信息化建设相对滞后的企业如何开展CALS工作

CALS工作与企业信息化紧密联系。本文分析了信息化相对落后企业的现状及原因,对企业如何开展CALS工作提出了具体做法,并就应重点处理的问题进行了阐述。     

军用方舱的舒适性设计

文章主要论述了军用方舱在舒适性方面的设计,内容主要包括舱内噪声的控制、舱内的通风设计、照明设计、色彩与内饰设计以及人机系统的设计。通过舒适性设计,可以为舱内工作人员创造、提供一个舒适、愉快、高效的工作、生活环境。     

临近空间飞行器应用前景及发展分析

文章以临近空间飞行器的应用前景及发展趋势为背景,综合近来国外的研究发展状况,介绍了临近空间飞行器的优势、军事应用,美国对临近空间飞行器的理解及发展目标和技术途径,并结合临近空间飞行器的发展趋势和我国的发展提出了建议。     

基于装备质量的蝴蝶效应

在装备质量问题分析中,应考虑蝴蝶效应,特别要重视那些看上去,好象毫无相关的、微不足道的变化,也许它就是造成装备质量问题的主要原因;在装备科研、生产质量的管理和控制上应注重蝴蝶效应,发现并解决那些已经有苗头而处在可控制阶段的偏差是十分重要的。     

Clustered coverage orienteering problem of unmanned surface vehicles for water sampling

This study investigates a clustered coverage orienteering problem (CCOP), which is a generalization of the classical orienteering problem. The problem is widely motivated by the emerging unmanned techniques (eg, unmanned surface vehicles and drones) applied to environmental monitoring. Specifically, the unmanned surface vehicles (USVs) are used to monitor reservoir water quality by collecting samples. In the CCOP, the water sampling sites (ie, the nodes) are grouped into clusters, and a minimum number of nodes must be visited in each cluster. With each node representing a certain coverage area of the water, the objective of the CCOP is to monitor as much as possible the total coverage area in one tour of the USV, considering that overlapping areas provide no additional information. An integer programming model is first formulated through a linearization procedure that captures the overlapping feature. A two-stage exact algorithm is proposed to obtain an optimal solution to the problem. The efficiency and effectiveness of the two-stage exact algorithm are demonstrated through experiments on randomly generated instances. The algorithm can effectively solve instances with up to 60 sampling sites.     

Optimal production ramp-up in the smartphone manufacturing industry

Motivated by challenges in the smartphone manufacturing industry, we develop a dynamic production ramp-up model that can be applied to economically satisfy nonstationary demand for short-life-cycle products by high-tech companies. Due to shorter life cycles and more rapid evolution of smartphones, production ramp-up has been increasingly critical to the success of a new smartphone. In the production ramp-up, the key challenge is to match the increasing capacity to nonstationary demand. The high-tech smartphone manufacturers are urged to jointly consider the effect of increasing capacity and decreasing demand. We study the production planning problem using a high-dimensional Markov decision process (MDP) model to characterize the production ramp-up. To address the curse of dimensionality, we refine Monte Carlo tree search (MCTS) algorithm and theoretically analyze its convergence and computational complexity. In a real case study, we find that the MDP model achieves revenue improvement by stopping producing the existing product earlier than the benchmark policy. In synthetic instances, we validate that the proposed MCTS algorithm saves computation time without loss of solution quality compared with traditional value iteration algorithm. As part of the Lenovo production solution, our MDP model enables high-tech smartphone manufacturers to better plan the production ramp-up.     

Revenue maximization in two-station tandem queueing systems

We study optimal pricing for tandem queueing systems with finite buffers. The service provider dynamically quotes prices to incoming price sensitive customers to maximize the long-run average revenue. We present a Markov decision process model for the optimization problem. For systems with two stations, general-sized buffers, and two or more prices, we describe the structure of the optimal dynamic pricing policy and develop tailored policy iteration algorithms to find an optimal pricing policy. For systems with two stations but no intermediate buffer, we characterize conditions under which quoting either a high or a low price to all customers is optimal and provide an easy-to-implement algorithm to solve the problem. Numerical experiments are conducted to compare the developed algorithms with the regular policy iteration algorithm. The work also discusses possible extensions of the obtained results to both three-station systems and two-station systems with price and congestion sensitive customers using numerical analysis.     

Mathematical formulation and heuristic algorithm for the block relocation and loading problem

This study considers the block relocation and loading problem in container terminals. The optimal loading sequence and relocation location are simultaneously decided on the basis of the desired ship‐bay and initial yard space configuration. An integer linear programming model is developed to minimize the number of relocations in the yard space on the basis of no shifts in the ship bay. The accuracy of the model is tested on small‐scale scenarios by using CPLEX. Considering the problem size in the real world, we present a rule‐based heuristic method that is combined with a mathematical model for the removal, loading, and relocation operations. The influence of rules on algorithm performance is also analyzed, and the heuristic algorithm is compared with different types of algorithms in the literature. The extensive numerical experiments show the efficiency of the proposed heuristic algorithm.     

超宽带雷达的欺骗式干扰技术研究

根据超宽带雷达的工作方式和成像特点,提出基于DRFM与DDS技术对超宽带雷达实施假目标干扰的方法.通过分析超宽带雷达距离维成像的基本原理,提出利用DDS技术对转发信号实施移频调制,并根据需要产生不同特征的假目标干扰.在理论分析的基础上进行了仿真实验,仿真结果证明了这种方法的可行性.该方法可对一维和二维雷达成像进行干扰.     

Evaluating the effects of machine breakdowns in stochastic scheduling problems

In most of the stochastic resource-allocation problems discussed in the literature it is supposed that the key resource, herein called the machine, is continuously available until all tasks are completed. Plainly, this will often be an unrealistic assumption. This paper supposes that intermittent availability of the machine is due to a breakdown proces, and describes various approaches to the evaluation of the effect of breakdowns. Firstly, for the case of geometric up times, conditions are given under which breakdowns have no effect on optimal allocation strategies. Secondly, two different procedures are given which yield an upper bound on the loss incurred when a processing strategy is adopted under the assumption of no breakdowns, when in fact breakdowns do occur. The first of these is based on Gittins's indices and is described for the case of geometric up times, and the second uses a bounding argument on the breakdown process.