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
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