基于改进免疫遗传机理的动态路径诱导算法研究

针对传统算法存在的不足,提出基于改进的免疫遗传机理的动态路径诱导算法。通过引入单点交叉算子配合控制策略的改进思想,在宏观上控制交叉过程以及构造优化简单的目标函数,较好地弥补了传统遗传算法早熟收敛、陷入局部最优解、运算效率较低等问题。最后采用此算法进行路网实例计算,结果表明该算法能较大程度地提高路网利用率,减少交通拥堵。     

小件快运中的最短运输时间问题

小件快运经过多年的发展,已经成为公路客运一个新的经济增长点,越来越多的公路客运企业和汽车客运站加入到经营小件快运的行列,小件快运也逐渐由单个企业的独立运营发展到多个企业联合的网络化运营。对中转运输中多条运输线路进行分析,得到最短运输时间线路,从而提高运输效率。     

Prioritizing new bicycle facilities to improve low-stress network connectivity

This paper introduces a new method to prioritize bicycle improvement projects based on accessibility to important destinations, such as grocery stores, banks, and restaurants. Central to the method is a new way to classify “bicycling stress” using marginal rates of substitution which are commonly developed through empirical behavioral research on bicyclist route choice. MRS values are input parameters representing bicycling stress associated with the number of lanes and speed limit of a street. The method was programmed as a geographic information system tool and requires commonly available data. The tool is demonstrated on three improvement scenarios that were recently proposed for Seattle, Washington. The full build-out scenario consists of 771 projects that include various new bike lanes, protected bike lanes, and multi-use trails. The tool produces priority rankings based on a project’s ability to improve low-stress connectivity between homes and important destinations. The analysis identifies specific areas and neighborhoods that can be expected to exhibit better bikeability. Transportation planners can use the tool to help communicate anticipated project impacts to decision-makers and the public.     

物流网络优化中路径问题的研究

在深入分析物流系统化和网络化的基础上,对物流网络优化中物流路径问题进行研究,通过分析物流结构模型和数学模型,提出了最短路径和关键路径物流策略的分析方法,给出了具体的计算方法,并举实例加以说明,为解决现代物流结构中存在的系统设计和运作等问题提供了理论依据和技术方法。     

集装箱公铁联运的费用加权最短路计算机算法

结合公铁联运过程中承运、中转和交付的3个环节,借鉴Dijkstra标号算法思路,提出一种多阶段定向搜索的标号算法解决集装箱公铁联运费用最短路问题。该算法考虑路网中铁路线路和公路线路的区别,引入了集装箱办理站选择集的概念,并考虑集装箱办理站的中转费用。给出若干计算实例,编程计算的结果证明该算法具有实际意义和高可靠性。     

基于GA和SVM的水火弯板焰道布置优化方法

水火弯板是目前船舶建造中普遍采用的曲型外板加工方法,由于机理复杂,其加工过程参数确定往往依赖于工人的加工经验,难以实现标准化和规范化。文章提出基于遗传算法(GA)和支持向量机(SVM)的水火弯板焰道布置优化方法,以成形曲面和设计曲面之间的形状误差最小为优化目标,将焰道布置优化问题分解成计算最小形状误差和搜寻最佳匹配位置两个问题,并分别运用嵌套GA和SVM来实现这两个问题的求解。实例验证表明该方法能快速高效确定最优的加热线布置方案。     

Stability of transportation networks under adaptive routing policies

Growing concerns regarding urban congestion, and the recent explosion of mobile devices able to provide real-time information to traffic users have motivated increasing reliance on real-time route guidance for the online management of traffic networks. However, while the theory of traffic equilibria is very well-known, fewer results exist on the stability of such equilibria, especially in the context of adaptive routing policy. In this work, we consider the problem of characterizing the stability properties of traffic equilibria in the context of online adaptive route choice induced by GPS-based decision making. We first extend the recent framework of “Markovian Traffic Equilibria” (MTE), in which users update their route choice at each intersection of the road network based on traffic conditions, to the case of non-equilibrium conditions, while preserving consistency with known existence and uniqueness results on MTE. We then exhibit sufficient conditions on the network topology and the latency functions for those MTEs to be stable in the sense of Lyapunov for a single destination problem. For various more restricted classes of network topologies motivated by the observed properties of travel patterns in the Singapore network, under certain assumptions we prove local exponential stability of the MTE, and derive analytical results on the sensitivity of the characteristic time of convergence to network and traffic parameters. The results proposed in this work are illustrated and validated on synthetic toy problems as well as on the Singapore road network with real demand and traffic data.     

基于混沌蚁群算法的最短路径选择研究

如何解决最短路径选择问题一直是城市交通流诱导系统的关键之一.基于群体仿生理论的蚁群算法是解决此问题的一种方法,针对采用蚁群算法进行最短路径选择时易出现的陷入局部最优解问题,引入混沌理论,采用混沌蚁群算法利用混沌初始化进行改善个体质量和利用混沌扰动避免在蚁群算法搜索过程中陷入局部极值,同时降低了蚁群算法的时间复杂度,从而更好的解决了最短路径选择问题.     

网络最短路径定界搜索算法

用Dijkstra算法求解大规模网络两顶点间最短路径时，需计算大量与最短路径无关的顶点，效率较低，双向定界搜索算法是首先对网络进行双向搜索，得到一条经任意点的最短路径，一般情况下，这条路径已非常接近、甚至等于最短路径。然后，以此路径的标号(即路径长)作为搜索计算的界，进行双向标号计算，对超过界的顶点不再计算，以提高计算效率．算法分析表明，用该算法可使计算效率提高约一倍。     

城市道路网络交通特性仿真模型及最短路径算法

就城市道路网系统宏观仿真中存在的问题进行研究，提出了更符合城市道路网系统实际特性的仿真模型，该模型对城市道路网交通特性空间分布的方向性差异及交叉口延误进行了抽象，并设计了基于该仿真模型的最短路算法。