论资本质量与财务目标

从传统财务目标的缺陷在于忽视资本质量的分析入手 ,论述了资本质量是资本的内在规定性 ,是资本社会属性的总和与资本经济属性的质量方面 ;将资本质量引入财务目标是由资本的本质和财务的本质、资本质量与资本数量之间的关系、时代特征和国家财务所决定的 ,资本质量最优化与资本数量最大化是财务目标的必然选择 ;提出了资本质量考核指标体系。     

网络零售配送系统最优运作成本的分析

针对配送运作成本关键部分棗平均运距作出的估计,在车辆路径问题渐进最优理论的基础上,建立了一个平均运作成本最优的规划模型,从经济的角度对运作策略作了简要分析。与其他规划模型不同,新建模型考虑了平均水平的概率特性及众多实际因素,因而具有较好的实用性。     

短杆菌(Brevibacterium sp WX-10)产酶条件研究

研究了碳源、氮源、无机盐、金属离子等培养基组成和初始pH、通风量、温度等发酵条件对短杆菌(Bre vibacteriumspWX 10)产酶的影响,通过正校试验优化得到的产酶培养基组成及发酵条件:蔗糖1%,NaCl2 5%,牛肉膏0 05%,NaNO30 05%,pH7 5,500mL三角瓶装培养基50mL,30℃于220r/min旋转式摇床上培养72h.在该培养条件下WX 10产酶量是原培养条件下的1 85倍.     

Bayesian locally optimal design of knockout tournaments

The elimination or knockout format is one of the most common designs for pairing competitors in tournaments and leagues. In each round of a knockout tournament, the losers are eliminated while the winners advance to the next round. Typically, the goal of such a design is to identify the overall best player. Using a common probability model for expressing relative player strengths, we develop an adaptive approach to pairing players each round in which the probability that the best player advances to the next round is maximized. We evaluate our method using simulated game outcomes under several data-generating mechanisms, and compare it to random pairings, to the standard knockout format, and to two variants of the standard format.     

考虑交通时间与设备转换时间的跨区域就医调度优化问题

在资源共享时代背景下,跨区域就医可以很好地解决患者日益增长的就医需求与医疗资源紧张的矛盾。本论文以医疗联盟为研究对象,在关键医疗资源共享的前提下,通过患者跨区域就医实现就医诊断延误最小化,以满足患者就医需求。本研究同时考虑了患者跨区域交通时间与基于患者诊断类型的设备转换时间,以最小化患者就医总延迟为目标,分配患者就诊医院及优化患者就诊/检查顺序。针对该问题,论文首次提出以最早交货期原则（EDD rule）为基础,以患者再分配为主导的EDD-ReAss1和EDD-ReAss2启发式算法,结合局部搜索算法以进一步提高就医调度方案的质量,缩短患者诊断/检查等待时间。实验结果表明,新启发式算法EDD-ReAss1和EDD-ReAss2算法性能显著好于EDD,SPT和LPT等调度规则;在较短运算时间内Swap局部搜索算法性能最优。     

“国培计划”培训团队建设政策的反思与改进--基于政策工具与政策要素的二维分析

培训团队建设是实施“国培计划”的基础工程,是保证“国培计划”实施质量的关键所在。“国培计划”培训团队建设政策是引领“国培计划”培训团队建设实践的重要依据。以2010-2019年“国培计划”培训团队建设政策文本为研究对象,基于政策工具与政策要素的二维分析框架展开研究。研究发现,“国培计划”培训团队建设政策经历了“建章立制”(2010-2012年)、“稳步发展”(2013-2014年)、“精准推进”(2015-2019年)三个阶段,呈现出政策工具差异化、团队成员多元化、运行机制精准化等特征,同时也暴露出政策工具运用失衡、团队建设目标不清晰、相关政策难以有效落地等问题。因此,“国培计划”培训团队建设要注重优化政策工具结构、明确团队建设目标、坚持因地因时制宜,进一步提升政策的长效性、持续性和精准性。     

中国粮食物流体系现代化建设策略

粮食物流体系是连接粮食生产和消费的重要一环,加快推进其现代化建设将有力保障我国的粮食安全。基于对现阶段中国粮食物流体系的全面调研,详细分析了我国粮食物流体系现代化建设的发展现状、存在问题和面临形势,并提出推进粮食物流体系现代化的策略。第一,提升粮食物流体系建设系统化水平,增强粮食流通能力;第二,加快粮食流通立法和标准化建设工作,打破要素流通制约;第三,提高粮食物流设施建设专业化水平,提升物流体系效能;第四,积极开展粮食物流体系信息化改革,优化资源配置效率;第五,统筹各地并优化资金配置,推进项目整体布局;第六,构建粮食流通“双循环”格局,培育国际化大粮商。     

Sampling from spatial databases

This paper deals with techniques for obtaining random point samples from spatial databases. We seek random points from a continuous domain (usually ²) which satisfy a spatial predicate that is represented in the database as a collection of polygons. Several applications of spatial sampling (e.g. environmental monitoring, agronomy, forestry, etc) are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). We discuss two fundamental approaches to sampling with spatial predicates, depending on whether we sample first or evaluate the predicate first. The approaches are described in the context of both quadtrees and R-trees, detailing the sample first, acceptance/rejection tree, and partial area tree algorithms. A sequential algorithm, the one-pass spatial reservoir algorithm is also described. The relative performance of the various sampling algorithms is compared and choice of preferred algorithms is suggested. We conclude with a short discussion of possible extensions.     

Sensitivity of the Optimum to Perturbations of the Profit or Weight of an Item in the Binary Knapsack Problem

In the binary single constraint Knapsack Problem, denoted KP, we are given a knapsack of fixed capacity c and a set of n items. Each item j, j = 1,...,n, has an associated size or weight w_j and a profit p_j. The goal is to determine whether or not item j, j = 1,...,n, should be included in the knapsack. The objective is to maximize the total profit without exceeding the capacity c of the knapsack. In this paper, we study the sensitivity of the optimum of the KP to perturbations of either the profit or the weight of an item. We give approximate and exact interval limits for both cases (profit and weight) and propose several polynomial time algorithms able to reach these interval limits. The performance of the proposed algorithms are evaluated on a large number of problem instances.     

A spanning heuristic for the unordered and ordered matching identification problem

The matching identification problem (MIP) is a combinatoric search problem related to the fields of learning from examples, boolean functions, and knowledge acquisition. The MIP involves identifying a single “goal” item from a large set of items. Because there is commonly a cost associated with evaluating each guess, the goal item should be identified in as few guesses as possible. As in most search problems, the items have a similar structure, which allows an evaluation of each guessed item. In other words, each guessed item elicits partial information about the goal item, i.e. how similar the guess is to the goal. With this information the goal is more quickly identified.The unordered MIP has been studied by Mehrez and Steinberg (ORSA J. Comput. 7 (1995) 211) in which they proposed two different types of algorithms. The purpose of the present paper is to suggest an improved Spanning Heuristic algorithm. Its improvement increases as the problem size increases. Further results and comparisons are derived for the unordered and ordered cases.This research shows that when the search space is very large, it is better to inquire from items that are known not to be the goal (they have been ruled out by previous guesses), for the purpose of acquiring more information about the goal. As the search space is narrowed, it is better to guess items that have not been ruled out.