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                                       Details van artikel 66 van 160 gevonden artikelen
 
 
  Developing a Genetic Algorithm to Solve Shortest Path Problem on a Raster Data Model
 
 
Titel: Developing a Genetic Algorithm to Solve Shortest Path Problem on a Raster Data Model
Auteur: S. Behzadi
Ali A. Alesheikh
E. Poorazizi
Verschenen in: Journal of applied sciences
Paginering: Jaargang 8 (2008) nr. 18 pagina's 3289-3293
Jaar: 2008
Inhoud: 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.
Uitgever: Asian Network for Scientific Information, Pakistan (provided by DOAJ)
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

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