首页> 外文OA文献 >DEVELOPMENT AND IMPLEMENTATION OF THE MULTI-RESOLUTION AND LOADING OF TRANSPORTATION ACTIVITIES (MALTA) SIMULATION BASED DYNAMIC TRAFFIC ASSIGNMENT SYSTEM, RECURSIVE ON-LINE LOAD BALANCE FRAMEWORK (ROLB)
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DEVELOPMENT AND IMPLEMENTATION OF THE MULTI-RESOLUTION AND LOADING OF TRANSPORTATION ACTIVITIES (MALTA) SIMULATION BASED DYNAMIC TRAFFIC ASSIGNMENT SYSTEM, RECURSIVE ON-LINE LOAD BALANCE FRAMEWORK (ROLB)

机译:基于运输活动(MALTA)仿真的动态交通分配系统,递归在线负载平衡框架(ROLB)的多分辨率和负载的开发与实现

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摘要

The Multi-resolution Assignment and Loading of Transport Activities (MALTA) system is a simulation-based Dynamic Traffic Assignment model that exploits the advantages of multi-processor computing via the use of the Message Passing Interface (MPI) protocol. Spatially partitioned transportation networks are utilized to estimate travel time via alternate routes on mega-scale network models, while the concurrently run shortest path and assignment procedures evaluate traffic conditions and re-assign traffic in order to achieve traffic assignment goals such as User Optimal and/or System Optimal conditions.Performance gain is obtained via the spatial partitioning architecture that allows the simulation domains to distribute the work load based on a specially designed Recursive On-line Load Balance model (ROLB). The ROLB development describes how the transportation network is transformed into an ordered node network which serves as the basis for a minimum cost heuristic, solved using the shortest path, which solves a multi-objective NP Hard binary optimization problem. The approach to this problem contains a least-squares formulation that attempts to balance the computational load of each of the mSim domains as well as to minimize the inter-domain communication requirements. The model is developed from its formal formulation to the heuristic utilized to quickly solve the problem. As a component of the balancing model, a load forecasting technique is used, Fast Sim, to determine what the link loading of the future network in order to estimate average future link speeds enabling a good solution for the ROLB method.The runtime performance of the MALTA model is described in detail. It is shown how a 94% reduction in runtime was achieved with the Maricopa Association of Governments (MAG) network with the use of 33 CPUs. The runtime was reduced from over 60 minutes of runtime on one machine to less than 5 minutes on the 33 CPUs. The results also showed how the individual runtimes on each of the simulation domains could vary drastically with naïve partitioning methods as opposed to the balanced run-time using the ROLB method; confirming the need to have a load balancing technique for MALTA.
机译:运输活动的多分辨率分配和加载(MALTA)系统是基于仿真的动态交通分配模型,该模型通过使用消息传递接口(MPI)协议来利用多处理器计算的优势。利用空间划分的运输网络来估计通过大型网络模型上的备用路线的行驶时间,而同时运行的最短路径和分配过程会评估交通状况并重新分配交通,以实现诸如“用户最优”和/或系统最佳条件。性能增益是通过空间划分架构获得的,该架构允许仿真域基于专门设计的递归在线负载平衡模型(ROLB)来分配工作负载。 ROLB的发展描述了如何将运输网络转换为有序节点网络,该网络用作最小成本启发式算法的基础,并使用最短路径进行求解,从而解决了多目标NP Hard二元优化问题。解决此问题的方法包含最小二乘公式,该公式试图平衡每个mSim域的计算负荷以及最小化域间通信要求。该模型从其形式表述发展为用于快速解决问题的启发式方法。作为平衡模型的组成部分,使用负载预测技术Fast Sim来确定未来网络的链路负载,以便估计未来的平均链路速度,从而为ROLB方法提供了一种很好的解决方案。详细介绍了MALTA模型。该图显示了使用33个CPU的Maricopa政府协会(MAG)网络如何实现94%的运行时间减少。运行时间从一台机器上超过60分钟的运行时间减少到33个CPU上不到5分钟的运行时间。结果还表明,使用简单的分区方法与使用ROLB方法的平衡运行时相比,每个仿真域上的各个运行时如何发生巨大变化。确认需要针对MALTA的负载平衡技术。

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    Villalobos Jorge Alejandro;

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  • 年度 2011
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  • 原文格式 PDF
  • 正文语种 en
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