On approximating the longest path in a graph |
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Authors: | D Karger R Motwani G D S Ramkumar |
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Affiliation: | (1) Department of Computer Science, Stanford University, 94305 Stanford, CA, USA |
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Abstract: | We consider the problem of approximating the longest path in undirected graphs. In an attempt to pin down the best achievable
performance ratio of an approximation algorithm for this problem, we present both positive and negative results. First, a
simple greedy algorithm is shown to find long paths in dense graphs. We then consider the problem of finding paths in graphs
that are guaranteed to have extremely long paths. We devise an algorithm that finds paths of a logarithmic length in Hamiltonian
graphs. This algorithm works for a much larger class of graphs (weakly Hamiltonian), where the result is the best possible.
Since the hard case appears to be that of sparse graphs, we also consider sparse random graphs. Here we show that a relatively
long path can be obtained, thereby partially answering an open problem of Broderet al.
To explain the difficulty of obtaining better approximations, we also prove hardness results. We show that, for any ε<1, the
problem of finding a path of lengthn-n
ε in ann-vertex Hamiltonian graph isNP-hard. We then show that no polynomial-time algorithm can find a constant factor approximation to the longest-path problem
unlessP=NP. We conjecture that the result can be strengthened to say that, for some constant δ>0, finding an approximation of ration
δ is alsoNP-hard. As evidence toward this conjecture, we show that if any polynomial-time algorithm can approximate the longest path
to a ratio of
, for any ε>0, thenNP has a quasi-polynomial deterministic time simulation. The hardness results apply even to the special case where the input
consists of bounded degree graphs.
D. Karger was supported by an NSF Graduate Fellowship, NSF Grant CCR-9010517, and grants from the Mitsubishi Corporation and
OTL. R. Motwani was supported by an Alfred P. Sloan Research Fellowship, an IBM Faculty Development Award, grants from Mitsubishi
and OTL, NSF Grant CCR-9010517, and NSF Young Investigator Award CCR-9357849, with matching funds from IBM, the Schlumberger
Foundation, the Shell Foundation, and the Xerox Corporation, G. D. S. Ramkumar was supported by a grant from the Toshiba Corporation.
Communicated by M. X. Goemans. |
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Keywords: | Long paths Hamiltonian paths Approximation algorithms Complexity theory Random graphs |
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