Enhanced Self-Organizing Map Solution for the Traveling Salesman Problem

  • Joao P. A. Dantas FAB
  • Andre N. Costa FAB
  • Marcos R. O. A. Maximo ITA
  • Takashi Yoneyama ITA

Resumo


Usando um método aprimorado de Mapa Auto-Organizável, fornecemos soluções abaixo do ideal para o Problema do Caixeiro Viajante. Além disso, empregamos o ajuste de hiperparâmetros para identificar os recursos mais críticos do algoritmo. Todas as melhorias no trabalho de benchmark trouxeram resultados consistentes e podem inspirar esforços futuros para melhorar este algoritmo e aplicá-lo a diferentes problemas.

Palavras-chave: Self-organizing maps, TSP problem, Machine Learning

Referências

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Publicado
29/11/2021
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DANTAS, Joao P. A.; COSTA, Andre N.; MAXIMO, Marcos R. O. A.; YONEYAMA, Takashi. Enhanced Self-Organizing Map Solution for the Traveling Salesman Problem. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 18. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 799-802. DOI: https://doi.org/10.5753/eniac.2021.18428.

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