培养学生科学思维和创新能力的研究与实践——谈大学数学研究型教学

通过从一个导数值等式的证明谈起,探讨教师在课堂教学中如何根据教学内容创设能激起学生新异感的问题情景,启发和引导学生发散思考,类比、联想、猜想,探索和发现新问题并给出解答.使学生思维不断攀升,丰富教学内容,激发学生兴趣,培养学生科学思维方法和创新能力.     

出租车司机社会贡献评价方法研究

出租车司机的社会贡献对于促进城市经济发展和社会进步具有重要的作用,评价出租车司机的社会贡献是激励出租车司机多做社会贡献的重要手段。为了评价出租车司机的社会贡献,本文提出了一种基于实际出租车运营数据的评价方法。本文设计了运营特性、重点区域、恶劣天气、大事件四个体现司机社会贡献的指标,以此构建了出租车司机社会贡献评价指标体系,进而选用了主观赋权法G1法和客观赋权法拉开档次法相结合的赋权方式对指标赋权,并选择四种评价信息集结方法建立了出租车司机社会贡献评价模型。最后,通过实际的出租车运营数据验证了本方法的可行性。本文为评价出租车司机社会贡献提供了一种研究思路和方法,并对政府政策的制定和企业策略的实施具有一定的启示。     

Strategic commitment to price to stimulate downstream innovation in a supply chain

It is generally in a firm’s interest for its supply chain partners to invest in innovations. To the extent that these innovations either reduce the partners’ variable costs or stimulate demand for the end product, they will tend to lead to higher levels of output for all of the firms in the chain. However, in response to the innovations of its partners, a firm may have an incentive to opportunistically increase its own prices. The possibility of such opportunistic behavior creates a hold-up problem that leads supply chain partners to underinvest in innovation. Clearly, this hold-up problem could be eliminated by a pre-commitment to price. However, by making an advance commitment to price, a firm sacrifices an important means of responding to demand uncertainty. In this paper we examine the trade-off that is faced when a firm’s channel partner has opportunities to invest in either cost reduction or quality improvement, i.e. demand enhancement. Should it commit to a price in order to encourage innovation, or should it remain flexible in order to respond to demand uncertainty. We discuss several simple wholesale pricing mechanisms with respect to this trade-off.     

Hemivariational inequality approach to constrained problems for star-shaped admissible sets

The hemivariational inequality approach is applied to establish the existence of solutions to a large class of nonconvex constrained problems in a reflexive Banach space. The admissible sets are supposed to be star-shaped with respect to a ball. Due to a discontinuity property of the Clarke directional differential related to the corresponding distance functions, the proposed method permits one to attain the solution without passing to zero with the penalization parameter. Some applications to nonconvex constrained variational problems illustrate the theory.     

Factorisation of Littlewood-Richardson coefficients

The hive model is used to show that the saturation of any essential Horn inequality leads to the factorisation of Littlewood-Richardson coefficients. The proof is based on the use of combinatorial objects known as puzzles. These are shown not only to account for the origin of Horn inequalities, but also to determine the constraints on hives that lead to factorisation. Defining a primitive Littlewood-Richardson coefficient to be one for which all essential Horn inequalities are strict, it is shown that every Littlewood-Richardson coefficient can be expressed as a product of primitive coefficients. Precisely the same result is shown to apply to the polynomials defined by stretched Littlewood-Richardson coefficients.     

