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Stochastic minimum spanning trees in euclidean spaces

Published: 13 June 2011 Publication History

Abstract

We study the complexity of geometric minimum spanning trees under a stochastic model of input: Suppose we are given a master set of points s1,s_2,...,sn in d-dimensional Euclidean space, where each point si is active with some independent and arbitrary but known probability pi. We want to compute the expected length of the minimum spanning tree (MST) of the active points. This particular form of stochastic problems is motivated by the uncertainty inherent in many sources of geometric data but has not been investigated before in computational geometry to the best of our knowledge. Our main results include the following.
We show that the stochastic MST problem is SPHARD for any dimension d ≥ 2. We present a simple fully polynomial randomized approximation scheme (FPRAS) for a metric space, and thus also for any Euclidean space. For d=2, we present two deterministic approximation algorithms: an O(n4)-time constant-factor algorithm, and a PTAS based on a combination of shifted quadtrees and dynamic programming. We show that in a general metric space the tail bounds of the distribution of the MST length cannot be approximated to any multiplicative factor in polynomial time under the assumption that P ≠ NP.
In addition to this existential model of stochastic input, we also briefly consider a locational model where each point is present with certainty but its location is probabilistic.

References

[1]
I. Althöfer, G. Das, D. Dobkin, D. Joseph, and J. Soares. On sparse spanners of weighted graphs. Discrete Comput. Geom., 9(1):81--100, 1993.
[2]
S. Arora. Polynomial time approximation schemes for euclidean tsp and other geometric problems. In FOCS, pages 2--11, 1996.
[3]
S. Arora. Polynomial time approximation schemes for euclidean traveling salesman and other geometric problems. J. ACM, 45(5):753--782, 1998.
[4]
J. Beardwood, J. H. Halton, and J. M. Hammersley. The shortest path through many points. Proc. Cambridge Philos. Soc., 55:299--327, 1959.
[5]
M. W. Bern and D. Eppstein. Worst-case bounds for subadditive geometric graphs. In Symposium on Computational Geometry, pages 183--188, 1993.
[6]
D. Bertsimas. Probabilistic Combinatorial Optimization Problems. PhD thesis, Operation Research Center, MIT, Cambridge, MASS, 1988.
[7]
T. M. Chan. Well-separated pair decomposition in linear time? Inf. Process. Lett., 107(5):138--141, 2008.
[8]
M. De Berg, O. Cheong, and M. van Kreveld. Computational geometry: algorithms and applications. Springer, 2008.
[9]
K. Dhamdhere, R. Ravi, and M. Singh. On two-stage stochastic minimum spanning trees. In IPCO, volume 3509, pages 321--334, 2005.
[10]
A. D. Flaxman, A. Frieze, and M. Krivelevich. On the random 2-stage minimum spanning tree. In SODA '05: Proc. 16th Annual ACM-SIAM symposium on Discrete algorithms, pages 919--926, 2005.
[11]
P. Gupta, A. Martin, R. Ravi, and A. Sinha. Boosted sampling: Approximation algorithms for stochastic optimization. In Proc. 36th Annual ACM Symposium on Theory of Computing, pages 417--426, 2003.
[12]
M. T. Hajiaghayi, R. Kleinberg, and T. Leighton. Improved lower and upper bounds for universal tsp in planar metrics. In Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm, SODA '06, pages 649--658. ACM, 2006.
[13]
F. K. Hwang, Richards, and P. D. S., Winter. The Steiner Tree Problem. North-Holland Publishing Company, 1992.
[14]
N. Immorlica, M. Karger, D.and Minkoff, and V. S. Mirrokni. On the costs and benefits of procrastination: approximation algorithms for stochastic combinatorial optimization problems. In SODA '04: Proc. 15th Annual ACM-SIAM symposium on Discrete algorithms, pages 691--700, 2004.
[15]
P. Jaillet. A priori solution of a traveling salesman problem in which a random subset of the customers are visited. Math. Oper. Res., 6(6), 1988.
[16]
I. A. Kanj, L. Perković, and X. Ge. Computing lightweight spanners locally. In DISC '08: Proceedings of the 22nd international symposium on Distributed Computing, pages 365--378, 2008.
[17]
H. J. Karloff. How long can a euclidean traveling salesman tour be? SIAM J. Discrete Math., 2(1), 1989.
[18]
I. Katriel, C. Kenyon-Mathieu, and E. Upfal. Commitment under uncertainty: Two-stage stochastic matching problems. Theoretical Computer Science, 408(2--3):213 -- 223, 2008.
[19]
M. Löffler and J. M. Phillips. Shape fitting on point sets with probability distributions. CoRR, abs/0812.2967, 2008.
[20]
M. Löffler and M. van Kreveld. Largest and smallest convex hulls for imprecise points. Algorithmica, 56:235--269, 2010.
[21]
M. Löffler and M. van Kreveld. Largest bounding box, smallest diameter, and related problems on imprecise points. Comput. Geom. Theory Appl., 43(4):419--433, 2010.
[22]
M. Löffler and M. van Kreveld. Largest bounding box, smallest diameter, and related problems on imprecise points. Comput. Geom., 43(4):419--433, 2010.
[23]
R. Motwani and P. Raghavan. Randomized Algorithms. Cambridge University Press, 1995.
[24]
G. Narasimhan and M. Smid. Geometric Spanner Networks. Cambridge University Press, New York, NY, USA, 2007.
[25]
L. K. Platzman and J. B. III. Spacefilling curves and the planar travelling salesman problem. J. ACM, 36(4):719--737, 1989.
[26]
J. S. Provan and M. O. Ball. The complexity of counting cuts and of computing the probability that a graph is connected. SIAM J. Comput., 12(4):777--788, 1983.
[27]
J. S. Provan. The complexity of reliability computations in planar and acyclic graphs. SIAM J. Comput., 15(3):694--702, 1986.
[28]
D. B. Shmoys and K. Talwar. A constant approximation algorithm for the a priori traveling salesman problem. In IPCO, pages 331--343, 2008.
[29]
T. L. Snyder and J. M. Steele. A priori bounds on the euclidean traveling salesman. SIAM J. Comput., 24(3), 1995.
[30]
J. Steele. On frieze's ζ (3) limit for lengths of minimal spanning trees. Ann. Prob., 9:365--376, 1987.
[31]
C. Swamy and D. B. Shmoys. Approximation algorithms for 2-stage stochastic optimization problems. SIGACT News, 37(1):33--46, 2006.
[32]
R. Tamassia. On embedding a graph in the grid with the minimum number of bends. SIAM J. Comput., 16(3):421--444, 1987.
[33]
G. T. Toussaint. The relative neighborhood graph of a finite planar set. Pattern Recognition, 12:261--268, 1980.

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    cover image ACM Conferences
    SoCG '11: Proceedings of the twenty-seventh annual symposium on Computational geometry
    June 2011
    532 pages
    ISBN:9781450306829
    DOI:10.1145/1998196
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 13 June 2011

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    Author Tags

    1. geometric data structures
    2. stochastic minimum spanning trees

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    SoCG '11
    SoCG '11: Symposium on Computational Geometry
    June 13 - 15, 2011
    Paris, France

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