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| Autore principale: | |
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| Natura: | Artículo científico |
| Lingua: | en |
| Pubblicazione: |
Universidad Nacional de La Plata
2016
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| Soggetti: | |
| Accesso online: | https://www.redalyc.org/articulo.oa?id=638067262007 |
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Sommario:
- A Many-objective Ant Colony Optimizationapplied to the Traveling Salesman Problem Francisco Riveros Néstor Benítez Julio Paciello Benjamín Barán Computación Many NSGA2 Hypervolume objective optimization Ant Colony Optimization Evolutionary algorithms present performancedrawbacks when applied to Many-objective Op-timization Problems (MaOPs). In this work, anovel approach based on Ant Colony Optimiza-tion theory (ACO), denominated ACOλbase-palgorithm, is proposed in order to handle Many-objective instances of the well-known TravelingSalesman Problem (TSP). The proposed algorithmwas applied to several Many-objective TSP ins-tances, verifying the quality of the experimentalresults using the Hypervolume metric. A compa-rison with other state-of-the-art Multi ObjectiveACO algorithms as MAS, M3AS and MOACS aswell as NSGA2 evolutionary algorithm was made,verifying that the best experimental results wereobtained when the proposed algorithm was used,proving a good applicability to MaOPs. 2016 artículo científico 1666-6046 https://www.redalyc.org/articulo.oa?id=638067262007 en http://www.redalyc.org/revista.oa?id=6380 Journal of Computer Science and Technology application/pdf Universidad Nacional de La Plata Journal of Computer Science and Technology (Argentina) Num.02 Vol.16