Solución del problema del agente viajero mediante clústeres y algoritmos genéticos
This paper tries to solve the well know Traveling Salesman Problem using clustering and genetic algorithms, so we divide a set of cities in clusters for minimize the number of cities when the genetic algorithm will be applied. Therefore we propose a new method to do the clusters, so we define K poin...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | México |
| Institución: | UNIVERSIDAD AUTÓNOMA DEL ESTADO DE HIDALGO |
| Repositorio: | PÄDI Boletín Científico de Ciencias Básicas e Ingeniería del ICBI |
| Idioma: | español |
| OAI Identifier: | oai:repository.uaeh.edu.mx:article/485 |
| Acceso en línea: | https://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/485 |
| Access Level: | acceso abierto |
| Palabra clave: | Clusters, centroids, genetic algorithm, heuristic, nodes. Clúster, centroides, algoritmos genéticos, heurísticos, nodos. |
| Sumario: | This paper tries to solve the well know Traveling Salesman Problem using clustering and genetic algorithms, so we divide a set of cities in clusters for minimize the number of cities when the genetic algorithm will be applied. Therefore we propose a new method to do the clusters, so we define K points and call it centroids. This points being clusters and we recalculate centroids so that the distance between cities and its centroids will be minimum until centroids do not change more. Then we applied the genetic algorithms on each cluster to minimize the tour´s length in each cluster. Finally we propose a method to unite all clusters minimizing the tour´s length final. |
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