中国决策情境下的多源流模型及其优化研究

作为当今公共政策研究领域最炙手可热的理论模型之一,约翰·金登的多源流分析理论业已得到国内外学者的广泛应用与认可。在对该模型的相关内容进行简单铺陈后,通过辨析国内外不同的政策主体参与逻辑,进一步厘清了我国公共决策的独有特征。研究重点是在整合提炼西方既有修正思路的基础上,沿袭模型的模糊性假设,结合我国具体实践案例,对多源流模型进行优化与补充。研究表明,中国决策情境下的多源流模型优化主要有提高源流间的融合性、政治源流的核心化、焦点事件的独立化以及特殊情况下的临时决策等四种路径,四种优化与补充路径的有机结合将为进一步提升模型适用性提供帮助。     

Particle swarm optimization based Liu-type estimator

In this study, a new method for the estimation of the shrinkage and biasing parameters of Liu-type estimator is proposed. Because k is kept constant and d is optimized in Liu’s method, a (k, d) pair is not guaranteed to be the optimal point in terms of the mean square error of the parameters. The optimum (k, d) pair that minimizes the mean square error, which is a function of the parameters k and d, should be estimated through a simultaneous optimization process rather than through a two-stage process. In this study, by utilizing a different objective function, the parameters k and d are optimized simultaneously with the particle swarm optimization technique.     

Modified genetic algorithm-based clustering for probability density functions

This article modifies two internal validity measures and applies them to evaluate the quality of clustering for probability density functions (pdfs). Based on these measures, we propose a new modified genetic algorithm called GA-CDF to establish the suitable clusters for pdfs. The proposed algorithm is tested by four numerical examples including two synthetic data sets and two real data sets. These examples illustrate the superiority of proposed algorithm over some existing algorithms in evaluating the internal or external validity measures. It demonstrates the feasibility and applicability of the GA-CDF for practical problems in data mining.     

On algorithmic construction of maximin distance designs

Maximin distance designs are useful for conducting expensive computer experiments. In this article, we compare some global optimization algorithms for constructing such designs. We also introduce several related space-filling designs, including nested maximin distance designs, sliced maximin distance designs, and general maximin distance designs with better projection properties. These designs possess more flexible structures than their analogs in the literature. Examples of these designs constructed by the algorithms are presented.     

采矿工程专业人才培养方案优化与实践

随着全球经济一体化的发展,我国煤炭行业得到了快速发展,煤炭工业需要大量的高素质复合型采矿工程专业毕业生,因此,修订和完善采矿专业人才培养方案具有重要意义。河南理工大学采矿工程专业为了不断提高人才培养质量,对采矿工程专业人才培养方案进行了优化,2010年10月通过全国工程教育专家委员会的认证工作。新的人才培养方案已经得到实施,效果明显。     

大学生专业操作能力优化教学模式的构建——以人力资源管理专业课程为例

高校人才培养与企业实际需求存在匹配度较低的问题,因而有必要构建新的大学生专业操作能力优化教学模式.新的教学模式涵盖目标描述、目标支撑、流程管理、经验教训、工具与表单五个方面.它可以让学生的学习从抽象到具体,从理论到实践,从宏观到微观,从被动接受到主动思考,达到对该模块更深刻的学习、掌握与运用,从而更加适应企业与社会的需求.     

地方高校大学英语课程结构的优化

本文阐述了地方高校大学英语教学长期延用的课程结构体系中存在的一些主要问题,并针对这些问题,提出了建立新型课程结构应该考虑的五个方面。     

基本药物遴选方法的宏观经济效果比较

基本药物遴选的结果与百姓医保报销利益密切相关。我国医改新政关于基本药物遴选的方法学习西方国家，又有所发展。应用比较经济学原理，使用中国统计年鉴数据，测量了世界卫生组织的专家委员会法、中国现行的专家库两轮评审法、循证评价法、药物经济法等四种方法遴选所得基本药物方案的宏观卫生经济数据，得出在医疗卫生体制改革的社会医学领域可以借鉴自然科学统筹优化的组合方法，以获得综合更优的社会期望。     

Bounding Optimal Expected Revenues for Assortment Optimization under Mixtures of Multinomial Logits

We consider assortment problems under a mixture of multinomial logit models. There is a fixed revenue associated with each product. There are multiple customer types. Customers of different types choose according to different multinomial logit models whose parameters depend on the type of the customer. The goal is to find a set of products to offer so as to maximize the expected revenue obtained over all customer types. This assortment problem under the multinomial logit model with multiple customer types is NP‐complete. Although there are heuristics to find good assortments, it is difficult to verify the optimality gap of the heuristics. In this study, motivated by the difficulty of finding optimal solutions and verifying the optimality gap of heuristics, we develop an approach to construct an upper bound on the optimal expected revenue. Our approach can quickly provide upper bounds and these upper bounds can be quite tight. In our computational experiments, over a large set of randomly generated problem instances, the upper bounds provided by our approach deviate from the optimal expected revenues by 0.15% on average and by less than one percent in the worst case. By using our upper bounds, we are able to verify the optimality gaps of a greedy heuristic accurately, even when optimal solutions are not available.     

供需不确定条件下基于CVaR的零售商库存鲁棒优化模型

在经典报童模型下考虑供应和需求不确定性,研究了具有风险厌恶的零售商库存优化问题。采用条件风险值（CVaR）对库存绩效进行度量,构建了基于CVaR的零售商库存运作模型;在此基础上,考虑上游供应商供货能力和下游市场需求不确定性,并采用一系列未知概率的离散情景进行描述,给出了供需不确定条件下基于CVaR的零售商库存鲁棒优化模型。进一步,采用区间不确定集对未知情景概率进行建模,给出了基于最大最小准则的鲁棒对应模型。针对同时考虑供需不确定性导致的模型非凸性,采用标准对偶理论将其转化为易于求解的数学规划问题。最后,通过数值计算分析了不同风险厌恶程度和不确定性程度对零售商库存决策以及库存绩效的影响。结果表明,供需不确定性的存在虽然会导致零售商库存绩效损失,但损失值较小。特别地,依据文中模型得到的鲁棒库存策略在多数情况下能够保证零售商获得更优的库存绩效。此外,不确定性和风险厌恶程度的增加虽然会影响零售商库存决策和运作绩效,但在同等风险厌恶态度下,随着不确定性程度的增加,基于文中方法得到的鲁棒库存策略仍能确保零售商获得理想的库存绩效,表明文中所建模型在应对供需不确定性方面具有良好的鲁棒性。