Nordic Journal of Computing Bibliography

U. Pferschy, R. Rudolf, and G. J. Woeginger. Some geometric clustering problems. Nordic Journal of Computing, 1(2):246-263, Summer 1994.
Abstract

This paper investigates the computational complexity of several clustering problems with special objective functions for point sets in the Euclidean plane. Our strongest negative result is that clustering a set of 3k points in the plane into k triangles with minimum total circumference is NP-hard. On the other hand, we identify several special cases that are solvable in polynomial time due to the special structure of their optimal solutions: The clustering of points on a convex hull into triangles; the clustering into equal-sized subsets of points on a line or on a circle with special objective functions; the clustering with minimal clusterdistances. Furthermore, we investigate clustering of planar point sets into convex quadrilaterals.

Categories and Subject Descriptors: F.2.2 [Analysis of Algorithms and Problem Complexity]: Nonnumerical Algorithms and Problems

Selected papers that cite this one

Selected references


Shortcuts:

  • Nordic Journal of Computing homepage
  • Bibliography top level
  • Nordic Journal of Computing Author Index
  • Search the HBP database