路网车流径路选择随机相关机会规划模型及其混合遗传算法

研究随机环境下车流径路的选择问题,首先给出路网车流径路方案可靠性的定义,并在此基础上建立随机环境下车流径路选择问题的随机相关机会多目标规划模型。模型考虑了车流具有不同权重的情况,目标为极大化车流径路方案的可靠性及极小化期望总费用。用C＋＋语言编写K短路算法,并在Visual Studio 6.0上基于该算法开发了软件,用于计算网络上任意两点之间的K短路。以该软件计算出的K短路作为节点间的可选径路集,提出一种基于随机模拟的混合遗传算法。算例表明,在不同交叉和变异概率的条件下算法均可在给定进化代数内收敛至相同的最优解,有较强的适应性。     

动力定位船舶桨-桨干扰处理策略研究

本文针对动力定位船舶在推力分配中桨-桨之间的水动力干扰问题,基于二次规划算法提出了一种改进的避免桨-桨干扰的策略。以一艘海洋平台供应船模型为研究对象,通过仿真验证了该算法可以有效地降低推进器的推力损失,提高船舶的定位精度,降低推进系统的能耗。     

汽车风窗玻璃电动刮水器耐久试验台设计

介绍长城汽车股份有限公司试验中心自制电动刮水器耐久试验台的构成和功能,论述其硬件水循环系统及控制程序的工作原理。     

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.     

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.