Airline planning and scheduling: Models and solution methodologies

The airline industry is a representative industry with high cost and low profitability. Therefore, airlines should carefully plan their schedules to ensure that overall profit is maximized. We review the literature on airline planning and scheduling and focus on mathematical formulations and solution methodologies. Our research framework is anchored on three major problems in the airline scheduling, namely, fleet assignment, aircraft routing, and crew scheduling. General formulation, widely used solution approaches, and important extensions are presented for each problem and integrated problems. We conclude the review by identifying promising areas for further research.     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

基于深度学习的安全缺陷报告预测方法实证研究

软件安全问题的发生在大多数情况下会造成非常严重的后果，及早发现安全问题，是预防安全事故的关键手段之一.安全缺陷报告预测可以辅助开发人员及早发现被测软件中潜藏的安全缺陷，从而尽早得以修复.然而，由于安全缺陷在实际项目中的数量较少，而且特征复杂（即安全缺陷类型繁多，不同类型安全缺陷特征差异性较大），这使得手工提取特征相对困难，并随后造成传统机器学习分类算法在安全缺陷报告预测性能方面存在一定的瓶颈.针对该问题，提出基于深度学习的安全缺陷报告预测方法，采用深度文本挖掘模型TextCNN和TextRNN构建安全缺陷报告预测模型；针对安全缺陷报告文本特征，使用skip-grams方式构建词嵌入矩阵，并借助注意力机制对TextRNN模型进行优化.所构建的模型在5个不同规模的安全缺陷报告数据集上展开了大规模实证研究，实证结果表明：深度学习模型在80%的实验案例中都要优于传统机器学习分类算法，性能指标F1-score平均可提升0.258，在最好的情况下甚至可以提升0.535.除此之外，针对安全缺陷报告数据集存在的类不均衡问题，对不同采样方法进行了实证研究，并对结果进行了分析.     

A prediction-based dynamic file assignment strategy for parallel file systems

Nowadays, the rapid development of the internet calls for a high performance file system, and a lot of efforts have already been devoted to the issue of assigning nonpartitioned files in a parallel file system with the aim of pursuing a prompt response to requests. Yet most of the existing strategies still fail to bring about an optimal performance on system mean response time metrics, and new strategies which can achieve better performance in terms of mean response time become indispensable for parallel file systems. This paper, while addressing the issue of assigning nonpartitioned files in parallel file systems where the file accesses exhibit Poisson arrival rates and fixed service times, presents an on-line file assignment strategy, named prediction-based dynamic file assignment (PDFA), to minimize the mean response time among disks under different workload conditions, and a comparison of the PDFA with the well-known file assignment algorithms, such as HP and SOR. Comprehensive experimental results show that PDFA is able to improve the performance consistently in terms of mean response time among all algorithms for comparison.     

A multiobjective integrated multiproject scheduling and multiskilled workforce assignment model considering learning effect under uncertainty

Today, organizations try to decline academically expenses using humans and resources in addition to rising managers and operators' satisfaction. Meantime, a very important step in the process of decision is the assignment of human resources, particularly in connection with research and development (R&D) projects in which the system is highly dependent on the capabilities of human resources. In this study, we tried all the assumptions that come true in the real world, considered a model for applied R&D projects to reduce costs and increase the efficiency of projects. Therefore, an integrated multiproject scheduling and multiskill human resource assignment model under uncertainty has developed for R&D projects. Furthermore, it is assumed that the activity processing time is related to human resources assignment that means the learning effect is considered. To demonstrate the proposed model efficiency, the various dimensions instance problem was solved accurately and efficiently in GAMS software, and the results have been reported. In addition, the proposed model is validated through the input parameter sensitivity analysis. The results indicate a suitable performance of the proposed fuzzy mathematical programming model is due to the complexity of the problem.     

有色金属工业如何面向新世纪

在本地纪初，我国有色金属工业面临着新的国际环境和市场形势，应以市场为导向，提高经济效益，促进科技进步，加快结构调整，培育有国际竞争力的大型企业集团。     

实行会计委派制可行性的探讨

探讨了为治理会计信息失真而实行的会计委派制在实际工作中的利弊，认为实行会计委派制不能从根本上解决会计信息失真的问题。     

遗传-蚁群算法在目标分配问题中的应用研究

针对传统算法很难满足大型水面舰艇编队防空武器的武器目标分配(weapon target assignment,WTA)问题,提出一种将遗传算法融入蚁群算法的混合算法。分析了遗传算法和蚁群算法的优缺点、利用遗传算法快速全局随机搜索能力生成一组粗略解,用其作为蚁群算法的初始信息素,再利用蚁群算法的并行性、正反馈机制,最后求得最优解,并对遗传-蚁群算法与蚁群算法、遗传算法这3种方法进行仿真比较。分析结果证明:遗传-蚁群算法用更少的时间获得最优的火力分配方案,缩短了武器系统反应时间,在求解质量方面有较大优势。     

劲性水泥土连续墙的抗弯刚度研究

阐述了劲性水泥土连续墙的工作机理，指出水泥土对荷载具有分担作用并对结构体的刚度具有贡献，而且这种分担作用和贡献将随荷载的变化而变化。将劲性水泥土连续墙体在荷载作用下的变形过程分为5个阶段，分析了各阶段结构有效截面和截面应力分布的演变情况，推导了在工程应力允许范围内连续墙结构刚度的计算式，并通过试验验证了计算方法的合理性。     

基于整数域改进粒子群优化算法的多平台武器目标分配

武器一目标分配( WTA)问题是军事运筹学中经典的NP完全问题,其模型为非线性整数规划模型,包含多种约束条件,求解复杂、收敛速度慢,采用改进粒子群优化( PSO)算法求解WTA问题.在建立WTA最优化分配模型的基础上,提出了一种针对多约束WTA问题的粒子编码方案及模型的适应度函数,解决了粒子的整数域初始化问题.采用粒子...