Improving MMAS using parameter control

Elizabeth Montero, María Cristina Riff, Daniel Basterrica

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferencia

4 Citas (Scopus)

Resumen

Tunning parameters values in metaheuristics is a time consuming task. Techniques to control parameters during the execution have been successfully applied into evolutionary algorithms. The key idea is that the algorithm themselves computes its parameters values according to its current state of the search. In this paper, we propose a strategy to include parameters control on ants based algorithms. We have tested our approach to solve hard instances of the travel salesman problem using MMAS. The tests shown that in some cases, it is possible to obtain better results than the reported ones for the same algorithm, by including a parameter control strategy.

Idioma originalInglés
Título de la publicación alojada2008 IEEE Congress on Evolutionary Computation, CEC 2008
Páginas4006-4010
Número de páginas5
DOI
EstadoPublicada - 14 nov 2008
Evento2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China
Duración: 1 jun 20086 jun 2008

Conferencia

Conferencia2008 IEEE Congress on Evolutionary Computation, CEC 2008
PaísChina
CiudadHong Kong
Período1/06/086/06/08

Áreas temáticas de ASJC Scopus

  • Teoría computacional y matemáticas
  • Ciencia computacional teórica

Huella Profundice en los temas de investigación de 'Improving MMAS using parameter control'. En conjunto forman una huella única.

  • Citar esto

    Montero, E., Riff, M. C., & Basterrica, D. (2008). Improving MMAS using parameter control. En 2008 IEEE Congress on Evolutionary Computation, CEC 2008 (pp. 4006-4010). [4631343] https://doi.org/10.1109/CEC.2008.4631343