基于遗传算法的企业配送路径问题研究

为提高企业竞争力,加快企业发展,企业已将优化重点转向物流配送环节,文中通过遗传算法设计并求解企业配送路径问题,设计合理的配送路线,提高配送效率,降低物流成本。     

遗传算法在军事物流运输路径选择中的运用

对物流中常见的运输路径选择问题进行了基于遗传算法的的分析，并主要针对军事目的中的时间限制问题（时间窗），结合军事物流的特点，对其遗传算法模型进行了一定的改进。     

一种汽车后侧推拉窗的设计及问题分析

文章介绍了某汽车公司一款微型车后侧推拉窗设计所使用的密封结构,即后侧窗固定玻璃、滑动玻璃与窗框胶条、中间密封条之间的配合衔接关系,并对其设计过程遇到的问题进行分析和解剖。     

浅析建筑外窗抗风压性能

抗风压性能是衡量建筑外窗物理性能的重要环节,结合外窗检测过程中遇到的一些问题,根据工作实践,浅谈影响窗户抗风压性能的几个原因。     

浅谈服装专卖店设计要素

本文探讨多种设计要素完美结合的有效性和可行性,以求较全面地反映专卖店设计要素在体现品牌文化,提升空间档次,营造购物的良好氛围时的一些基本规律,希望能对品牌服装专卖店设计实践起到一定的借鉴意义和参考价值。     

考虑多模糊时间窗医药物流配送路径优化

以医药物流客户满意度最大和总成本最低为目标,建立了考虑多模糊时间窗的车辆路径问题优化模型。为满足低碳物流的要求,在路径规划中引入碳排放成本,为防止类似大型医疗器械运输超载问题引入超载惩罚项,引入多模糊时间窗来评价客户在可以忍受送达时间段和期待送达时间段的满意度。以单个配送中心3辆配送车辆25个客户为算例,运用遗传算法对模型求解,求解得到的最优车辆配送路径提高了满意度并降低了总成本。该模型亦适用于满足相应约束条件的类似行业的供应链优化。     

“压缩动态虚拟视窗算法”在自动拣选系统中的应用

对自动拣选系统工作模式及工作步骤进行分析,给出压缩动态虚拟视窗算法数学模型,在此基础上,设计应用算法,使压缩动态虚拟视窗算法的使用方法明确化。     

浅谈夏热冬冷地区建筑外窗及外窗玻璃对建筑能耗的影响

本文从国外及我国建筑外窗现状、外窗开启扇对建筑物使用的影响、外窗玻璃的性能分析、培养被动节能的习惯,这四个方面阐述建筑外窗及外窗玻璃对建筑能耗的影响。     

Out-of-sample forecasts of China's economic growth and inflation using rolling weighted least squares

Macroeconomic forecasting in China is essential for the government to take proper policy decisions on government expenditure and money supply, among other matters. The existing literature on forecasting Chinas macroeconomic variables is unclear on the crucial issue of how to choose an optimal window to estimate parameters with rolling out-of-sample forecasts. This study fills this gap in forecasting economic growth and inflation in China, by using the rolling weighted least squares (WLS) with the practically feasible cross-validation (CV) procedure of Hong et al. (2018) to choose an optimal estimation window. We undertake an empirical analysis of monthly data on up to 30 candidate indicators (mainly asset prices) for a span of 17 years (2000–2017). It is documented that the forecasting performance of rolling estimation is sensitive to the selection of rolling windows. The empirical analysis shows that the rolling WLS with the CV-based rolling window outperforms other rolling methods on univariate regressions in most cases. One possible explanation for this is that these macroeconomic variables often suffer from structural changes due to changes in institutional reforms, policies, crises, and other factors. Furthermore, we find that, in most cases, asset prices are key variables for forecasting macroeconomic variables, especially output growth rate.     

Use of the Proceeds and Long‐term Performance of French SEO Firms

This paper examines the long‐term stock performance of French SEO with rights by looking at the intended use of the proceeds. Firms that raise equity for pure capital structure motives are separated from the ones that use the SEO proceeds to finance specific investment projects. Issuers in the first category are concerned about preserving their financial flexibility and they are expected to evolve in a capital structure irrelevancy framework. On the other hand, issuers in the second category are more inclined to be sensitive to adverse selection problems or agency conflicts and thus, they should be more exposed to under‐reaction on the long‐run. According to a matching firm methodology, ‘Financing New Investment’ issuers underperform their benchmark at a rate of 4% to 8% per year over a 36‐month horizon while ‘Capital Structure’ issuers do not show any abnormal performance. These results are robust according to alternative Beta pricing models. In addition, managers of both issuer's types time the SEO after a period of positive abnormal performance in order to sell overpriced securities. However, only the ‘Financing New Investment’ sample experiences a performance reversal; the abnormal returns decreasing gradually from the issue on, to become significantly negative 24 months after the event.