Distributed coordinated in-vehicle online routing using mixed-strategy congestion game

This study proposes a coordinated online in-vehicle routing mechanism for smart vehicles with real-time information exchange and portable computation capabilities. The proposed coordinated routing mechanism incorporates a discrete choice model to account for drivers’ behavior, and is implemented by a simultaneously-updating distributed algorithm. This study shows the existence of an equilibrium coordinated routing decision for the mixed-strategy routing game and the convergence of the distributed algorithm to the equilibrium routing decision, assuming individual smart vehicles are selfish players seeking to minimize their own travel time. Numerical experiments conducted based on Sioux Falls city network indicate that the proposed distributed algorithm converges quickly under different smart vehicle penetrations, thus it possesses a great potential for online applications. Moreover, the proposed coordinated routing mechanism outperforms traditional independent selfish-routing mechanism; it reduces travel time for both overall system and individual vehicles, which represents the core idea of Intelligent Transportation Systems (ITS).     

The Green Ship Routing and Scheduling Problem (GSRSP): A conceptual approach

Recent reviews of the literature on ship routing and scheduling note the increased attention to environmental issues. This is an area of paramount importance for international shipping and will be even more so in the future. This short communication is motivated by the increasing attention to ‘green’ routing and scheduling and outlines some possible ways to incorporate the air emissions dimension into maritime transportation OR. The main contribution of this note vis-a-vis the state of the art is that it conceptualizes the formulation of the ‘Green Ship Routing and Scheduling Problem’ (GSRSP) based on existing formulations and highlights all the important parameters of the problem.     

A real-life Multi Depot Multi Period Vehicle Routing Problem with a Heterogeneous Fleet: Formulation and Adaptive Large Neighborhood Search based Matheuristic

In this paper, a new rich Vehicle Routing Problem that could arise in a real life context is introduced and formalized: the Multi Depot Multi Period Vehicle Routing Problem with a Heterogeneous Fleet. The goal of the problem is to minimize the total delivery cost. A heterogeneous fleet composed of vehicles with different capacity, characteristics (i.e. refrigerated vehicles) and hourly costs is considered. A limit on the maximum route duration is imposed. Unlike what happens in classical multi-depot VRP, not every customer may/will be served by all the vehicles or from all the depots. The planning horizon, as in most real life applications, consists of multiple periods, and the period in which each route is performed is a variable of the problem. The set of periods, within the time horizon, in which the delivery may be carried out is known for each customer. A Mixed Integer Programming (MIP) formulation for MDMPVRPHF is presented in this paper, and an Adaptive Large Neighborhood Search (ALNS) based Matheuristic approach is proposed, in which different destroy operators are defined. Computational results, pertaining to realistic instances, which show the effectiveness of the proposed method, are provided.     

无线传感网络中QoS约束多播路由算法

分析了无线传感网络中具有时延、带宽和剩余能量等多QoS约束的多播路由问题.描述了一种适应于研究QoS多播路由的网络模型.提出了一种具有多QoS约束的能量有效的多播路由算法(EMRA),该算法成功地解决了无线传感网络中多播节点动态变化时的QoS路由选择问题.仿真实验证明了EMRA的有效性和优越性.     

基于水上交通冲突技术的船舶定线制警戒区安全评价*

针对以分道通航制为主的船舶定线制没能解决各主要交通流汇集区域的船舶会遇问题,结合我国船舶定线制发展的特点,分析了交通冲突技术应用于船舶定线制警戒区安全研究的有效性,提出了一种以水上交通冲突技术(VTCT)和灰色聚类为理论依据的船舶定线制警戒区交通安全评价方法。应用该方法,对宁波-舟山港核心港区深水航路船舶定线制的共4个警戒区及1个环形通道的交通安全状况进行评价,评价结果为安全诊断和优化船舶定线制的设计方案等提供了依据。     

基于等价交路组合的乘务值乘计划优化

根据乘务值乘计划的优化性与乘务交路的排列顺序不是一一对应的特性,提出等价交路组合的概念。通过构建接续网络刻画部分交路接续关系,在此基础上,基于等价交路组合设计了求解乘务值乘计划的启发式优化方法。以广深线数据为例,对提出的优化方法进行验证,并分析了不同乘务规则取值对需要的乘务员数量的影响。     

考虑自行车步行影响的交通平衡综合分析模型

步行和自行车等外界因素对机动车流的影响也具有随机性,但是这种影响更多地表现为可预见性和可控制性(尤其从交通管理的角度来看),可以说这种影响将导致可预见性的路段实际通过能力降级,并且可预见性特征使得这种影响不同于随机用户平衡中路段旅行时间的感知误差.笔者通过区分路段通过能力降级因素为内因(路段上车流量增加导致道路服务水平降级)和外因(由与路段上与车流量无关的外部因素,如随意过街人流、自行车流等外部因素,引起的道路通过能力降级),并且区分路段旅行时间为通行能力降级路段上行程时间和排解交通拥堵花费的滞留时间两个构成部分的基础上,建立了考虑自行车步行影响的交通平衡综合分析模型;通过对路段参数敏感性分析和实例对照,既展示了该综合分析模型-路径期望旅行时间平衡分析模型与确定性网络用户平衡分析模型的差异性,又展示了路径期望旅行时间平衡分析模型能较好地再现人们对道路路段通行能力降级情形下的车流路径选择行为.     

带时间窗的甩挂运输路径优化问题研究

针对带时间窗的甩挂运输路径优化问题,考虑整车和卡车2种运输方式,以及整车、卡车、混合3种行驶路径,以行驶时间为目标函数构建模型,设计基于A、B策略的两阶段混合启发式算法.算例分析结果表明：针对客户规模在100以内的小规模算例,均可在3s内求得结果,策略B的求解时间少于策略A,而策略A的目标函数优于策略B;当客户规模逐步增至900时,选择策略A可获得更高的求解效率.可见,本文所构建的模型与算法是可行和有效的,对实际配送过程中的车辆指派与路径优化具有一定的参考价值.     

绿色多式联运随机优化策略

针对速度服从随机分布时绿色多式联运路径特点,探索路径优化策略问题,使用随机优化方法,建立绿色多式联运随机路径优化模型,设计了一种将样本平均近似法和基于优先权的粒子群算法相结合的混合算法求解该模型.结合多式联运实际情况设计数值算例验证模型的有效性,对模型中速度的正态分布与均匀分布和碳排放因子进行较为完整的情景分析,结合实际情况得出当样本规模为600,速度服从均匀分布时,情景3-2运输成本为501.11、碳排放成本为649.07是稳定性较高的理想决策,碳排放因子增为0.8有利于成本的降低.实验结果表明,本文建立的随机优化模型能够较好解决速度服从随机分布时多式联运路径优化问题,为实际多式联运运营提供决策支持.     

基于合同网的IRP问题协商机制研究

针对存贮路径问题，采用多代理系统技术，将问题功能实体抽象成Agent，从而构建了基于多代理系统的体系结构，通过基于合同网的协商机制分析，探讨了补货任务与配送车辆之间智能分配策略，并以实例进行了说明。