城市居民出行调查数据处理系统设计

城市居民出行调查所得到的交通数据非常庞大，必须通过计算机来进行快速处理和存储。探讨了利用Visual Basic程序设计语言和Access数据库建立城市居民出行调查数据处理系统的软件设计，主要针对系统各大模块关键技术问题，探讨了各模块功能的实现。     

环境承载力约束条件下城市最大乘用车保有量预测

以城市环境承载力为约束条件预测城市内可容纳的最大乘用车保有量。预测模型是一个双层优化问题，其中上层是环境承载力约束下的最大乘用车保有量模型，以交通小区的乘用车保有量之和最大为目标函数，以各路段的环境承载力为约束条件；下层是道路网上的用户平衡分配模型，模拟乘用车出行者的路径选择行为，预测交通需求在道路网上的分布及行驶特征。开发了一个基于灵敏度分析的算法用于实现上下层模型间的反馈及同时求解两个优化问题。利用实例验证了模型及算法的有效性。     

长江干流交通管理系统的研究

长江是我国东西交通的大动脉,随着经济建设的发展,水上运输日趋繁忙,为了保证水上交通安全,提高船舶运输效率,防止环境污染,在长江水域建立船舶交通管理系统是当务之急。本文首先分析了长江干流水域特点,根据最优化原则提出长江干流建立船舶交通管理系统的方案,特别是应用模糊综合数学模型和德尔菲(Delphin)专家咨询方法对10个重点航段交通管理系统的需要程度作了排序,使交通管理系统规划设计的科学性、定量化提高到新的高度。     

从查询式到事件驱动的软件接口开发技术

通过对一款电话语音卡软件接口的分析，利用windows操作系统中对多线程程序设计提供的相关支持，提供了在查询式软件接口上开发基于事件驱动模型的软件接口的方法。采用提供的方法可以使用户的应用软件的设计变得较为简单。     

单线铁路平行运行图区间通过能力的整数规划法

本文通过分析，建立了单线铁路成对非追踪平行运行图区间通过能力的整数规划模型，分析了模型的基本性质，提出了模型的解法。     

基于遗传规划的发动机燃烧系统故障诊断

探讨了利用遗传规划自动生成有效诊断特征参数的方法 ,弥补了故障诊断知识的不足 ,从而使该系统具有自学习能力 ,提高了诊断的效率和精度。     

技术直达列车编组计划的阶跃函数模型及同构变换

本文构造了技术直达列车编组计划（ＴＦＰ）问题的阶跃函数模型。通过对该模型做同构变换，获得了该问题的几种典型优化模型形式：线性０－１规划模型，目标函数为线性而约束条件是二次的０－１规划模型。从而为引进各种特定的算法提供了条件。文末以五个支点站为例给出了各种模型的具体形式。     

连续消耗应急物资调运问题研究

以多出救点、单应急点的连续消耗应急物资调运问题为研究对象,考虑应急物资调运具有时间效率重于经济效益的特点,以及应急系统的整体可靠性及费用,以物资参与救援开始时间最早为第一目标,以出救点数目最少为第二目标,建立了相应的多目标优化决策模型。在满足物资参与救援开始时间最早的基础上,给出了出救点数目优化过程的3个判断条件,并设计了简单的求解算法,最后通过算例验证了模型及算法的有效性。     

A network enhancement model with integrated lane reorganization and traffic control strategies

Lane reorganization strategies such as lane reversal, one‐way street, turning restriction, and cross elimination have demonstrated their effectiveness in enhancing transportation network capacity. However, how to select the most appropriate combination of those strategies in a network remains challenging to transportation professionals considering the complex interactions among those strategies and their impacts on conventional traffic control components. This article contributes to developing a mathematical model for a traffic equilibrium network, in which optimization of lane reorganization and traffic control strategies are integrated in a unified framework. The model features a bi‐level structure with the upper‐level model describing the decision of the transportation authorities for maximizing the network capacity. A variational inequality (VI) formulation of the user equilibrium (UE) behavior in choosing routes in response to various strategies is developed in the lower level. A genetic algorithm (GA) based heuristic is used to yield meta‐optimal solutions to the model. Results from extensive numerical analyses reveal the promising property of the proposed model in enhancing network capacity and reducing congestion. Copyright © 2016 John Wiley & Sons, Ltd.     

Strategic evacuation planning with pedestrian guidance and bus routing: a mixed integer programming model and heuristic solution

This paper presents a mathematical model to plan emergencies in a densely populated urban zone where a certain numbers of pedestrians depend on transit for evacuation. The proposed model features an integrated operational framework, which simultaneously guides evacuees through urban streets and crosswalks (referred to as “the pedestrian network”) to designated pickup points (e.g., bus stops), and routes a fleet of buses at different depots to those pick‐up points and transports evacuees to their destinations or safe places. In this level, the buses are routed through the so‐called “vehicular network.” An integrated mixed integer linear program that can effectively take into account the interactions between the aforementioned two networks is formulated to find the maximal evacuation efficiency in two networks. Because the large instances of the proposed model are mathematically difficult to solve to optimality, a two‐stage heuristic is developed to solve larger instances of the model. Results from hundreds of numerical examples analysis indicate that proposed heuristic works well in providing (near) optimal or feasibly good solutions for medium‐scale to large‐scale instances that may arise in real transit‐based evacuation situations in a much shorter amount of computational time compared with cplex (can find optimal/feasible solutions for only five instances within 3 hours of running). Copyright © 2016 John Wiley & Sons, Ltd.