By Kurt Mehlhorn (auth.), Tiziana Calamoneri, Irene Finocchi, Giuseppe F. Italiano (eds.)
This publication constitutes the refereed complaints of the sixth Italian convention on Algorithms and Computation, CIAC 2006, held in Rome, Italy, in may perhaps 2006.
The 33 revised complete papers provided including three invited papers have been rigorously reviewed and chosen from eighty submissions. one of the subject matters addressed are sequential, parallel and dispensed algorithms, info constructions, approximation algorithms, randomized algorithms, online algorithms, graph algorithms, research of algorithms, set of rules engineering, algorithmic video game idea, computational biology, computational complexity, verbal exchange networks, computational geometry, cryptography, discrete optimization, graph drawing, mathematical programming, and quantum algorithms.
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Extra resources for Algorithms and Complexity: 6th Italian Conference, CIAC 2006, Rome, Italy, May 29-31, 2006. Proceedings
A2 − 1]. These operations are simultaneously performed on DL as well. t. the sorted
That ∗ S | u∈S y (S, u) = 1 for every u ∈ U. 2 A Network Flow Formulation This section is written in hard-drs terms, but similar arguments can be made in the case of soft-drs. It is very useful to view the LP relaxation as a network ﬂow problem [7, 2]. Here we are given a (fractional) set of lines x and wish to ﬁnd the best possible assignment y. The network Nx is the standard construction used for bipartite graphs. On one side we have all the lines and on the other side we have all the rectangles.
The hardness of the one-dimensional rectangle stabbing (soft or hard) is open. An O(d) approximation algorithm for hard-drs is also open, as well as an O(d) approximation algorithm for weighted soft-drs. In the full version, we show that weighted hard-drs is set-cover hard. Gaur et al.  presented a d-approximation algorithm for weighted drs that uses linear programming to reduce the problem to d one-dimensional instances. Their analysis relies on the integrality of the LP relaxation in the one dimensional case.