Using ACO metaheuristic for MWT problem

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. This paper shows how the Ant Colony Optimization (ACO) metaheuristic can be used to find high quality triangulations. For the experimental study we have created a set of instances for MWT problem since no reference to benchmarks for these problems were found in the literature. Through the experimental evaluation, we assess the applicability of the ACO metaheuristic for MWT problem

Approximations on minimum weight pseudo-triangulations using ant colony optimization metaheuristic

Globally optimal pseudo-triangulations are di cult 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 Pseudo-Triangulation (MWPT) problem of a given set of n points in the plane. This paper shows how the Ant Colony Optimization (ACO) metaheuristic can be used to nd optimal pseudo-triangulations of minimum weight. For the experimental study presented here we have created a set of instances for MWPT since no reference to benchmarks for these problems were found in the literature. We assess through the experimental evaluation the applicability of the ACO metaheuristic for MWPT.Presentado en el X Workshop Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Approximations on minimum weight pseudo-triangulations using ant colony optimization metaheuristic

Globally optimal pseudo-triangulations are di cult 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 Pseudo-Triangulation (MWPT) problem of a given set of n points in the plane. This paper shows how the Ant Colony Optimization (ACO) metaheuristic can be used to nd optimal pseudo-triangulations of minimum weight. For the experimental study presented here we have created a set of instances for MWPT since no reference to benchmarks for these problems were found in the literature. We assess through the experimental evaluation the applicability of the ACO metaheuristic for MWPT.Presentado en el X Workshop Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

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 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.Facultad de Informátic

Metaheuristic approaches for MWT and MWPT problems

It is known that the Minimum Weight Triangulation problem is NP-hard. Also the complexity of Minimum Weight Pseudo-Triangulation problem is unknown, suspecting that it is also a NP-hard problem. Therefore we focused on the development of approximate algorithms to find high quality triangulations and pseudo-triangulations of minimum weight. In this work we propose the use of two metaheuristics to solve these problems: Ant Colony Optimization (ACO) and Simulated Annealing (SA). For the experimental study we have created a set of instances for MWT and MWPT problems since no reference to benchmarks for these problems were found in the literature. Through the experimental evaluation, we assess the applicability of the ACO and SA metaheuristics for MWT and MWPT problems. These results are compared with those obtained from the application of deterministic algorithms for the same problems (Delaunay Triangulation for MWT and a Greedy algorithm respectively for MWT and MWPT).Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Geometría computacional y bases de datos

La línea de investigación “Geometría Computacional y Bases de Datos” enmarcada en el proyecto “Tecnologías Avanzadas de Bases de Datos” vincula el estudio de las disciplinas Bases de Datos, Geometría Computacional y Metaheurísticas, utilizando los métodos y las herramientas provistas para la resolución de problemas orientados a optimización.Eje: Bases de Datos y Minería de DatosRed de Universidades con Carreras en Informática (RedUNCI

Geometría computacional y bases de datos

La línea de investigación Geometría Computacional y Bases de Datos del proyecto Tecnologías Avanzadas de Bases de Datos, vincula el estudio de las disciplinas Bases de Datos, Geometría Computacional y Metaheurísticas, utilizando los métodos y las herramientas provistas para la resolución de problemas orientados a optimización.Eje: Bases de Datos y Minería de DatosRed de Universidades con Carreras en Informática (RedUNCI

Approximations on minimum weight pseudo-triangulations using ant colony optimization metaheuristic

Globally optimal pseudo-triangulations are di cult 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 Pseudo-Triangulation (MWPT) problem of a given set of n points in the plane. This paper shows how the Ant Colony Optimization (ACO) metaheuristic can be used to nd optimal pseudo-triangulations of minimum weight. For the experimental study presented here we have created a set of instances for MWPT since no reference to benchmarks for these problems were found in the literature. We assess through the experimental evaluation the applicability of the ACO metaheuristic for MWPT.Presentado en el X Workshop Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Geometría computacional y bases de datos

El proyecto Tecnologías Avanzadas de Bases de Datos de la Universidad Nacional de San Luis tiene como objetivo principal el estudio de bases de datos avanzadas, en donde se involucra el diseño y desarrollo de herramientas para administrar eficientemente datos no estructurados. La línea de investigación Geometría Computacional y Bases de Datos vincula el estudio de las disciplinas Bases de Datos, Geometría Computacional y Metaheurísticas, utilizando los métodos y las herramientas provistas para la resolución de problemas orientados a optimización.Eje: Base de Datos y Minería de DatosRed de Universidades con Carreras en Informática (RedUNCI

Geometría computacional y bases de datos

El proyecto Tecnologías Avanzadas de Bases de Datos de la Universidad Nacional de San Luis tiene como objetivo principal el estudio de bases de datos avanzadas, en donde se involucra el diseño y desarrollo de herramientas para administrar eficientemente datos no estructurados. La línea de investigación Geometría Computacional y Bases de Datos vincula el estudio de las disciplinas Bases de Datos, Geometría Computacional y Metaheurísticas, utilizando los métodos y las herramientas provistas para la resolución de problemas orientados a optimización.Eje: Base de Datos y Minería de DatosRed de Universidades con Carreras en Informática (RedUNCI