Algoritomos transgenéticos aplicados ao problema da árvore geradora biobjetivo
The Multiobjective Spanning Tree is a NP-hard Combinatorial Optimization problem whose application arises in several areas, especially networks design. In this work, we propose a solution to the biobjective version of the problem through a Transgenetic Algorithm named ATIS-NP. The Computational Tran...
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| Formato: | Dissertação |
| Idioma: | por |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/18019 |
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| Resumo: | The Multiobjective Spanning Tree is a NP-hard Combinatorial Optimization problem whose
application arises in several areas, especially networks design. In this work, we propose a
solution to the biobjective version of the problem through a Transgenetic Algorithm named
ATIS-NP. The Computational Transgenetic is a metaheuristic technique from Evolutionary
Computation whose inspiration relies in the conception of cooperation (and not competition)
as the factor of main influence to evolution. The algorithm outlined is the evolution of a work
that has already yielded two other transgenetic algorithms. In this sense, the algorithms
previously developed are also presented. This research also comprises an experimental
analysis with the aim of obtaining information related to the performance of ATIS-NP when
compared to other approaches. Thus, ATIS-NP is compared to the algorithms previously
implemented and to other transgenetic already presented for the problem under consideration.
The computational experiments also address the comparison to two recent approaches from
literature that present good results, a GRASP and a genetic algorithms. The efficiency of the
method described is evaluated with basis in metrics of solution quality and computational
time spent. Considering the problem is within the context of Multiobjective Optimization,
quality indicators are adopted to infer the criteria of solution quality. Statistical tests evaluate
the significance of results obtained from computational experiments |
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