非线性规划法计算船舶稳性

船舶自由纵倾状态下的稳性曲线计算，最后归结为使消耗在倾斜船舶的功为最小，满足等排水体积约束条件的优化问题。运用非线性规划法中的惩罚函数法作为优化计算方法，与通常采用的拉格朗日乘子法相比，公式推导简洁，而立每一次迭代计算只需计算水线面以下的排水体积及浮心坐标，不需要计算水线面上的面积、漂心、惯性矩等诸要素，减少了计算量，反映了问题的本质。通过对60000吨油船在各种载况下稳性曲线的计算，证明了该方法可行实用。     

面向产品全生命周期工艺知识分类编码系统

在对产品全生命周期工艺知识进行调研的基础上,采用面分类法和线分类法相结合的方式对工艺知识进行了分类,得到工艺知识分类体系,在此基础上对工艺知识进行编码,并开发了相应的计算机辅助分类编码系统,可有效地解决机械制造企业信息化过程中知识的交流与共享问题.     

离散柱型屈曲的优化设计

本文构造的最小质量柱型为五段级、离散型、对称、简支柱型。约束条件为各段级临界压力相等和最小截面满足强度要求。求得各离散截面系数λ,μ的最优相关条件为: -0.53λ~(2/r 2) 0.088λ~(2/r 2)μ~2 2.53μ~(2/r 2) 0.088λ~2μ~(2/r 2)=0 推导过程中运用了非线性规划理论,并以Lagrange法求解。为了便于设计时使用,以表格形式和曲线描述了λ,μ的各种参数。 文末以船用支柱作为实例,其计算结果表明:在相同的临界载荷下,优化柱型可减轻质量36.9％,效果明显,具有推广使用的价值。 这是一种通用柱型,在一切构架中均可采用,尤其适用于大型构件,例如大型船舶中的立柱。     

路用矿质混合料的级配设计及其优化

对于路用矿质混合料级配设计及其优化,可针对设计及其优化的不同要求创建相应的数学模型,处理办法是将设计与优化有机的结合在一起,以设计要求作为约束条件,以优化为目标,设计与优化一并完成.该法可用于各类矿质混合料的级配设计,且其中相关模型的求解亦分别有成熟的计算手段或程序可资利用,非常方便和适用.     

Innovative Public Transport Oriented Policies in Seoul

The objective of this paper is to introduce the innovative transport policies of Seoul that have recently been planned and implemented. In this paper, the various transport policies of Seoul are classified and explained according to two important paradoxes that are highlighted by Downs and Thomson, and Edgeworth. These paradoxes describe how to break the vicious circle of car and public transport use by restraining car use and encouraging the use of public transport, and thus indicate how traffic congestion problems might be solved.     

显微图象处理系统的软件设计

介绍显微图像处理系统软件设计中所涉及的相关概念和实现方法,主要对图像与数据库的关联技术进行了探讨,通过一显微图像处理系统开发的实例,叙述了面向对象的程序设计技术。     

基于可视化客车调度管理信息系统的设计与实现

为实现客车调度管理的科学化和信息化,在规范和统一客车技术管理的相关数据资源,建立铁路客车技术信息库的基础上,本系统以电子动态编组板为基本界面,将调度室与各个车间的业务有机联系起来,在提供便捷的动态鳊组工具的同时,实现相关信息资源的综合运用和共享,有效提高信息查询、分析处理的效率和准确性.     

Time control point strategy coupled with transfer coordination in bus schedule design

A schedule consisting of an appropriate arrival time at each time control point can ensure reliable transport services. This paper develops a novel time control point strategy coupled with transfer coordination for solving a multi‐objective schedule design problem to improve schedule adherence and reduce intermodal transfer disutility. The problem is formulated using a robust mixed‐integer nonlinear programming model. The mixed‐integer nonlinear programming model is equivalently transformed into a robust mixed‐integer linear programming model, which is then approximated by a deterministic mixed‐integer linear programming model through Monte Carlo simulation. Thus, the optimal scheduled arrival time at each time control point can be precisely obtained using cplex . Numerical experiments based on three bus lines and the mass rapid transit system in Singapore are presented, and the results show that the schedule determined using the developed model is able to provide not only reliable bus service but also a smooth transfer experience for passengers. Copyright © 2016 John Wiley & Sons, Ltd.     

Container liner fleet deployment: A systematic overview

Container liner fleet deployment (CLFD) is the assignment of containerships to port rotations (ship routes) for efficient transport of containers. As liner shipping services have fixed schedules, the ship-related operating cost is determined at the CLFD stage. This paper provides a critical review of existing mathematical models developed for the CLFD problems. It first gives a systematic overview of the fundamental assumptions used by the existing CLFD models. The operating characteristics dealt with in existing studies are then examined, including container transshipment and routing, uncertain demand, empty container repositioning, ship sailing speed optimization and ship repositioning. Finally, this paper points out four important future research opportunities: fleet deployment considering ship surveys and inspections, service dependent demand, pollutant emissions, and CLFD for shipping alliances.     

Recursive expected conditional value at risk in the fleet renewal problem with alternative fuel vehicles

We study the fleet portfolio management problem faced by a firm deciding which alternative fuel vehicles (AFVs) to choose for its fleet to minimise the weighted average of cost and risk, in a stochastic multi-period setting. We consider different types of technology and vehicles with heterogeneous capabilities. We propose a new time consistent recursive risk measure, the Recursive Expected Conditional Value at Risk (RECVaR), which we prove to be coherent. We then solve the problem for a large UK based company, reporting how the optimal policies are affected by risk aversion and by the clustering for each type of vehicle.