港口物流与区域产业结构优化--基于湛江市的实证

基于2004-2014年的数据,采用灰色关联度和线性回归模型对湛江市港口物流与区域产业结构优化效应进行分析。结果显示：港口物流两大指标与湛江市 GDP 及三大产业的平均关联度均超过0.7,回归分析亦得到同样的结果,说明发展港口物流对区域经济增长和产业结构优化有重要作用。优化湛江市产业结构,可以从做好临港产业发展规划,引导钢铁和石化产业集聚;完善港口物流基础设施,大力发展集装箱运输;积极推进内陆无水港建设,拓宽内陆经济腹地;大力推进"保税物流中心"建设,推动区港联动发展等几个方面进行。     

结构优化对我国农产品出口竞争力的影响

应用产业组织理论,揭示结构优化对农产品国际竞争力的作用机理。以RCA衡量农产品出口竞争力并建立多元回归模型,在有效分离工资、土地灌溉面积和汇率等因素后,实证研究发现技术结构对农产品出口竞争力有显著正向影响。当前经济背景下,提升农产品出口竞争力的政策思路,需从传统的要素禀赋优势转移到结构优化的轨道上来。优化农产品出口结构,政府需加大对高附加值农产品在生产、流通、出口等环节的支持力度,营造寡占的农产品市场结构,鼓励和扶持创意农业的发展。     

基于粒子群算法与改进Ziegler-Nichols算法的PID整定方法

针对Ziegler-Nichols算法设计的PID控制器阶跃响应不理想,不具有灵活性等缺点,提出基于粒子群算法与改进 Ziegler-Nichols算法的PID整定方法。采用粒子群算法优化了Ziegler-Nichols算法中的幅值和相角,设计了具有更好性能 指标的PID控制器。实验结果表明采用该方法进行参数整定后的PID控制器响应速度较快,降低了系统的超调量。     

基于灰色系统的小型精密机床热误差模型

为减少热误差对数控机床加工精度的影响,文章利用灰色系统研究热误差建模。初步分析机床热源后,应用灰 色关联度分析结合模糊分类方法优化得到13组关键温度测点,结合小型精密五轴机床处于实际加工状态时的实验数 据,应用GM(I,N)灰色结构进行建模。将实际数据与拟合数据进行对比分析,结果表明此灰色系统模型具有计算方法 成熟、鲁棒性强的特点,适用于机床热误差研究。     

模具钢干铣削试验及参数优化研究

为了对铣削力做进一步的研究,以及预测铣削参数的改变对铣削力变化的影响,文章建立了铣削力预测模型,引 入了PSO优化算法。试验采用正交设计方法,干式铣削SKD61模具钢;KISTLER测力仪测量铣削力;HRsoft_DW数采软 件采集试验数据,并对数据进行极差分析。研究结果表明每齿进给量是铣削参数中影响铣削力最为主要的因素。研究 验证了PSO算法对铣削参数优化问题具有有效性。     

大学生认知方式与德育方法的优化

认知方式划分为场依存和场独立两种类型,大学生认知方式与德育方法实施产生的效果有相关性。笔者认为应构建"以人为本"的德育方法论体系,根据大学生不同的认知方式采取分类指导原则,实施相应的有针对性和实效性的德育方法。     

An oracle-based algorithm for robust planning of production routing problems in closed-loop supply chains of beverage glass bottles

The demand for glass bottles is exhibiting an upward trend over time. The manufacturing of glass bottles is costlier in terms of time and resources and is associated with a higher level of heat generation and environmental pollution compared to recycling processes. In response to the aforementioned challenges, companies that use glass bottles need to implement strategies to manage their reverse supply chains in conjunction with their traditional supply chains, as the economic and environmental benefits of returned products are unquestionable. Closed-loop supply chains (CLSCs) integrate forward and reverse flows of products and information. This integration helps companies to have a broader view of the whole chain. Despite these advantages, managing CLSCs can be challenging as they are exposed to many uncertainties regarding supply and demand processes, travel times, and quantity/quality of returned products.In this study, we consider the production planning, inventory management, and vehicle routing decisions of a CLSC of beverage glass bottles. We propose an MILP model and rely on a multi-stage adjustable robust optimization (ARO) formulation to deal with the randomness in both the demand for filled bottles and the requests for pickups of empty bottles. We develop an exact oracle-based algorithm to solve the ARO problem and propose a heuristic search algorithm to reduce the solution time. Our numerical experiments not only show the incompetency of the customary method, namely the affine decision rule approach, but also illustrate how our algorithms can solve the small-size problems and significantly improve the quality of the obtained solution for large problems. Furthermore, our numerical results show that robust plans tend to be sparse, meaning the routes are chosen so that empty bottles are transported to production sites in such a way that fewer new bottles need to be ordered. Thus, robust planning makes the CLSCs more environmentally friendly.     

Reconstruction of populations by stochastic optimization: Sensitivity analysis

The reconstruction of populations by stochastic optimization solves the nontrivial problem of finding demographic flows from population registers or vital statistics and censuses, if available. These flows allow the reconstruction of stocks (age pyramids and vital statistics). After a review of reconstruction methods, the sensitivity analysis shows the robustness of the method by stochastic optimization to flawed or missing values, to the length of the reconstruction period, and to variations in the actual demographic flows.     

A note on the non-negativity of continuous-time ARMA and GARCH processes

A general approach for modeling the volatility process in continuous-time is based on the convolution of a kernel with a non-decreasing Lévy process, which is non-negative if the kernel is non-negative. Within the framework of Continuous-time Auto-Regressive Moving-Average (CARMA) processes, we derive a necessary condition for the kernel to be non-negative, and propose a numerical method for checking the non-negativity of a kernel function. These results can be lifted to solving a similar problem with another approach to modeling volatility via the COntinuous-time Generalized Auto-Regressive Conditional Heteroscedastic (COGARCH) processes.     

河北省金融资源充分利用的路径选择

在开放的市场条件下,金融作为现代经济的核心,其资源的优化配置对区域经济发展有着及其重要的作用,本文根据河北省金融资源配置现状,分析了河北省金融资源利用中存在的问题,指出要充分利用河北省金融资源,必须从调整经济产业结构、改善金融生态环境、抑制金融资源外流和提高金融业自身水平做起。只有这样才能提高河北金融的竞争能力,促进河北经济的整体发展。