We show that a fully polynomial time approximation scheme given
for an optimization problem can always be simply modified to a
polynomial time algorithm solving the problem optimally if the
computation model is the deterministic Turing Machine or the
logarithmic cost RAM and ...
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TSP(1,2), the Traveling Salesman Problem with distances 1 and 2, is
the problem of finding a tour of minimum length in a complete
weighted graph where each edge has length 1 or 2. Let $d_o$ satisfy
$0<d_o<1/2$. We show that TSP(1,2) has no PTAS on the set ...
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We present the first approximation schemes for minimizing weighted flow time
on a single machine with preemption. Our first result is an algorithm that
computes a $(1+\eps)$-approximate solution for any instance of weighted flow
time in $O(n^{O(\ln W \ln P/\eps^3)})$ time; here $P$ is the ratio ...
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We prove that MAX-3SAT can be approximated in polynomial time
within a factor 9/8 on random instances.
We prove existence of approximation schemes for instances of MAX-CUT with $\Omega(\frac{n^2}{\Delta})$ edges which work in $2^{O^\thicksim(\frac{\Delta}{\varepsilon^2})}n^{O(1)}$ time. This entails in particular existence of quasi-polynomial approximation schemes (QPTASs) for mildly sparse instances of MAX-CUT with $\Omega(\frac{n^2}{\operatorname{polylog} n})$ edges. The result depends on new sampling method for smoothed linear programs that ... more >>>
Suppose you ran a chess tournament, everybody played everybody, and you wanted to use the results to rank everybody. Unless you were really lucky, the results would not be acyclic, so you could not just sort the players by who beat whom. A natural objective is to find a ranking ... more >>>
We construct the first constant time value approximation schemes (CTASs) for Metric and Quasi-Metric MAX-rCSP problems for any $r \ge 2$ in a preprocessed metric model of computation, improving over the previous results of [FKKV05] proven for the general core-dense MAX-rCSP problems. They entail also the first sublinear approximation schemes ... more >>>