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Minimum-Cost Load-Balancing Partitions


We consider the problem of balancing the load among several service-providing facilities, while keeping the total cost low. Let D be the underlying demand region, and let p 1,…,p m be m points representing m facilities. We consider the following problem: Subdivide D into m equal-area regions R 1,…,R m , so that region R i is served by facility p i , and the average distance between a point q in D and the facility that serves q is minimal.

We present constant-factor approximation algorithms for this problem, with the additional requirement that the resulting regions must be convex. As an intermediate result we show how to partition a convex polygon into m equal-area convex subregions so that the fatness of the resulting regions is within a constant factor of the fatness of the original polygon. In fact, we prove that our partition is, up to a constant factor, the best one can get if one’s goal is to maximize the fatness of the least fat subregion.

We also discuss the structure of the optimal partition for the aforementioned load balancing problem: indeed, we argue that it is always induced by an additive-weighted Voronoi diagram for an appropriate choice of weights.

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Author information

Correspondence to Matthew J. Katz.

Additional information

An earlier version of this paper appeared in the Proceedings of the 22nd Annual ACM Symposium on Computational Geometry, pp. 301–308, 2006.

B. Aronov’s research supported in part by NSF grant ITR-0081964 and by a grant from the US-Israel Binational Science Foundation.

P. Carmi partially supported by the Lynn and William Frankel Center for Computer Sciences.

M.J. Katz partially supported by grant no. 2000160 from the US-Israel Binational Science Foundation.

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Aronov, B., Carmi, P. & Katz, M.J. Minimum-Cost Load-Balancing Partitions. Algorithmica 54, 318–336 (2009).

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  • Geometric optimization
  • Load balancing
  • Additive-weighted Voronoi diagram
  • Fatness
  • Fat partitions
  • Approximation algorithms