分段线性变参数控制在数字式自动找平控制系统中的应用

为了验证分段线性变参数控制在自动找平控制系统中的应用前景,对自动找平控制系统的结构、控制方式进行了介绍;分析了分段线性控制方式的工作原理及特点,在实验室建立了沥青混凝土摊铺机数字式自动找平控制系统试验台,设计了3套试验方案,即普通电磁阀方案、高速开关阀方案和分段线性控制方案;对这3种控制方案进行了试验比较,得出了在阶跃干扰作用下,3种控制方案的响应速度及产生超调时的超调量。结果表明:分段线性控制方案具有较快的响应速度,但在系统产生超调时,其超调量相对较大。     

基于航速调整的班轮燃油补给优化

燃油成本在班轮运营总成本中占有很大比重,燃油补给是影响航运公司班轮运营成本和效益的一项重要决策.基于航速调整策略,以班轮运营总成本最小化为目标,建立燃油补给混合整数非线性规划模型,运用分段线性逼近法对燃油消耗函数进行线性化处理,并设计了求解算法步骤.实例分析验证了模型和求解方法的有效性.结果表明,在航运市场需求低迷的情况下,船舶更适宜采取较低的航速,采取灵活的加油港策略或放宽船舶到港时间窗限制,能更为有效地降低燃油成本.     

囊式空气弹簧机械阻抗特性研究

根据小幅振动的线性叠加原理将囊式空气弹簧分成几个简单的可解析计算的规则区域,结合线性空气波动理论求解出空气弹簧内部声压场的分布。根据弹性薄壳无矩理论推导出旋转壳体状态向量的一阶常微分矩阵方程,利用齐次扩容精细积分法推导出壳体的传递矩阵,结合动力平衡方程求出空气弹簧在位移谐波激励下所受到的激励力,进而得出其机械阻抗。算例结果表明该方法合理可行,为运用近似解析法分析空气弹簧的阻抗特性提供了一种新的思路。     

Liner shipping network design with emission control areas: A genetic algorithm-based approach

To curb emissions, containerized shipping lines face the traditional trade-off between cost and emissions (CO₂ and SO_x) reduction. This paper considers this element in the context of liner service design and proposes a mixed integer linear programming (MILP) model based on a multi-commodity pickup and delivery arc-flow formulation. The objective is to maximize the profit by selecting the ports to be visited, the sequence of port visit, the cargo flows between ports, as well as the number/operating speeds of vessels on each arc of the selected route. The problem also considers that Emission Control Areas (ECAs) exist in the liner network and accounts for the vessel carrying capacity. In addition to using the MILP solver of CPLEX, we develop in the paper a specific genetic algorithm (GA) based heuristic and show that it gives the possibility to reach an optimal solution when solving large size instances.     

基于粒子群算法的水下多元线阵阵形有源校正方法

针对存在阵元位置误差的水下多元线阵,提出一种基于粒子群优化算法的远场有源阵形校正方法.该方法选用2个辅助源分时工作方式,利用无条件最大似然方位估计算法构建目标函数,并通过粒子群算法对阵元位置进行寻优.利用该方法对均匀线阵进行性能仿真实验.结果表明:该方法稳健性好、校正精度高,具有一定的应用前景.     

Dynamic traffic metering in urban street networks: Formulation and solution algorithm

Traffic metering offers great potential to reduce congestion and enhance network performance in oversaturated urban street networks. This paper presents an optimization program for dynamic traffic metering in urban street networks based on the Cell Transmission Model (CTM). We have formulated the problem as a Mixed-Integer Linear Program (MILP) capable of metering traffic at network gates with given signal timing parameters at signalized intersections. Due to the complexities of the MILP model, we have developed a novel and efficient solution approach that solves the problem by converting the MILP to a linear program and several CTM simulation runs. The solution algorithm is applied to two case studies under different conditions. The proposed solution technique finds solutions that have a maximum gap of 1% of the true optimal solution and guarantee the maximum throughput by keeping some vehicles at network gates and only allowing enough vehicles to enter the network to prevent gridlocks. This is confirmed by comparing the case studies with and without traffic metering. The results in an adapted real-world case study network show that traffic metering can increase network throughput by 4.9–38.9% and enhance network performance.     

The generators of paratransit trips by persons with disabilities

Identifying the generators of paratransit trips by persons with disabilities is important to comprehend the current demand patterns and forecast future demand. Only a handful of studies have been conducted so far to identify the generators of paratransit trips and most focused on the home end of the trips. Given some of the inconsistencies in past studies and the scarcity of studies on the generators of trips away from home, this study attempts to identify the generators of paratransit trips beginning and ending at clients’ homes and away from home. It uses an extremely large dataset consisting of 1.91 million trips made by NJ TRANSIT’s Access Link clients, socioeconomic data from the American Community Survey, employment data from the Longitudinal Employer-Household Dynamics, and establishment data from Dun and Bradstreet. The analytical methods include an ordinary least squares model (OLS) and several spatial generalized linear mixed models (GLMM) to identify the characteristics of census block groups associated with Access Link trip generation at home and away from home, Geographic Information System (GIS) analysis to identify the types of establishments located in the immediate vicinity of drop-offs, and a multinomial logit model (MNL) to examine the relationship between the characteristics of the establishments in the vicinity of drop-offs and the characteristics of the dropped-off clients. Together, the various analyses provide useful insights about paratransit trip generators at the macro and micro levels. Some implications of the findings are discussed.     

Power network parameter estimation method based on data mining technology

The parameter values which actually change with the circumstances, weather and load level etc.produce great effect to the result of state estimation. A new parameter estimation method based on data mining technology was proposed. The clustering method was used to classify the historical data in supervisory control and data acquisition (SCADA) database as several types. The data processing technology was impliedto treat the isolated point, missing data and yawp data in samples for classified groups. The measurement data which belong to each classification were introduced to the linear regression equation in order to gain the regression coefficient and actual parameters by the least square method. A practical system demonstrates the high correctness, reliability and strong practicability of the proposed method.     

一种水下非均质拖曳线列阵动力学仿真方法及试验验证

基于Ablow和Schechter经典差分方法,分析水下非均质拖曳线列阵的受力特性,建立其空间运动控制方程.采用中心差分法和牛顿迭代法对运动控制方程进行离散及时间和空间上的迭代求解,获得水下非均质拖曳线列阵的动力学特性.在此基础上,结合非均质线列阵实尺度模型,设计并开展湖中的实航拖曳试验,分析比较了试验数据与仿真结果.研究表明,本文提出的数学仿真方法有效可靠,可为水下非均质拖曳线列阵动力学特性分析提供一种有效的技术手段.     

Improving maritime inventory routing: application to a Brazilian petroleum case

The crude oil offloading and supply problem (COSP) is a type of operation maritime inventory routing (MIR) problem encountered by petroleum companies. In COSP, the company not only is responsible for the ship scheduling to carry the crude oil from production sites to discharge ports but also must maintain inventory levels at both ports (production and consumption) between safety operational bounds to avoid disruptions in its crude oil production and/or refining processes. We show how to improve significantly the decision-making process in a Brazilian petroleum company using a mixed-integer linear programming (MILP) model to represent COSP. Comparison tests with a current ship-scheduling method adopted in the company indicated that the use of the MILP model increased the transportation efficiency and reduced costs by 20% on average. In addition to the quantitative gains, the use of a MILP model to solve COSP has succeeded when encountering real-life events, such as variation in production or consumption rates, berth unavailability, and changes in the storage capacities at ports.