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.     

A nuclear-armed North Korea without ICBMs: the best achievable objective

This article analyzes the North Korean nuclear crisis from a balance-of-power perspective. It is in the long-term interests of international peace for a secure and independent North Korea to serve as a buffer between US and Chinese ground forces. However, the conventional military advantage of the South Korean-American alliance over North Korea has grown drastically since the end of the Cold War, threatening North Korea’s survival. Since North Korea lacks any reliable ally, nuclear weapons represent its most cost-effective way to restore a balance of power and thus secure itself. Accepting security guarantees in exchange for its nuclear arsenal is rhetorically appealing but not a viable approach. North Korea’s development of intercontinental ballistic missiles (ICBMs), however, has overcompensated for the post-Cold War imbalance, inviting talk in Washington of waging a preventive war. Persuading North Korea to give up its ICBM capability, not its nuclear arsenal, should therefore be the primary objective of US diplomacy.     

Potential impact of recharging plug‐in hybrid electric vehicles on locational marginal prices

Plug‐in hybrid electric vehicles (PHEVs), upon market penetration, will create additional recharging loads to the electric power systems. This article considers different recharging scenarios and uses game theoretic models to study the potential impact of the recharging loads on locational marginal prices (wholesale electricity prices). Computational results from a Pennsylvania‐New Jersey‐Maryland Interconnection case study show that, under the existing recharging infrastructures, even a small magnitude of load increase caused by PHEV recharging could have a significant undesirable impact on locational marginal prices. The impact could be mitigated to a varying extent by the availability of possible future recharging infrastructures, including realtime pricing recharging meters, battery stations, or vehicle‐to‐grid technology.© 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010