双层过道布置问题的混合整数非线性规划模型及两阶段改进模拟退火算法

结合实际布局活动中，设施在多层空间布置的实际情况，提出了双层过道布置问题，并构建了该问题的混合整数非线性规划（MINLP）模型。针对问题特征，提出了一种改进模拟退火算法，通过采用两阶段改进策略，对退火过程及抽样过程进行改进。该算法以自适应搜索策略替代马氏链搜索长度，并引入记忆功能、回火操作以提高求解质量，通过设置双阈值来提高求解效率。应用所提算法对24个基准算例进行测试，并将其与原模拟退火算法和GUROBI精确方法作对比，验证了所提算法的有效性。     

基于学科竞赛的中医药类院校程序设计课程教学模式的探索

高素质人才培养是我国可持续发展战略、科教兴国战略以及人才强国战略等多项发展战略的一项基础性工程。本文针对中医药类院校程序设计类课程实践教学模式单一等教学实际，以“学科竞赛”为平台，“赛教结合”为理念，以《C语言程序设计》为例，从现存问题、赛教结合模式的引入、建立实施及其评价机制4个方面展开阐述，旨在提高学生学习积极性和能力。     

高温深井通风降温技术的适用条件研究

随着矿山开采深度的不断增加，“三高一扰动”恶劣开采环境问题日益突出，给矿井通风降温工作带来极大困难。对于深井矿山，仅采用通风降温难以满足深部开采的需要，系统研究高温深井矿山通风降温技术的适用性问题，对矿山深部开采具有重要的理论意义和工程适用价值。首先从热力学角度，揭示风流在通风线路中的热交换规律；其次利用差分法原理计算深井筒风流温度，并依此推导出巷道和回采工作面风流温度变化趋势；然后结合采场安全生产允许温度进行反推，最终获取通风降温条件下的可采极限深度计算公式，并选取广西铜坑矿锌多金属矿体作为工程应用试验区进行论证分析。结果表明：基于风流的热交换模型可以推导出风流在井筒、巷道及工作面的温度计算公式，该公式与低温梯度、风流流经路径长度有关；假定工作面温度达到安全开采允许最高温度，可反推出该条件下矿山可采极限深度和巷道通风极限长度（仅采用通风降温措施时）；基于铜坑矿区锌多金属矿的实际条件，代入相关数据，验证计算所得极限开采深度符合实际，即所推导公式是可行的。     

A dual Newton strategy for tree‐sparse quadratic programs and its implementation in the open‐source software treeQP

This paper presents a dual Newton scheme for tree‐sparse quadratic programs as they may arise in the field of stochastic programming. Previous work suggests to introduce auxiliary variables to decompose the tree into scenarios and use Newton's method to solve a dual problem formulation. Following a different approach, we apply the same principle directly on the tree‐sparse problem, avoiding the increase in dimensionality. In combination with a tailored algorithm for the calculation of the step direction, which is typically the most expensive operation per iteration, the proposed algorithm achieves a linear complexity in the number of nodes and supports parallel processing of the tree branches in a stage‐wise fashion. An open‐source implementation of the presented dual Newton strategy is publicly available in treeQP , a toolbox of open‐source solvers for tree‐sparse quadratic programs.     

Probabilistic tree-based representation for solving minimum cost integer flow problems with nonlinear non-convex cost functions

The minimum cost flow problem (MCFP) is the most generic variation of the network flow problem which aims to transfer a commodity throughout the network to satisfy demands. The problem size (in terms of the number of nodes and arcs) and the shape of the cost function are the most critical factors when considering MCFPs. Existing mathematical programming techniques often assume the cost functions to be linear or convex. Unfortunately, the linearity and convexity assumptions are too restrictive for modelling many real-world scenarios. In addition, many real-world MCFPs are large-scale, with networks having a large number of nodes and arcs. In this paper, we propose a probabilistic tree-based genetic algorithm (PTbGA) for solving large-scale minimum cost integer flow problems with nonlinear non-convex cost functions. We first compare this probabilistic tree-based representation scheme with the priority-based representation scheme, which is the most commonly-used representation for solving MCFPs. We then compare the performance of PTbGA with that of the priority-based genetic algorithm (PrGA), and two state-of-the-art mathematical solvers on a set of MCFP instances. Our experimental results demonstrate the superiority and efficiency of PTbGA in dealing with large-sized MCFPs, as compared to the PrGA method and the mathematical solvers.     

