15,432 research outputs found
Finding tight Hamilton cycles in random hypergraphs faster
In an -uniform hypergraph on vertices a tight Hamilton cycle consists
of edges such that there exists a cyclic ordering of the vertices where the
edges correspond to consecutive segments of vertices. We provide a first
deterministic polynomial time algorithm, which finds a.a.s. tight Hamilton
cycles in random -uniform hypergraphs with edge probability at least . Our result partially answers a question of Dudek and Frieze [Random
Structures & Algorithms 42 (2013), 374-385] who proved that tight Hamilton
cycles exists already for for and for
using a second moment argument. Moreover our algorithm is superior to
previous results of Allen, B\"ottcher, Kohayakawa and Person [Random Structures
& Algorithms 46 (2015), 446-465] and Nenadov and \v{S}kori\'c
[arXiv:1601.04034] in various ways: the algorithm of Allen et al. is a
randomised polynomial time algorithm working for edge probabilities , while the algorithm of Nenadov and \v{S}kori\'c is a
randomised quasipolynomial time algorithm working for edge probabilities .Comment: 17 page
A Distributed algorithm to find Hamiltonian cycles in Gnp random graphs
In this paper, we present a distributed algorithm to find Hamiltonian cycles in random binomial graphs Gnp. The algorithm works on a synchronous distributed setting by first creating a small cycle, then covering almost all vertices in the graph with several disjoint paths, and finally patching these paths and the uncovered vertices to the cycle. Our analysis shows that, with high probability, our algorithm is able to find a Hamiltonian cycle in Gnp when p_n=omega(sqrt{log n}/n^{1/4}). Moreover, we conduct an average case complexity analysis that shows that our algorithm terminates in expected sub-linear time, namely in O(n^{3/4+epsilon}) pulses.Postprint (published version
A domination algorithm for -instances of the travelling salesman problem
We present an approximation algorithm for -instances of the
travelling salesman problem which performs well with respect to combinatorial
dominance. More precisely, we give a polynomial-time algorithm which has
domination ratio . In other words, given a
-edge-weighting of the complete graph on vertices, our
algorithm outputs a Hamilton cycle of with the following property:
the proportion of Hamilton cycles of whose weight is smaller than that of
is at most . Our analysis is based on a martingale approach.
Previously, the best result in this direction was a polynomial-time algorithm
with domination ratio for arbitrary edge-weights. We also prove a
hardness result showing that, if the Exponential Time Hypothesis holds, there
exists a constant such that cannot be replaced by in the result above.Comment: 29 pages (final version to appear in Random Structures and
Algorithms
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