Abstract

One way to cope with an NP-hard problem is to find an algorithm that is fact on average with respect to a natural probability distribution on inputs. We consider from that point of view the Hamiltonian Path Problem. Our algorithm for the Hamiltonian Path Problem constructs or establishes the nonexistence of a Hamiltonian path. For a fixed probability p, the expected run-time of our algorithm on a random graph with n vertices and the edge probability p is $O(n)$. The algorithm is adaptable to directed graphs.

MSC codes

  1. 05G35
  2. 60C05
  3. 68A10
  4. 68A20

Keywords

  1. average case complexity
  2. NP-hard Hamiltonian circuit Hamiltonian path
  3. probability
  4. random graphs
  5. expected polynomial time
  6. expected sublinear time

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References

1.
D. Angluin, L. G. Valiant, Fast probabilistic algorithms for Hamiltonian circuits and matchings, J. Comput. System Sci., 18 (1979), 155–193
2.
Richard Bellman, Combinatorial processes and dynamic programmingProc. Sympos. Appl. Math., Vol. 10, American Mathematical Society, Providence, R.I., 1960, 217–249
3.
B. Bollobas, Graph theory, Graduate Texts in Mathematics, Vol. 63, Springer-Verlag, New York, 1979x+180, Berlin
4.
B. Bollobas, T. I. Fenner, A. M. Frieze, An algorithm for finding Hamilton cycles in a random graph, Proc. 17th Annual ACM Symposium on Theory of Computing, 1985, 430–439
5.
Herman Chernoff, A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations, Ann. Math. Statistics, 23 (1952), 493–507
6.
Paul Erdös, Joel Spencer, Probabilistic methods in combinatorics, Academic Press [A subsidiary of Harcourt Brace Jovanovich, Publishers], New York-London, 1974, 106–
7.
Michael R. Garey, David S. Johnson, Computers and intractability, W. H. Freeman and Co., San Francisco, Calif., 1979x+338
8.
R. L. Graham, Applications of the FKG inequality and its relativesMathematical programming: the state of the art (Bonn, 1982), Springer, Berlin, 1983, 115–131, New York
9.
Y. Gurevich, S. Shelah, Expected computation time for Hamiltonian Path Problem and clique problem, Tech. Report, CRL-TR-50-84, Univ. of Michigan, Ann Arbor, 1984
10.
Michael Held, Richard M. Karp, A dynamic programming approach to sequencing problems, J. Soc. Indust. Appl. Math., 10 (1962), 196–210
11.
David S. Johnson, The NP-completeness column: an ongoing guide, J. Algorithms, 5 (1984), 284–299
12.
L. Levin, Problems, complete in “average” instance, Proc. 16th Annual ACM Symposium on Theory of Computing, 1984, 465–
13.
L. Posa, Hamiltonian circuits in random graphs, Discrete Math., 14 (1976), 359–364
14.
Walter J. Savitch, Relationships between nondeterministic and deterministic tape complexities, J. Comput. System. Sci., 4 (1970), 177–192
15.
Eli Shamir, How many random edges make a graph Hamiltonian?, Combinatorica, 3 (1983), 123–131

Information & Authors

Information

Published In

cover image SIAM Journal on Computing
SIAM Journal on Computing
Pages: 486 - 502
ISSN (online): 1095-7111

History

Submitted: 27 June 1985
Accepted: 26 July 1986
Published online: 13 July 2006

MSC codes

  1. 05G35
  2. 60C05
  3. 68A10
  4. 68A20

Keywords

  1. average case complexity
  2. NP-hard Hamiltonian circuit Hamiltonian path
  3. probability
  4. random graphs
  5. expected polynomial time
  6. expected sublinear time

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