Intelligent transport route planning using parallel genetic algorithms and MPI in high performance computing cluster

被引：12

作者：

Arunadevi, J. ^{[1
]}

Johnsanjeevkumar, A. ^{[2
]}

Sujatha, N. ^{[3
]}

机构：

[1] Thiagarajar Sch Management, Madurai, Tamil Nadu, India

[2] Thiagarajar Coll Engn, Madurai, Tamil Nadu, India

[3] Madurai Kamaraj Univ, Madurai, Tamil Nadu, India

来源：

ADCOM 2007: PROCEEDINGS OF THE 15TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING AND COMMUNICATIONS | 2007年

关键词：

GIS; SDSS; parallel genetic algorithm; route finding; vehicle routing problem;

D O I：

10.1109/ADCOM.2007.76

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

下载

页码：578 / +

页数：3

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