是做大做强做优高职教育的根本途径.结合我院实际,全面论述了我院专业建设中所应急需解决的几个方面的问题.通过真正落实与不断加强专业建设,全面提高我院的办学质量、效益与水平.     

Nonlinear programming approaches for an inverse problem in quasibrittle fracture

Characterization of the parameters describing the cohesive crack model is an important and difficult problem. Based on the availability of load-deflection data, obtained from such standard tests as the three-point bending and wedge splitting experiments, we formulate the required parameter identification as a special type of inverse problem. The formulation is in the form of a constrained optimization problem known as a mathematical program with equilibrium constraints characterized, in the present instance, by complementarity conditions involving the orthogonality of two sign-constrained vectors. Due to the difficulty of solving such a mathematical program directly, we investigate a number of numerical algorithms that are all based on solving a series of standard nonlinear programming problems. Computational results, using actual experimental data, are presented to compare the various schemes proposed.     

论企业营销工作中的顾客满意和顾客忠诚

文章阐明了顾客满意与顾客忠诚这二个不同概念的内涵,对顾客满意与忠诚二者间的关系进行了论述,并对怎样提高顾客满意度,培养忠诚感进行了探讨;指出顾客满意不等于顾客忠诚,而是实现顾客忠诚的一个有效途径,认为顾客满意只是顾客忠诚的前提,顾客忠诚才是结果。提出了营销的关键就是怎样使顾客从满意到忠诚。     

基于Jack的虚拟环境中一种防止穿越的实现

在虚拟环境下虚拟人手和虚拟物体的交互中,会发生穿越现象。为了解决穿越问题,在人体模型系统Jack的虚拟环境中,根据约束Constraint对象的特点,利用Constraint对象来模拟物体对人手阻挡作用,并利用约束队列实现了对场景中Constraint对象的管理,达到防穿越的效果。     

第三方物流企业顾客满意的要素分析

介绍了应用博弈论和危险分析的方法鉴定顾客对产品和服务不满意的关键因素和能够使顾客愉悦的关键因素,通过一组来自实际的数据及鉴定过程,证实了沙普利值法和归因危险度分析在制订最优市场战略中的理论及实用的优势.     

具有两参数的非线性非局部扰动发展方程奇摄动问题

本文研究了一类具有非线性非局部扰动发展方程的奇摄动问题.利用奇摄动方法,对该问题解的结构在两个小参数相互关联的情形和适当的条件下展开了全面研究.首先,构造了问题的外部解;然后在区域的边界邻域构造局部坐标系,再在该邻域中引入多尺度变量,得到问题解的边界层校正项,另外,通过引入伸长变量构造了初始层校正项;最后,利用不动点定理,证明了问题的解的一致有效的渐近展开式.用上述方法得到的各次近似解,具有便于求解、精度高等特点.     

Headquarter-centered common sourcing management through order coordination and consolidation

It is common for subsidiaries of a group company to use the same types of components for producing similar products. Different subsidiary companies may well procure such components from the same suppliers. This paper studies two sourcing management models. One is the Subsidiary-Autonomous Sourcing Management (SD-ASM) where subsidiaries manage their inventories and place purchasing orders independent of each other. The other is the Headquarter-centered Common Sourcing Management (HQ-CSM) where purchasing orders of subsidiaries are processed centrally through some kind of headquarter coordination. In the SD-ASM model, each subsidiary places replenishment orders at a time interval corresponding to their economic order quantity (EOQ). In the HQ-CSM model, two purchasing order management policies are examined. One is the Order Coordination policy in which common replenishment epochs or time periods are proposed by the headquarter and the subsidiaries are encouraged to coordinate the timing of their orders based on the common replenishment epochs. The other is the Order Consolidation policy in which the subsidiaries combine the quantity of their orders and the headquarter places a combined order with the supplier. In the Order Coordination policy, classic RAND heuristic is used to find the best common replenishment epoch and the best replenishment timing of each subsidiary. In the Order Consolidation policy, the optimal order quantity of the combined order is obtained from a mathematical model. The combined order is then allocated to the subsidiaries according to a proportional allocation rule. A series of numerical studies is conducted to compare the costs of the SD-ASM and HQ-CSM policies. The results show that HQ-CSM outperforms SD-ASM in terms of cost and robustness against demand uncertainties. This achievement is largely due to the economies of process (synergistic ordering process), the economies of scale (large order quantity with price discount) and risk pooling effect (transshipments). The results also reveal that the Order Consolidation policy with a combined order always performs better than the Order Coordination policy with common replenishment epochs especially in face of high demand uncertainties and high service level in the global market.     

地表水监测存在的问题及改进方法研究

随着工业生产和科学技术的迅猛发展,环境污染问题越发严重,严重影响了人们的生活质量.地表水是常见的一种水体形式,本研究探讨地表水监测存在的问题及改进方法,为改善环境污染提供参考.     

An artificial neural network based decision support system for solving the buffer allocation problem in reliable production lines

One of the major design problems in the context of manufacturing systems is the well-known Buffer Allocation Problem (BAP). This problem arises from the cost involved in terms of space requirements on the production floor and the need to keep in mind the decoupling impact of buffers in increasing the throughput of the line. Production line designers often need to solve the Buffer Allocation Problem (BAP), but this can be difficult, especially for large production lines, because the task is currently highly time consuming. Designers would be interested in a tool that would rapidly provide the solution to the BAP, even if only a near optimal solution is found, especially when they have to make their decisions at an operational level (e.g. hours). For decisions at a strategic level (e.g. years), such a tool would provide preliminary results that would be useful, before attempting to find the optimal solution with a specific search algorithm.     

A cluster-DEE-based strategy to empower protein design

The Medical and Pharmaceutical industries have shown high interest in the precise engineering of protein hormones and enzymes that perform existing functions under a wide range of conditions. Proteins are responsible for the execution of different functions in the cell: catalysis in chemical reactions, transport and storage, regulation and recognition control. Computational Protein Design (CPD) investigates the relationship between 3-D structures of proteins and amino acid sequences and looks for all sequences that will fold into such 3-D structure. Many computational methods and algorithms have been proposed over the last years, but the problem still remains a challenge for Mathematicians, Computer Scientists, Bioinformaticians and Structural Biologists. In this article we present a new method for the protein design problem. Clustering techniques and a Dead-End-Elimination algorithm are combined with a SAT problem representation of the CPD problem in order to design the amino acid sequences. The obtained results illustrate the accuracy of the proposed method, suggesting that integrated Artificial Intelligence techniques are useful tools to solve such an intricate problem.