• DocumentCode
    2046926
  • Title

    Optimal triangulation by means of evolutionary algorithms

  • Author

    Prestifilippo, Giovanni ; Sprave, Joachim

  • Author_Institution
    Dept. of Comput. Sci., Dortmund Univ., Germany
  • fYear
    1997
  • fDate
    2-4 Sep 1997
  • Firstpage
    492
  • Lastpage
    497
  • Abstract
    The comparison in the paper shows that the evolutionary algorithm (EA) triangulation is superior to traditional deterministic algorithms, and that the EA is at least an alternative to simulated annealing (SA). Although SA produces results of the same quality in shorter time, the EA may be preferable for large problem instances due to the existence of efficient parallel implementations. From a more general view, the SA and EA are probabilistic search methods which could be easily modeled in a common framework. The successful application of EAs to surface reconstruction presented here can be seen as a first feasibility study. It is very likely that both the performance of the algorithm and the quality of the results can be further improved by advanced operators, such as recombination and self-adaptive mutation rates
  • Keywords
    genetic algorithms; evolutionary algorithms; large problems; optimal triangulation; probabilistic search methods; recombination; self-adaptive mutation rates; surface reconstruction;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Genetic Algorithms in Engineering Systems: Innovations and Applications, 1997. GALESIA 97. Second International Conference On (Conf. Publ. No. 446)
  • Conference_Location
    Glasgow
  • ISSN
    0537-9989
  • Print_ISBN
    0-85296-693-8
  • Type

    conf

  • DOI
    10.1049/cp:19971229
  • Filename
    681075