Integrated order acceptance and supply chain scheduling problem with supplier selection and due date assignment

The importance, benefits, and impact of integration of decisions within supply chains have long been investigated by many researchers. Order acceptance and supplier selection are two of the most critical decisions for supply chain managers. Throughout the process of order acceptance, a manufacturer has to decide which orders to be accepted and processed and based on the accepted orders, the volume of required raw material is determined. On the other hand, a manufacturer aims to choose one or several suppliers among all possible choices to provide sufficient raw material for the accepted orders, subject to different criteria such as list price, transportation cost, etc. This paper addresses an integrated framework for profit maximization in an integrated supplier selection, order acceptance and scheduling problem in a single-machine environment with multiple customers. There is substantial literature on the problems of supplier selection and order acceptance; however, to the best of our knowledge, this paper is the first research that integrates these essential decisions in the form of a mathematical model to maximize the total profit. The problem is NP-hard in nature; therefore, solving to optimality is not practically possible for problems with medium and large size. For that purpose, we developed a Heuristic Algorithm (HA) to solve the problem above in a reasonable time, with proper accuracy. Results from this heuristic algorithm are compared with that of a commercial solver (GAMS) and the well-known Genetic Algorithm (GA) and Variable Neighborhood Search (VNS). Computational experiments demonstrate that the developed heuristic algorithm is more efficient in comparison with other tested methods.     

结合优化支持向量机与K-means++的工控系统入侵检测方法

针对工业控制系统传统单一检测算法模型对不同攻击类型检测率和检测速度不佳的问题，提出一种优化支持向量机和K-means++算法结合的入侵检测模型。首先利用主成分分析法（PCA）对原始数据集进行预处理，消除其相关性；其次在粒子群优化（PSO）算法的基础上加入自适应变异过程避免在训练的过程中陷入局部最优解；然后利用自适应变异粒子群优化（AMPSO）算法优化支持向量机的核函数和惩罚参数；最后利用密度中心法改进K-means算法与优化后的支持向量机组合成入侵检测模型，从而实现工业控制系统的异常检测。实验结果表明，所提方法在检测速度和对各类攻击的检测率上得到明显提升。     

基于GRA-GRNN模型的露天金属矿爆破后矿岩界线位移分析

为了避免露天金属矿爆破后导致爆堆边缘矿石品位贫化损失,需要根据最低品位阈值重新计算矿岩边界,而影响矿岩边界发生改变因素众多,需要确定主要影响因素。因此,利用爆堆爆破前地形方向和爆堆地质数据,构建灰色关联-广义回归神经网络模型(GRA-GRNN)分析爆堆矿岩边界变化主要影响因素。首先对爆堆钻孔品位数据使用析取克里金法进行空间插值,并根据矿山工艺最低品位阈值提取爆破前的矿岩边界;其次,将爆破前后的数字DEM模型进行求差,求得爆破后的爆堆数字DEM模型,并构建爆破前后爆堆数字DEM模型空间分布椭圆,从而确定爆堆爆破后的水平形变方向;对影响爆堆爆破后形变的可能因素进行提取,并应用GRA-GRNN模型选取主要影响因素及对其强度进行分析,并将其结果与BP神经网络模型预测结果进行了对比。从实验结果可知,影响爆堆爆破后形变强度排前三的因素为:爆破前地形方向、爆孔排距和列距,强度分别为0.880、0.760和0.755,预测结果优于BP模型。     

应用独立分量分析的激光测风雷达湍流频谱分解

针对大型风力发电机机组中常见的脉动湍流、风机尾流与涡流等湍流信号,研究了利用自然梯度下降的独立分量分析方法的湍流频谱分离效果,以区分中心风速与湍流信号,提高风机机组的综合工作效率。首先分析了风机组中常见湍流信号的后向散射与频谱分布特点,然后依据这些特点设计了对应的独立分量分析模型。在仿真结果符合要求的基础上,进行了双目激光雷达天线的风速采集与实际分离效果检测。实验结果表明,在大气折射率结构常数C2n≤10-14同时广义大气常数α≥4的通常情况下,利用双目信号能够分离出一个湍流中心和一个中心风速。对1 s内两个谱峰的波动范围进行统计,获得(2.59±0.05)MHz的中心风速以及(1.22±0.19)MHz的湍流中心估计,且二者的平均信噪比分别为25.93 dB和31.01 dB,能够在获得稳定的中心风速估计的同时得到一个较为稳定的湍流中心估计。     

基于熵权-灰色关联分析的电动汽车充电基础设施PPP项目风险评价研究

电动汽车充电基础设施PPP项目的建设和实施,不仅可以有效缓解政府财政和管理压力,还可以借助社会资本先进的管理运营经验,提高充电服务供给效率,实现双赢。但是,电动汽车充电基础设施PPP项目具有投资大、特许运营期长等特点,同时还涉及多个项目参与者,关系复杂,潜在的风险因素较多。文章通过文献梳理,首先识别出了电动汽车充电基础设施PPP项目潜在的风险因素,从宏观、中观、微观三个层次建立了基于项目全生命周期的风险评价指标体系,然后建立了基于熵权-灰色关联分析的项目风险评价模型。最后,以T市电动汽车充电基础设施PPP项目为例进行了实证分析,并根据风险评价的结果,从不同项目参与方的角度提出了风险应对的策略。     

