大空间建筑防火设计应注意的问题

大空间建筑是近年发展起来的新兴建筑。本文分析了大空间建筑的火灾危险性 ,并就其防火设计提出了对策。     

椭圆型方程曲线网格的快速生成方法

本文在用椭圆型方程的网格生成方法生成曲线网格时,通过比较四种常用的计算格式,得到了收敛速度较快的生成方法。在计算流体力学领域,对于边界形状随时间变化的流动问题的数值计算,及自适应网格的生成等同题,生成网格的收敛速度直接影响流场的计算速度。在上述情况下使用本文的结果,能有效的减少机时,提高计算效率。     

Workload distribution of discrete‐time parallel queues with two servers

We study discrete‐time, parallel queues with two identical servers. Customers arrive randomly at the system and join the queue with the shortest workload that is defined as the total service time required for the server to complete all the customers in the queue. The arrivals are assumed to follow a geometric distribution and the service times are assumed to have a general distribution. It is a no‐jockeying queue. The two‐dimensional state space is truncated into a banded array. The resulting modified queue is studied using the method of probability generating function (pgf) The workload distribution in steady state is obtained in form of pgf. A special case where the service time is a deterministic constant is further investigated. Numerical examples are illustrated. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 440–454, 2000     

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.     

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.     

Estimating the lead-time demand distribution for an autocorrelated demand by the pearson system and a normal approximation

The exact first four moments of lead-time demand L are derived for an AR(1) and a MA(1) demand structures where the arbitrary lead-time distribution is assumed to be independent of the demand structure. These moments then form a basis for the Pearson curve-fitting procedure for estimating the distribution of L. A normal approximation to L, a version of the central limit theorem, is obtained under some general conditions. Reorder points (ROPs) of an inventory system are then estimated based on the Pearson system and a normal approximation. Their performances are evaluated. Numerical investigation shows that the Pearson system performs extremely well. The normal approximation, however, is good only for some limited cases, and is sensitive to the choice of the lead-time distribution. A possible improvement is noted.     

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.     

基于AOS包业务模型的最优帧长与吞吐量性能

分析了影响AOS包业务吞吐量性能的因素及帧长度对系统吞吐量性能的影响,建立了包复用效率及差错信道下吞吐量的数学模型,通过仿真验证数学模型的可靠性。并进一步得出差错信道下使系统吞吐量性能最大的最优帧长度配置。研究结果为以吞吐量性能为指标,通过信道状态自适应调节帧长来优化AOS协议提供了理论依据。