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Journal of Applied Sciences
  Year: 2008 | Volume: 8 | Issue: 18 | Page No.: 3289-3293
DOI: 10.3923/jas.2008.3289.3293
 
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Developing a Genetic Algorithm to Solve Shortest Path Problem on a Raster Data Model

S. Behzadi, Ali A. Alesheikh and E. Poorazizi

Abstract:
It is mostly believed that raster maps are not practically useful for finding shortest path and generally vector approaches are more prevalent. But any raster approach can open new horizons. Among various approaches, Genetic Algorithm (GA) can contribute effectively in solving lots of problems including shortest path problem in raster maps where other algorithms are inefficient. In this research a novel Genetic Algorithm (GA) will be presented for solving shortest path on a raster map. In a raster map, each road is shown by a specific color. A few pre-processes are performed on raster map based on the color attributes then all parameters of Genetic Algorithm will be defined. In order to evaluate the proposed algorithm, a raster map as an urban road map is selected. In the case study, the algorithm was successful in determining the shortest path.
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How to cite this article:

S. Behzadi, Ali A. Alesheikh and E. Poorazizi, 2008. Developing a Genetic Algorithm to Solve Shortest Path Problem on a Raster Data Model. Journal of Applied Sciences, 8: 3289-3293.

DOI: 10.3923/jas.2008.3289.3293

URL: https://scialert.net/abstract/?doi=jas.2008.3289.3293

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