快递企业航空货运网络的构建

快递业竞争激烈,构建高效合理的航空货运网络是快递企业提高竞争力的重要手段。“枢纽—辐射”式航空货运网络是整合航空快递资源、提高航空快递资源利用效率、提高快递企业竞争力的有效模式。本文以降低航空快递网络成本、加快航空快递处理时间为目标,从航空快递网络枢纽的选取、指派关系的确定、枢纽个数的选择三个方面研究了航空快递网络模型建立问题,选用遗传算法求解不同枢纽个数下航空快递网络的运输成本,并据此进行枢纽的选取,运用重力模型法进行指派关系的确定,在此基础上运用超效率DEA模型确定枢纽个数。接着,以包含17个节点的顺丰航空快递网络的规划为例,对本文所提出的模型和算法进行了验证,验证结果证实了模型的合理性。本文的研究为快递企业构建航空货运网络提供了科学实用的方法,该方法的使用可以降低航空货运成本,提高效率,从而提高快递企业的竞争力。     

Resource downgrading

This paper aims to develop models to optimally manage costs associated with resources that can be downgraded. These resources are reused a number of times before becoming unsuitable for their original purpose, and then they are assigned for some other purpose. The typical decisions are the quantity of resources to purchase, to downgrade and to hold in the inventory. A network-based model is developed to formulate the problem and to investigate several special cases. As the model becomes an integer program due to some side constraints, several heuristics are developed here to overcome the challenges associated with solving the resulting integer program. A semiconductor industry application for test wafer management is presented using real-life data.     

Effects of imprecise weighting in hierarchical preference programming

Preference programming is a general term for multi-criteria decision analytical approaches allowing incomplete preference information. In the PAIRS method, interval judgments are assigned to weight ratios between attributes to model imprecision in multi-attribute value trees. This paper studies the effects of a hierarchical model structure on the overall imprecision, as the form of the hierarchy also affects the form of imprecision that can be assigned to the model. The aim is to find out good procedural practices for reducing overall imprecision descending inherently from the model structure. The study provides simulation results about the ability of various weighting schemes to identify dominated alternatives, which are discussed with respect to other issues related to the weighting process. According to the results, a hierarchical model is structurally somewhat more unable to identify dominances than a corresponding nonhierarchical model, but its cognitive advantages often cancel out this. The results also suggest paying reasonable attention to the precision of the lower level judgments and to identifying possible correlations between the criteria.     

Transition to turbulence, small disturbances, and sensitivity analysis I: A motivating problem

For over 100 years, researchers have attempted to predict transition to turbulence in fluid flows by analyzing the spectrum of the linearized Navier-Stokes equations. However, for many simple flows this approach fails to match experimental results. Recently, new scenarios for transition have been proposed that are based on the interaction of the linearized equations of motion with small disturbances to the flow system. These new “mostly linear” theories have increased our understanding of the transition process, but the role of nonlinearity has not been explored in detail. This paper is the first of a two part work in which sensitivity analysis is used to study the effects of small disturbances on transition to turbulence. In this part, we study a highly sensitive one-dimensional Burgers' equation as a motivating problem. Sensitivity analysis is used to predict the large changes in solutions in the presence of a small disturbance. Also, sensitivity analysis is shown to provide more information about the disturbed nonlinear problem than a purely linear analysis of the problem. In the second part of this work, this analysis will be extended to the three-dimensional Navier-Stokes equations to show that small disturbances have great potential to trigger transition to turbulence.     

缩短订货提前期的汽车动态生产计划

为缩短客户从提交订单到领取汽车时间,通过对汽车企业定制化生产供应链要素分析,以订单处理带动生产管理改进.通过改善企业软能力,增强应对市场应变能力,允许一定提前期的订单修改,减少订单处理与等待时间;为适应订单的变化,生产中管理中采用“漏斗模型”,利用粗集理论制定动态生产计划,提高生产效率,达到最终减少客户等待时间目的.     

Learning to Ignore Online Help Requests

Email discussion groups provide a useful way of organizing email communities with a common interest in a certain topic. Emails submitted to the discussion group are sent automatically to each individual member, thereby eliminating the need to send multiple emails. This method may present unexpected difficulties however, when it comes to cooperation between members. An experimental study shows that email requests for help sent through discussion groups received less responses than emails sent individually to members of a group. Furthermore, subscribers to large discussion groups responded less often to help requests, whether they were sent to the group as a whole or to individuals. These results are discussed in terms of the separate roles of social cues and experience on the diffusion of responsibility effect.     

