Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic
Globally optimal triangulations are difficult to be found by deterministic methods as, for most type of criteria, no polynomial algorithm is known. In this work, we consider the Minimum Weight Triangulation (MWT) problem of a given set of n points in the plane. Our aim is to show how the Ant Colony...
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| Autores principales: | , , , |
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| Formato: | Articulo |
| Lenguaje: | Inglés |
| Publicado: |
2010
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/9668 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Jun10-1.pdf |
| Aporte de: |
| Sumario: | Globally optimal triangulations are difficult to be found by deterministic methods as, for most type of criteria, no polynomial algorithm is known. In this work, we consider the Minimum Weight Triangulation (MWT) problem of a given set of n points in the plane. Our aim is to show how the Ant Colony Optimization (ACO) metaheuristic can be used to search for globally optimal triangulations of minimum weight. We present an experimental study for a set of instances for MWT problem. We create these instances since no reference to benchmarks for this problem were found in the literature. We assess through the experimental evaluation the applicability of the ACO metaheuristic for MWT problem. |
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