Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models

We extend the recently introduced latent threshold dynamic models to include dependencies among the dynamic latent factors which underlie multivariate volatility. With an ability to induce time-varying sparsity in factor loadings, these models now also allow time-varying correlations among factors, which may be exploited in order to improve volatility forecasts. We couple multi-period, out-of-sample forecasting with portfolio analysis using standard and novel benchmark neutral portfolios. Detailed studies of stock index and FX time series include: multi-period, out-of-sample forecasting, statistical model comparisons, and portfolio performance testing using raw returns, risk-adjusted returns and portfolio volatility. We find uniform improvements on all measures relative to standard dynamic factor models. This is due to the parsimony of latent threshold models and their ability to exploit between-factor correlations so as to improve the characterization and prediction of volatility. These advances will be of interest to financial analysts, investors and practitioners, as well as to modeling researchers.     

基于成本优化的制造业生产物流装配线排序问题分析

为了降低制造业的生产成本，提高收益，在分析生产物流配线闲置和超载成本的基础上，采用粒子群算法对其进行优化，并利用模糊自适应改进惯性权值，通过实证研究表明该方法实用，可操作性强，可以有效降低制造业生产物流成本，具有广泛的应用价值。     

Linear programing models for portfolio optimization using a benchmark

We consider the problem of constructing a perturbed portfolio by utilizing a benchmark portfolio. We propose two computationally efficient portfolio optimization models, the mean-absolute deviation risk and the Dantzig-type, which can be solved using linear programing. These portfolio models push the existing benchmark toward the efficient frontier through sparse and stable asset selection. We implement these models on two benchmarks, a market index and the equally-weighted portfolio. We carry out an extensive out-of-sample analysis with 11 empirical datasets and simulated data. The proposed portfolios outperform the benchmark portfolio in various performance measures, including the mean return and Sharpe ratio.     

基于SD模型的诸城市农业结构仿真优化研究

［目的］预测2017—2035年诸城市农业结构的变化趋势，对农业结构进行多情景优化仿真，提出优化调整建议。［方法］文章以山东省诸城市作为研究对象，将农业结构划分为种植、种养结合和加工休闲3个子系统，选取56个指标，运用多元统计回归分析等方法构建41个方程，建立农业结构系统动力学（System Dynamics，简称SD）模型，运用Vensim—PLE软件进行仿真优化分析。［结果］SD模型预测结果表明，到2035年，粮食作物播种面积1105万hm2，总产量8037万t，经济作物播种面积652万hm2，总产量15203万t； 生猪出栏量达到29615万头，家禽出栏量1105 231亿只，畜禽粪污利用率8792%； 农业总产值达到25132亿元，休闲农业产值6134亿元，食品加工业产值1 25263亿元。假设种植业生产中的农业科技投入增加2个百分点， 2035年粮食作物产量较优化前增加576万t； 经济作物产量较优化前增加2814万t； 假设有机肥施用补贴增加3个百分点， 2035年畜禽粪污利用率较优化前提高762个百分点； 假设农产品加工业的研发力度和科技投入增加1个百分点， 2035年食品加工产值较优化前增加73521亿元； 农产品加工业产值占农业总产值比值由优化前的325：1达到41：1。［结论］为进一步推进诸城市农业结构调整，迫切需要加大农业科技投入，完善有机肥扶持政策，培育种养结合新型经营主体，重点扶持培育加工龙头企业，发展现代化休闲农场，促进农业产业融合发展。     

基于改进粒子群算法的无人机航迹规划

针对当前基本粒子群算法无人机航迹规划在后期收敛速度比较慢、效率不高、易陷入局部最优等问题,提出一种改进粒子群算法。首先,在迭代前期和后期分段设置惯性权值的调整,实现粒子惯性和寻优行为的平衡;其次,设置一个定值与相邻2次适应度函数最优值比较策略,防止陷入局部最优;最后,引入遗传算法的交叉、变异机制,得出更优的结果。并通过仿真验证了改进粒子群算法在三维空间航迹规划的有效性和可行性。结果表明,与其他航迹规划算法相比,新算法具有路径长度更短、耗时更少、路径更平滑等优点,加快了收敛速度,提高了航迹规划效率和稳定性。因此,改进算法的航迹规划可得到满足约束关系的最优航迹,对实现自主飞行有重要的参考价值。     

基于双层规划模型的冷链物流网络多目标优化

针对冷链物流时效性强这一特性,应用软时间窗反映客户满意度,并结合T.T.T理论换算货损成本。在考虑满足客户时间窗的条件下,寻找配送中心建设及操作成本、车辆成本、惩罚成本及货损成本所构成的总成本最小时的最优配送方案,建立冷链物流配送选址及路径优化的双层规划模型,并将改进的遗传算法运用到该模型中,借助Matlab软件对具体实例进行求解,得到最优结果,为冷链物流网络多目标优化问题提供理论依据。     

基于物联网的无人值守远程计量系统的设计与实现

针对厂矿计量系统的计量节点多,计量操作繁杂,人力成本较高,而且工作环境差,难于防范计量过程的作弊行为等诸多弊端,提出一种基于物联网的无人值守远程计量管理系统的设计.设计方案在充分利用已有硬件资源的基础上,通过RFID射频技术自动识别车牌、红外压边智能检测和视频监控技术等,对数据进行综合分析与管理,达到远程计量无人值守的目的.不但能使计量的数据信息及时准确,还能有效防止计量过程的作弊行为,进而实现优化企业资源配置,降低生产运营成本,提高管理效率,提升企业的市场竞争力.     

An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.     

基于SBO-PP模型的水资源可持续发展能力评价模型及应用

为利用投影寻踪(PP)技术科学,客观评价区域水资源可持续发展能力,基于生态环境、水资源和经济社会因素选取20个指标构建区域水资源可持续发展能力评价指标体系。利用新型仿生群体智能算法——凉亭鸟优化(SBO)算法优化PP技术最佳投影方向,提出SBO-PP水资源可持续发展能力评价模型,并构建灰狼优化(GWO)算法-PP模型、人工蜂群(ABC)算法-PP模型、差分进化(DE)算法-PP模型、地理生物学优化(BBO)算法-PP模型、粒子群优化(PSO)算法-PP模型作对比,以云南省2006—2015年及2020年水资源可持续发展能力评价为例进行实例研究。结果表明:SBO算法优化PP技术获得的适应度值优于GWO、ABC、DE、BBO和PSO算法,具有较好的求解精度、稳健性能和极值寻优能力。SBO-PP模型对云南省2006—2007年水资源可持续发展能力评价为"较差",2008—2015年评价为"中等",2020年评价为"较强"。     

Economies of Product Diversity in Collaborative Logistics

Collaborative logistics, also known as shipper collaboration, is a method of reducing the freight logistics cost of firms that produce and/or distribute tangible goods (shippers), which seeks to improve capacity utilizations of trucks. This study looks at this shipper collaboration problem in the U.S. truckload (TL) industry and proposes a new approach. Unlike other studies, which focused on reducing TL costs by utilizing economies of density, we present an approach that utilizes specific TL economies gained by mixing multiple products with different weight‐to‐volume ratios, which we call economies of product diversity. Using theoretical and empirical evidence, we show that the performance of shipper collaboration can be enhanced notably using this concept, economies of product diversity, which is currently overlooked in the literature.