一种新的异类多传感器系统误差融合估计算法

为解决由测向测时差无源被动传感器与主动传感器组网探测时异类多传感器系统误差估计问题,提出了一种新的异类多传感器系统误差融合估计算法.首先,通过对主被动传感器进行组合并构建异类传感器系统误差量测模型,实现了各组合传感器系统误差的实时估计;其次,通过建立多传感器融合估计结构,对多传感器系统误差的组合估计信息进行融合并反馈,获得了各传感器系统误差的全局融合估计.蒙特卡罗仿真结果表明:该算法能够对组网探测系统中各主、被动传感器的测向测时差及测距系统误差进行有效的融合估计,具有较高的工程应用价值.     

应急救援物流中物资分发点多目标排队选址优化

基于模糊数学、排队理论与选址理论,建立了应急救援物流中物资分发点的多目标模糊排队选址优化模型,其中：受灾点的需求率和物资分发点的服务率为模糊数,物资分发点建立成本最小和救援反应时间最短为目标函数．设计了模型的求解算法,确定了物资分发点的选址以及各个分发点所覆盖的受灾点区域范围．结合具体算例,验证了模型的实用性,并分析了物资分发点应急服务能力对救援效果的影响．     

手机定位数据获取出行OD：现状及展望

手机定位数据可以用于获取交通信息。近年来利用这种数据获取路段速度已经成为研究热点,但在获取OD方面研究较少。通过总结手机定位获取OD方面的研究现状,分析目前研究存在的主要问题,指出未来的研究重点。     

阿德兰启发式算法在CNG加气站选址中的应用

随着CNG加气站建设的蓬勃发展,其规划选址问题也日益突出。以CNG加气站规划选址进程图为框架,分析CNG加气站规划选址的原则及影响因素,并制定合理的评价指标体系。最后,提出用阿德兰启发式算法计算客户加气成本的选址方法。     

公交中途停靠站站台设置问题实证研究

公交停靠站作为重要的城市公交设施,其设置不合理会导致公交站服务水平低,道路通行能力下降等问题.针对目前城市公交停靠站存在的问题,本文从公交站台设置的形式、方法、位置、站台物理条件及停靠线路五个方面入手,基于这五方面对公交站及公交服务水平的影响,归纳公交站台设置改善措施,并结合实例展开关于公交站设置的实际研究.通过对公交...     

码头闸口集装箱箱号自动识别系统设计与开发

码头集装箱的进出车辆登记,传统采用人工记录方式,效率低。为了提高码头的运转效率,重要的是减少车辆的登记时间。笔者设计的集装箱箱号自动识别系统,基于轴线扫描和垂直投影的箱号定位,有效地去除了干扰信息,获取准确的箱号位置;同时采用将灰度投影字符分割法和欧式距离字符识别相结合的方法,提高识别效果;采用摄像头拍摄车辆图像,利用监控计算机对图像进行处理,识别出集装箱箱号,录入数据库,并做决策,控制闸口设备的操作。仿真结果表明:该系统可以实现自动录入进出闸口的集装箱箱号,车辆进出闸口无需停车,提高了码头运转效率,减少了塞车机会,并解决了采用射频(RFID)识别系统成本高、难统一标准的难题。     

驱护舰编队短波通信干扰战术运用

通过分析通信干扰压制区,明确通信干扰阵位,提出干扰时机要求,为海上编队通信对抗的战术使用提供参考。     

Biofuel refinery location and supply chain planning under traffic congestion

This research focuses on planning biofuel refinery locations where the total system cost for refinery investment, feedstock and product transportation and public travel is minimized. Shipment routing of both feedstock and product in the biofuel supply chain and the resulting traffic congestion impact are incorporated into the model to decide optimal locations of biofuel refineries. A Lagrangian relaxation based heuristic algorithm is introduced to obtain near-optimum feasible solutions efficiently. To further improve optimality, a branch-and-bound framework (with linear programming relaxation and Lagrangian relaxation bounding procedures) is developed. Numerical experiments with several testing examples demonstrate that the proposed algorithms solve the problem effectively. An empirical Illinois case study and a series of sensitivity analyses are conducted to show the effects of highway congestion on refinery location design and total system costs.     

Joint inventory-location problem under the risk of probabilistic facility disruptions

This paper studies a reliable joint inventory-location problem that optimizes facility locations, customer allocations, and inventory management decisions when facilities are subject to disruption risks (e.g., due to natural or man-made hazards). When a facility fails, its customers may be reassigned to other operational facilities in order to avoid the high penalty costs associated with losing service. We propose an integer programming model that minimizes the sum of facility construction costs, expected inventory holding costs and expected customer costs under normal and failure scenarios. We develop a Lagrangian relaxation solution framework for this problem, including a polynomial-time exact algorithm for the relaxed nonlinear subproblems. Numerical experiment results show that this proposed model is capable of providing a near-optimum solution within a short computation time. Managerial insights on the optimal facility deployment, inventory control strategies, and the corresponding cost constitutions are drawn.     

A mixed-integer linear program for optimizing sensor locations along freeway corridors

How to optimally allocate limited freeway sensor resources is of great interest to transportation engineers. In this paper, we focus on the optimal allocation of point sensors, such as loop detectors, to minimize performance measurement errors. Although it has been shown that the minimization problem can be intuitively formulated as a nonlinear program, the formulation is so complex that only heuristic approaches can be used to solve the problem. In this paper, we transform the nonlinear program into an equivalent mixed-integer linear model. The linearized model is shown to have a graphical interpretation and can be solved using resource constrained shortest path algorithms. A customized Branch-and-Bound technique is then proposed to solve the resource constrained shortest path problem. Numerical experiments along an urban freeway corridor demonstrate that this sensor location model is successful in allocating loop detectors to improve the accuracy of travel time estimation.