Evolutionary search for difficult problem instances to support the design of job shop dispatching rules

Dispatching rules are simple scheduling heuristics that are widely applied in industrial practice. Their popularity can be attributed to their ability to flexibly react to shop floor disruptions that are prevalent in many real-world manufacturing environments. However, it is a challenging and time-consuming task to design local, decentralised dispatching rules that result in a good global performance of a complex shop.An evolutionary algorithm is developed to generate job shop problem instances for which an examined dispatching rule fails to achieve a good solution due to a single suboptimal decision. These instances can be easily analysed to reveal limitations of that rule which helps with the design of better rules. The method is applied to a job shop problem from the literature, resulting in new best dispatching rules for the mean flow time measure.     

A Neuro-Fuzzy Approach to Optimize Hierarchical Recurrent Fuzzy Systems

To simplify the definition of fuzzy systems or to reduce its complexity hierarchical structures can be used. Thus, more transparent rule bases that are also easier to maintain can be designed. Furthermore, it is sometimes necessary to use time delayed input or to reuse time delayed output from the fuzzy system itself to obtain a rule base that describes the analyzed problem appropriately. This leads to hierarchical recurrent architectures that have increased approximation capabilities since they are able to store information of the past. In this article we present a neuro-fuzzy model that can be used to optimize hierarchical recurrent fuzzy rule bases if training data is available. Furthermore, we present an approach to learn initial rule bases from data using rule templates.     

ENVIRONMENTAL CHANGE AND THE CONTRIBUTION OF BIODIVERSITY TO ECOSYSTEM ADAPTATION

Abstract This paper develops a measure of the contribution of biodiversity in enhancing ecosystem performance that is subject to environmental fluctuation. The analysis draws from an ecological model that relates high phenotypic variance with lower short‐term productivity (due to the presence of suboptimal species) and higher long‐term productivity (due to better ability to respond to environmental fluctuations). This feature, which is a notable extension to existing economic‐ecological models of biodiversity, enables assessment of the interactions between diversity and a range of environmental fluctuations to highlight that biodiversity could be rendered economically disadvantageous when environmental fluctuation is insufficient. The resulting economic‐ecological model generates discounted present value of harvests for an ecosystem with diverse set of species. This value is compared with the harvest value of a similar economic‐ecological model with no diversity and that of an ecosystem where the dynamics of phenotypes in response to environmental fluctuations is disregarded. The results show that diversity positively contributes to the performance of ecosystems subject to sufficiently large environmental fluctuation. In addition, neglecting an ecosystem's increasing ability to adapt to match environmental conditions is also shown to be more costly than having no diversity in an otherwise identical ecosystem.     

考虑充电设施重入的电动汽车旅行商问题研究

出于减少环境危害和响应相关法规的考虑,物流企业开始逐步将运输车辆转变为电动汽车;而由于电动汽车的续航里程有限,对电动汽车的路径优化也将涉及充电设施。充电设施的“重入”是指电动汽车返回之前已经通过的充电设施进行充能的现象,它的存在需要改变经典旅行商问题模型中的“子回路约束”。本文聚焦于充电设施的“重入”,构建了一个无需预估充电设施重入次数上限的电动汽车旅行商问题模型,并通过引入路径可行性判别方法和增加充电设施选择与重复策略,设计了一种改进蚁群算法对问题进行求解。结果表明:与未考虑重入的模型相比,本文提出的考虑充电设施重入的模型能在电动汽车电池容量较低的情况下求出最优解,同时也能够使充电设施承担多次充电任务,从而在较少充电设施情况下依然能够得到可行的最优路径。     

Identification of interrelationship of key customers’ needs based on structural model for services/capabilities provided by a Semiconductor-Intellectual-Property Mall

The semiconductor industry is shifting towards innovation and acquisition of intellectual property. Semiconductor-Intellectual-Property (SIP) design, a new industry, is also rapidly growing. This challenges both providers and users to develop infrastructure and standard interfaces. Establishing an SIP Mall to provide a full array of SIP business services is a new concept used to promote growth of the SIP industry. Many foundries and governments have been involved in setting up SIP Malls; however, the major services needed for an SIP Mall to attract SIP providers and SIP users must still be clarified. In this paper, the DEMATEL (DEcision MAking Trial and Evaluation Laboratory) method was used to discover and illustrate the key services needed to attract SIP users and SIP providers to an SIP Mall. Research enabled the derivation of the interrelated services and the structural interrelationship between them using the DEMATEL method. Overall, four key services were found to be vital for an SIP Mall to attract customers and to allocate resources efficiently.     

