Results 251 to 260 of about 5,110,730 (289)

Modular scheduling of tightly coupled production lines. [PDF]

open access: yesJ Intell Manuf
Marcè I Igual J   +3 more
europepmc   +1 more source

Lower Bounds for Shellsort

Journal of Algorithms, 1997
Summary: We show lower bounds on the worst-case complexity of Shellsort. In particular, we give a fairly simple proof of an \(\Omega (n(\text{lg}^2n/(\text{lg lg } n)^2)\) lower bound for the size of Shellsort sorting networks for arbitrary increment sequences.
C. Greg Plaxton, Torsten Suel
openaire   +3 more sources

On lower bounded lattices

Algebra Universalis, 2001
The authors study the hierarchy of properties that define lower bounded lattices within the class of all finite lattices. A lattice \(L\) is lower bounded if any homomorphism \(h\) from a finitely generated lattice \(K\) into \(L\) is lower bounded, i.e.\ if \(\{ x\in K\); \(a\leq h(x) \}\) is either empty or has a least element whenever \(a\in h(K)\).
Adaricheva, K. V., Gorbunov, V. A.
openaire   +1 more source

Lower bounds for VLSI

Proceedings of the thirteenth annual ACM symposium on Theory of computing - STOC '81, 1981
Increased use of Very Large Scale Integration (VLSI) for the fabrication of digital circuits has led to increased interest in complexity results on the inherent VLSI difficulty of various problems. Lower bounds have been obtained for problems such as integer multiplication [1,2], matrix multiplication [7], sorting [8], and discrete Fourier transform [9]
Richard J. Lipton, Robert Sedgewick
openaire   +1 more source

A Lower Bound for Interpolation

Logic Journal of IGPL, 1997
A formula \(J\) is called an interpolant of a valid implication \(A\supset B\) if \(J\) contains only the common variables of \(A\) and \(B\) and both \(A\supset J\) and \(J\supset B\) hold; \(\xi (A\supset B)\) denotes the size of the shortest interpolant of the implication \(A\supset B\).
openaire   +2 more sources

Lower bounds on treespan

Information Processing Letters, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Range of lower bounds

Applied Mathematics and Computation, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Lower Bounds for Kernelization

2014
Kernelization is the process of transforming the input of a combinatorial decision problem to an equivalent instance, with a guarantee on the size of the resulting instances as a function of a parameter. Recent techniques from the field of fixed parameter complexity and tractability allow to give lower bounds for such kernels.
openaire   +1 more source

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