Uncertain location–allocation decisions for a bi-objective two-stage supply chain network design problem with environmental impacts

In the cases that the historical data of an uncertain event is not available, belief degree-based uncertainty theory is a useful tool to reflect such uncertainty. This study focuses on uncertain bi-objective supply chain network design problem with cost and environmental impacts under uncertainty. As such network may be designed for the first time in a geographical region, this problem is modelled by the concepts of belief degree-based uncertainty theory. This article is almost the first study on belief degree-based uncertain supply chain network design problem with environmental impacts. Two approaches such as expected value model and chance-constrained model are applied to convert the proposed uncertain problem to its crisp form. The obtained crisp forms are solved by some multi-objective optimization approaches of the literature such as TH, Niroomand, MMNV. A deep computational study with several test problems are performed to study the performance of the crisp models and the solution approaches. According to the results, the obtained crisp formulations are highly sensitive to the changes in the value of the cost parameters. On the other hand, Niroomand and MMNV solution approaches perform better than other solution approaches from the solution quality point of view.     

风传感器故障检测与诊断

文章详细介绍了风传感器的组成和工作原理。从传感器原理出发,分析了洛阳机场风速风向传感器(WAA151/WAV151)常见故障,探讨解决方法,并对维护要点进行总结,为业务人员维护和维修风传感器提供参考。     

Maternal Malnutrition Affects Hepatic Metabolism through Decreased Hepatic Taurine Levels and Changes in HNF4A Methylation

Fetal programming implies that the maternal diet during pregnancy affects the long-term health of offspring. Although maternal diet influences metabolic disorders and non-alcoholic fatty liver disease in offspring, the hepatic mechanisms related to metabolites are still unknown. Here, we investigated the maternal diet-related alterations in metabolites and the biological pathway in male offspring at three months of age. Pregnant rats were exposed to 50% food restriction during the prenatal period or a 45% high-fat diet during the prenatal and postnatal periods. The male offspring exposed to food restriction and high-fat diets had lower birth weights than controls, but had a catch-up growth spurt at three months of age. Hepatic taurine levels decreased in both groups compared to controls. The decreased hepatic taurine levels in offspring affected excessive lipid accumulation through changes in hepatocyte nuclear factor 4 A methylation. Moreover, the alteration of gluconeogenesis in offspring exposed to food restriction was observed to a similar extent as that of offspring exposed to a high fat diet. These results indicate that maternal diet affects the dysregulation in hepatic metabolism through changes in taurine levels and HNF4A methylation, and predisposes the offspring to Type 2 diabetes and non-alcoholic fatty liver disease in later life.     

Design of energy‐efficient train speed profiles considering fixed‐block signaling system

In dense traffic railway networks, trains may often slow down or stop between stations owing to previous train delays. If preceding train trajectory can be predicted, energy‐efficient driving can be achieved by suppressing unnecessary speed changes. In this paper, we propose an algorithm to find energy‐efficient driving considering fixed‐block signaling (FBS) system by using dynamic programming (DP). DP is suitable for use because it can optimize the control inputs with discrete and state constraints. In this paper, we discuss energy‐efficient driving by considering a FBS system using some case studies of simulation. In the simulation, we examine a technique to drive an express train in an energy‐efficient way when the preceding local train is running toward the station with passing loops. The results show that the proposed method can derive complex speed profiles for energy‐efficient driving and the train can be operated with a maximum reduced energy consumption of 8.3%.     

符合阿贝原则的数控机床几何误差建模

为提高现有数控机床空间误差分析方法的准确度,本文基于阿贝原则对齐次转换矩阵(HTM)几何误差补偿模型进行优化。首先,推导出XYFZ型三轴机床适用的HTM几何误差补偿模型并给出模型正确使用的前提条件;然后,基于阿贝原则分析了三轴机床的空间误差传递机理,指出阿贝误差对机床定位精度的影响,给出理论计算公式并在机床运动轴上进行实验验证;最后,基于阿贝原则和布莱恩原则对现有的HTM几何误差补偿模型进行优化,采用该模型拟合体对角线空间误差,并与实测机床体对角线误差进行对比验证。现有HTM几何补偿模型可将机床空间误差由41.15μm补偿至16.37μm,补偿率为60.22%;优化后的补偿模型可将机床空间误差补偿至5.32μm,补偿率为87.07%,提高了26.85%。实验结果表明,优化后的补偿模型更加合理,进一步改善了空间误差的补偿精度。