An evaluation of off-line calibration techniques for evolutionary algorithms

Elizabeth Montero, María Cristina Riff, Bertrand Neveu

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

5 Citas (Scopus)

Resumen

Most metaheuristics define a set of parameters that must be tuned. A good setup of those parameter values can lead to take advantage of all the metaheuristic capabilities to solve the problem at hand. Tuning techniques are step by step methods based on multiple runs of the algorithm. In this study we compare three automated tuning methods: FRace, Revac and ParamILS. We evaluate the performance of each method using a genetic algorithm for combinatorial optimization. The differences and advantages of each technique are discussed. Finally we establish some guidelines that might help to choose a tuning process to use.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10
Páginas299-300
Número de páginas2
DOI
EstadoPublicada - 27 ago 2010
Evento12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010 - Portland, OR, Estados Unidos
Duración: 7 jul 201011 jul 2010

Conferencia

Conferencia12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010
PaísEstados Unidos
CiudadPortland, OR
Período7/07/1011/07/10

Áreas temáticas de ASJC Scopus

  • Teoría computacional y matemáticas
  • Ciencia computacional teórica

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  • Citar esto

    Montero, E., Riff, M. C., & Neveu, B. (2010). An evaluation of off-line calibration techniques for evolutionary algorithms. En Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 (pp. 299-300) https://doi.org/10.1145/1830483.1830540