Intelligent Transport Route Planning Using Parallel Genetic Algorithms and MPI In High Performance Computing Cluster

15th International Conference on Advanced Computing and Communications (ADCOM 2007) Pub Date : 2007-12-18 DOI:10.1109/ADCOM.2007.81

J. Arunadevi, A. Johnsanjeevkumar, N. Sujatha

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引用次数: 21

Abstract

Network analysis in geospatial information system (GIS) provides strong decision support for users in searching optimal route, finding the nearest facility and determining the service area. Searching optimal path is an important advanced analysis function in GIS. In present GIS route finding modules, heuristic algorithms have been used to carry out its search strategy. Due to the lack of global sampling in the feasible solution space, these algorithms have considerable possibility of being trapped into local optima. This paper addresses the problem of selecting route to a given destination on an actual map under a static environment. The proposed solution uses a parallel genetic algorithm (PGA) implemented using High performance Cluster(HPC). A part of an arterial road is regarded as a virus. We generate a population of viruses in addition to a population of routes. A customized method based on a genetic algorithm has been proposed in this paper. Keywords: GIS, SDSS, Parallel Genetic Algorithm, Route Finding, Vehicle Routing Problem.

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基于并行遗传算法和MPI的高性能计算集群智能交通路径规划

地理空间信息系统(GIS)中的网络分析为用户寻找最优路线、寻找最近的设施和确定服务区提供了强有力的决策支持。最优路径搜索是地理信息系统中一项重要的高级分析功能。在现有的GIS寻路模块中，多采用启发式算法来实现寻路策略。由于在可行解空间中缺乏全局采样，这些算法有很大的可能陷入局部最优。本文研究了静态环境下实际地图上到达给定目的地的路线选择问题。该方案采用高性能集群(HPC)实现的并行遗传算法(PGA)。主干道的一部分被视为病毒。我们产生了一群病毒，除了一群路线。本文提出了一种基于遗传算法的自定义方法。关键词:GIS, SDSS，并行遗传算法，寻路，车辆路径问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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15th International Conference on Advanced Computing and Communications (ADCOM 2007)

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