基于matlab的电磁场仿真与分析

电磁场问题往往较为抽象，并且计算也相对比较复杂。为此，借助计算机软件对复杂问题进行求解的重要性也得到凸显。本文通过两个例子，着重介绍了matlab在电磁场仿真与数值分析中的应用。结果表明这一方法具有计算效率高，能使抽象的场的问题具体化的优点。     

An analysis model of diagnosis and treatment for COVID-19 pandemic based on medical information fusion

Exploring the complicated relationships underlying the clinical information is essential for the diagnosis and treatment of the Coronavirus Disease 2019 (COVID-19). Currently, few approaches are mature enough to show operational impact. Based on electronic medical records (EMRs) of 570 COVID-19 inpatients, we proposed an analysis model of diagnosis and treatment for COVID-19 based on the machine learning algorithms and complex networks. Introducing the medical information fusion, we constructed the heterogeneous information network to discover the complex relationships among the syndromes, symptoms, and medicines. We generated the numerical symptom (medicine) embeddings and divided them into seven communities (syndromes) using the combination of Skip-Gram model and Spectral Clustering (SC) algorithm. After analyzing the symptoms and medicine networks, we identified the key factors using six evaluation metrics of node centrality. The experimental results indicate that the proposed analysis model is capable of discovering the critical symptoms and symptom distribution for diagnosis; the key medicines and medicine combinations for treatment. Based on the latest COVID-19 clinical guidelines, this model could result in the higher accuracy results than the other representative clustering algorithms. Furthermore, the proposed model is able to provide tremendously valuable guidance and help the physicians to combat the COVID-19.     

液滴撞击液膜过程气泡卷吸的FTM数值模拟

采用界面追踪法(front tracking method,FTM)对液滴撞击液膜形成的气泡卷吸现象进行直接数值模拟,分析不同无量纲液膜厚度(H*)和不同Bo对卷吸气泡出现时间和消失时间的影响。结果表明:在Bo=4.00时,H*的增加会使得卷吸气泡出现和消失的时间提前,并且在H*0.415时,卷吸气泡不再出现;在H*分别为0.250和0.150时,卷吸气泡不再出现的临界Bo分别为3.58和3.19,但不同的H*对卷吸气泡出现和消失的时间的影响与固定Bo时趋势一致。     

Implementing lean practices in manufacturing SMEs: testing ‘critical success factors’ using Necessary Condition Analysis

Lean practices are known to increase operational performance. Previous research has identified critical success factors for implementing lean practices. This research aims to examine the extent to which success factors are critical for various degrees of lean practice implementation. Using multiple-respondent self-assessments from 33 Dutch manufacturing small and medium-sized enterprises (SMEs), we conducted a Necessary Condition Analysis. Our findings indicated that the criticality of success factors is progression dependent. In the initial stages of the lean journey, SMEs could improve their lean practices in a bottom-up manner through local factors such as a learning focus, improvement training and support congruence. When lean practices are more advanced, some company-wide factors must be present: top management support, a shared improvement vision and a supplier link. Our findings question the universality of success factors such as strategic involvement and indicate the need for a more dynamic model of lean implementation.     

Porous ceramics with tailored pore size and morphology as substrates for coral larval settlement

The growing demand for stony corals as ornamental aquarium animals requires defined aquacultural breeding strategies. For the sexual propagation of corals, material substrates are needed, that attract larvae and support their settlement and development. In this study, five types of highly porous ceramic materials were developed following the example of coral skeleton. The applicability of these settlement substrates was tested using larvae of the stony coral Pocillopora damicornis. Partial sintering of pressed clay pellets, freeze casting of clay and alumina-mullite based slurries and direct foaming of high alkane phase emulsified suspensions (HAPES) using alumina were employed. By the addition of mm-sized spherical polystyrene beads as sacrificial templates during freeze casting (alumina-mullite), superficial pores in the size of the larvae were created. The inorganic substrates featured open porosities between 35% (pressed clay) and 83% (foamed alumina), pore sizes ranging from nm to mm-scale and pore morphologies dominated by interparticle porosity (pressed), lamellar pores (freeze casting) and cellular pore types (direct foaming). The ceramic substrates were incubated in artificial sea water for 3 months to induce necessary biofilm formation and algae growth. Afterwards, individual substrates were exposed to 5 coral larvae, and their settlement behavior was monitored over 14 days. At the end of this period, all ceramic materials were successfully accepted as settlement substrates, with a mean settlement rate of 46.2%, and no significant differences between the substrate types. On samples with large surface superficial pores, a significantly reduced survival of settled larvae (79%) compared to the other porous materials (93–98%) was determined, suggesting a non-ideal surface topography. While alumina foam samples (HAPES) exhibit the most promising results in terms of settlement and survival of larvae, clay-based substrates provide a more economic solution for the sexual propagation of corals in aquaculture.