University students’ perspectives on diagnostic testing in mathematics

Many universities issue mathematical diagnostic tests to incoming first-year students, covering a range of the basic concepts with which they should be comfortable from secondary school. As far as many lecturers are concerned, the purpose of this test is to determine the students' mathematical knowledge on entry. It should also provide an early indication of which students are likely to need additional help, and hopefully encourage such students to avail of extra support mechanisms at an early stage. However, it is not clear that students recognize these intentions and there is a fear that students who score poorly in the test will have their confidence further damaged in relation to mathematics and will be reluctant to seek help. To this end, a questionnaire was developed to explore students’ perspectives on diagnostic testing. Analysis of responses received to the questionnaire provided an interesting insight into students’ perspectives including the optimum time to conduct such a test, their views on the aims of diagnostic testing, whether they feel that testing is a good idea, and their attitudes to the support systems put in place to help those who scored poorly in the test.     

Using algorithmic thinking to design algorithms: The case of critical path analysis

Algorithmic thinking is emerging as an important competence in mathematics education, yet research appears to be lagging this shift in curricular focus. The aim of this generative study is to examine how students use the cognitive skills of algorithmic thinking to design algorithms. Task-based interviews were conducted with four pairs of Year 12 students (n = 8) to analyze how they used decomposition and abstraction to specify the projects, designed algorithms to solve scheduling problems by first devising fundamental operations and then using algorithmic concepts to account for complex and special cases of the problems, and tested and debugged their algorithms. A deductive-inductive analytical process was used to classify students’ responses according to the four cognitive skills to develop sets of subskills to describe how the students engaged these cognitive skills.     

Modeling customer impatience in a newsboy problem with time-sensitive shortages

Customers across all stages of the supply chain often respond negatively to inventory shortages. One approach to modeling customer responses to shortages in the inventory control literature is time-dependent partial backlogging. Partial backlogging refers to the case in which a customer will backorder shortages with some probability, or will otherwise solicit the supplier’s competitors to fulfill outstanding shortages. If the backorder rate (i.e., the probability that a customer elects to backorder shortages) is assumed to be dependent on the supplier’s backorder replenishment lead-time, then shortages are said to be represented as time-dependent partial backlogging. This paper explores various backorder rate functions in a single period stochastic inventory problem in an effort to characterize a diversity of customer responses to shortages. We use concepts from utility theory to formally classify customers in terms of their willingness to wait for the supplier to replenish shortages. Under mild assumptions, we verify the existence of a unique optimal solution that corresponds to each customer type. Sensitivity analysis experiments are conducted in order to compare the optimal actions associated with each customer type under a variety of conditions. Additionally, we introduce the notion of expected value of customer patience information (EVCPI), and then conduct additional sensitivity analyses to determine the most and least opportune conditions for distinguishing between customer behaviors.     

Teaching young children decomposition strategies to solve addition problems: An experimental study

The ability to count has traditionally been considered an important milestone in children's development of number sense. However, using counting (e.g., counting on, counting all) strategies to solve addition problems is not the best way for children to achieve their full mathematical potential and to prepare them to develop more complex and advanced computational skills. In this experimental study, we demonstrated that it was possible to teach children aged 5-6 to use decomposition strategy and thus reduced their reliance on counting to solve addition problems. The study further showed that children’ ability to adopt efficient strategies was related to their systematic knowledge of the part-part-whole relationship of the numbers 1-10.