平曲线超高和加宽施工验算的可视化程序设计

按照公路等级、设计时速、平曲线参数,确定公路超高过渡段的旋转方式以及公路加宽过渡段的计算方式,选择Visual Foxpro 9.0作为开发工具,结合VBA命令,在Microsoft Word平台上进行二次开发,以数据录入模块、平曲线超高及加宽计算模块、结果打印输出模块作为系统的三大功能部分,实现公路平曲线超高和加宽的计算机辅助计算,为公路设计和施工提供方便。     

非对称悬索桥主缆线形计算流程及程序开发

探讨非对称悬索桥缆索线形分析的方法.设计程序化流程图,通过MATLAB软件将悬索桥成桥状态和空缆状态主缆线形程序化,并用普立悬索桥作为算例进行程序正确性验证.计算表明,该方法具有使用方便、计算速度快、精度高等优点,可在设计及施工中应用.     

时程分析法在大蒲春河特大桥主桥抗震验算中的应用

采用时程分析法对大蒲春河特大桥进行抗震分析,对主桥控制部位E1概率和E2概率地震作用下的响应进行验算,并利用验算结果指导该桥的抗震设计.     

暖棚法在高墩0#块冬季施工的应用

该文介绍葫芦河特大桥主墩0#块冬季施工方法,对西北严寒地区混凝土生产、运输、施工、养护等成功的经验进行了总结。提出采用"暖棚保温、管道覆盖、暖棚养护"法进行混凝土施工是一种较好的方法。     

基于VC＋＋实现公路工程试验数据的处理系统

介绍了在公路工程试验室管理中,运用Visual VC＋＋实现公路工程试验室数据处理系统的方法,其中包括数据存储、窗口界面、报表打印等主要功能的构成。叙述了系统总体设计、数据存储、菜单设计、工具栏设计、用户窗口设计及报表打印的步骤和方法。     

信息化条件下的防空武器装备运输线路优化算法

弹药保障,是武器系统战斗力的重要标志。着眼适应未来信息化战争运输保障的特点和要求,应用线性规划和多端网络最大流问题,将运输保障问题抽象为运筹中的线路问题,建立模型,以提高军交运输保障能力。     

A multiobjective chance constrained programming model for supplier selection under uncertainty

Risk management is an inherent part of supplier selection. While companies are enjoying the benefits of outsourcing, risks brought by this practice should be taken into account in the process of decision making. This paper presents a multiobjective stochastic sequential supplier allocation model to help in supplier selection under uncertainty. Demand for products, capacities at suppliers as well as transportation and other variable costs are the main sources of uncertainty and are modeled using probability distributions. Disruptions are exogenous events and the model provides proactive mitigation strategies against disruptions by assigning backup suppliers who can be used in case of a default at a primary supplier. When there is no disruption, the model’s solution is an optimal supplier order assignment, considering operational risks.     

A frequency-based maritime container assignment model

This paper transfers the classic frequency-based transit assignment method of Spiess and Florian to containers demonstrating its promise as the basis for a global maritime container assignment model. In this model, containers are carried by shipping lines operating strings (or port rotations) with given service frequencies. An origin–destination matrix of full containers is assigned to these strings to minimize sailing time plus container dwell time at the origin port and any intermediate transhipment ports. This necessitated two significant model extensions. The first involves the repositioning of empty containers so that a net outflow of full containers from any port is balanced by a net inflow of empty containers, and vice versa. As with full containers, empty containers are repositioned to minimize the sum of sailing and dwell time, with a facility to discount the dwell time of empty containers in recognition of the absence of inventory. The second involves the inclusion of an upper limit to the maximum number of container moves per unit time at any port. The dual variable for this constraint provides a shadow price, or surcharge, for loading or unloading a container at a congested port. Insight into the interpretation of the dual variables is given by proposition and proof. Model behaviour is illustrated by a simple numerical example. The paper concludes by considering the next steps toward realising a container assignment model that can, amongst other things, support the assessment of supply chain vulnerability to maritime disruptions.     

Modeling heterogeneous risk-taking behavior in route choice: A stochastic dominance approach

This paper proposes a unified approach to modeling heterogonous risk-taking behavior in route choice based on the theory of stochastic dominance (SD). Specifically, the first-, second-, and third-order stochastic dominance (FSD, SSD, TSD) are respectively linked to insatiability, risk-aversion and ruin-aversion within the framework of utility maximization. The paths that may be selected by travelers of different risk-taking preferences can be obtained from the corresponding SD-admissible paths, which can be generated using general dynamic programming. This paper also analyzes the relationship between the SD-based approach and other route choice models that consider risk-taking behavior. These route choice models employ a variety of reliability indexes, which often make the problem of finding optimal paths intractable. We show that the optimal paths with respect to these reliability indexes often belong to one of the three SD-admissible path sets. This finding offers not only an interpretation of risk-taking behavior consistent with the SD theory for these route choice models, but also a unified and computationally viable solution approach through SD-admissible path sets, which are usually small and can be generated without having to enumerate all paths. A generic label-correcting algorithm is proposed to generate FSD-, SSD-, and TSD-admissible paths, and numerical experiments are conducted to test the algorithm and to verify the analytical results.     

The price of uncertainty in pavement infrastructure management planning: An integer programming approach

Currently there is a true dichotomy in the pavement maintenance and rehabilitation (M&R) literature. On the one hand, there are integer programming-based models that assume that parameters are deterministically known. On the other extreme, there are stochastic models, with the most popular class being based on the theory of Markov decision processes that are able to account for various sources of uncertainties observed in the real-world. In this paper, we present an integer programming-based alternative to account for these uncertainties. A critical feature of the proposed models is that they provide – a priori – probabilistic guarantees that the prescribed M&R decisions would result in pavement condition scores that are above their critical service levels, using minimal assumptions regarding the sources of uncertainty. By construction of the models, we can easily determine the additional budget requirements when additional sources of uncertainty are considered, starting from a fully deterministic model. We have coined this additional budget requirement the price of uncertainty to distinguish from previous related work where additional budget requirements were studied due to parameter uncertainties in stochastic models. A numerical case study presents valuable insights into the price of uncertainty and shows that it can be large.