DocumentCode :
579037
Title :
Using ACO Metaheuristic for MWT Problem
Author :
Dorzan, M.G. ; Gagliardi, E.O. ; Leguizamon, M.G. ; Penalver, G.H.
Author_Institution :
Fac. de Cienc. Fis. Mat. y Naturales, Univ. Nac. de San Luis, San Luis, Argentina
fYear :
2011
fDate :
9-11 Nov. 2011
Firstpage :
228
Lastpage :
237
Abstract :
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.
Keywords :
ant colony optimisation; computational complexity; computational geometry; deterministic algorithms; set theory; ACO metaheuristic; MWT problem; NP-hard problems; ant colony optimization metaheuristic; computational geometry; deterministic methods; global optimal triangulations; minimum weight triangulation problem; no polynomial algorithm; Algorithm design and analysis; Approximation algorithms; Approximation methods; Computational geometry; Optimization; Probabilistic logic; Runtime; ACO Metaheuristic; Computational Geometry; Minimum Weight; Triangulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science Society (SCCC), 2011 30th International Conference of the Chilean
Conference_Location :
Curico
ISSN :
1522-4902
Print_ISBN :
978-1-4673-1364-3
Type :
conf
DOI :
10.1109/SCCC.2011.30
Filename :
6363402
Link To Document :
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