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Simulated Annealing Genetic Algorithm for Surface Intersection

Authors: Min Tang 0001; Jinxiang Dong;

Simulated Annealing Genetic Algorithm for Surface Intersection

Abstract

The paper integrated genetic algorithm and marching method into a novel algorithm to solve the surface intersection problem. By combining genetic algorithm with local searching method the efficiency of evolution is greatly improved. By fully utilizing the global searching ability and instinct attribute for parallel computation of genetic algorithm and the local rapid convergence of marching method, the algorithm can compute the intersection robustly and generate correct topology of intersection curves. The details of the new algorithm are discussed here. The algorithm have been implemented in a prototype system named TigerSurf based on Windows/NT platform, and a soundly result is gotten from test datum.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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