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Given a set S of n points in the plane and a parameter ε>0, a Euclidean (1+ε) -spanner is a geometric graph G=(S,E) that contains a path of weight at most (1+ε)∥pq∥2 for all p,q∈S . We show that the minimum weight of a Euclidean (1+ε)-spanner for n points in the unit square [0,1]2 is O(ε−3/2n−−√), and this bound is the best possible. The upper bound is based on a new spanner algorithm that sparsifies Yao-graphs. It improves upon the baseline O(ε−2n−−√), obtained by combining a tight bound for the weight of an MST and a tight bound for the lightness of Euclidean (1+ε)-spanners, which is the ratio of the spanner weight to the weight of the MST. The result generalizes to d-space for all d∈N : The minimum weight of a Euclidean (1+ε)-spanner for n points in the unit cube [0,1]d is Od(ε(1−d2)/dn(d−1)/d), and this bound is the best possible. For the n×n section of the integer lattice, we show that the minimum weight of a Euclidean (1+ε)-spanner is between Ω(ε−3/4n2) and O(ε−1log(ε−1)n2). These bounds become Ω(ε−3/4n−−√) and O(ε−1log(ε−1)n−−√) when scaled to a grid of n points in [0,1]2. .
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Separating subadditive Euclidean functionals
The classical Beardwood-Halton-Hammersly theorem (1959) asserts the existence of an asymptotic formula of the form $$\beta \sqrt n$$ for the minimum length of a Traveling Salesperson Tour throuh $$n$$ random points in the unit square, and in the decades since it was proved, the existence of such formulas has been shown for other such \emph{Euclidean functionals} on random points in the unit square as well. Despite more than 50 years of attention, however, it remained unknown whether the minimum length TSP through $$n$$ random points in $[0,1]^2$ was asymptotically distinct from its natural lower bounds, such as the minimum length spanning tree, the minimum length 2-factor, or, as raised by Goemans and Bertsimas, from its linear programming relaxation. We prove that the TSP on random points in Euclidean space is indeed asymptotically distinct from these and other natural lower bounds, and show that this separation implies that branch-and-bound algorithms based on these natural lower bounds must take nearly exponential ($$e^{\tilde \Omega(n)}$$) time to solve the TSP to optimality, even in average case. This is the first average-case superpolynomial lower bound for these branch-and-bound algorithms (a lower bound as strong as $$e^{\tilde \Omega (n)}$$ was not even been known in worst-case analysis).
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- Award ID(s):
- 1661063
- PAR ID:
- 10054181
- Date Published:
- Journal Name:
- Random structures & algorithms
- Volume:
- 51
- ISSN:
- 1042-9832
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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