Dynamic maintenance of shortest path trees in simple polygons

Author(s):  
Sanjiv Kapoor ◽  
Tripurari Singh
Author(s):  
Annalisa D’Andrea ◽  
Mattia D’Emidio ◽  
Daniele Frigioni ◽  
Stefano Leucci ◽  
Guido Proietti

1994 ◽  
Vol 52 (2) ◽  
pp. 77-85 ◽  
Author(s):  
C.H. Peng ◽  
J.S. Wang ◽  
R.C.T. Lee

2014 ◽  
Vol 70 (5-6) ◽  
pp. 221-232 ◽  
Author(s):  
David Neuhäuser ◽  
Christian Hirsch ◽  
Catherine Gloaguen ◽  
Volker Schmidt

2015 ◽  
Vol 20 ◽  
pp. 1-33 ◽  
Author(s):  
Annalisa D'Andrea ◽  
Mattia D'Emidio ◽  
Daniele Frigioni ◽  
Stefano Leucci ◽  
Guido Proietti

2008 ◽  
Vol 52 (17) ◽  
pp. 3284-3295 ◽  
Author(s):  
Shigeo Shioda ◽  
Kenji Ohtsuka ◽  
Takehiro Sato

Algorithmica ◽  
2021 ◽  
Author(s):  
Davide Bilò ◽  
Luciano Gualà ◽  
Stefano Leucci ◽  
Guido Proietti

1992 ◽  
Vol 02 (02) ◽  
pp. 175-190 ◽  
Author(s):  
SUMANTA GUHA

We present efficient parallel algorithms for two problems in simple polygons: the all-farthest neighbors problem and the external all-farthest neighbors problem. The all-farthest neighbors problem is that of computing, for each vertex p of a simple polygon P, a point ψ(p) in P farthest from p when the distance between p and ψ(p) is measured by the shortest path between them constrained to lie inside P. The external all-farthest neighbors problem is that of computing, for each vertex p of a simple polygon P, a point ϕ(p) on (the boundary of) P farthest from p when the distance between p and ϕ(p) is measured by the shortest path between them constrained to lie outside (the interior of) P. Both our algorithms run in O( log 2 n) time on a CREW PRAM with O(n) processors. Our divide-and-conquer method for the external all-farthest neighbors problem, in fact, leads to a new O(n log n) time serial algorithm that matches the currently best serial algorithm for this problem, but is simpler.


Algorithmica ◽  
1998 ◽  
Vol 22 (3) ◽  
pp. 250-274 ◽  
Author(s):  
D. Frigioni ◽  
A. Marchetti-Spaccamela ◽  
U. Nanni

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