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We present randomized algorithms for finding maximum matchings in general and bipartite graphs. Both algorithms have running time O(n/sup w/), where w is the exponent of the best known matrix multiplication algorithm. Since w < 2.38, these algorithms break through the O(n/sup 2.5/) barrier for the matching problem. They both have a very simple(More)
The Travelling Salesman Problem is one the most fundamental and most studied problems in approximation algorithms. For more than 30 years, the best algorithm known for general metrics has been Christofides's algorithm with approximation factor of 3 2 , even though the so-called Held-Karp LP relaxation of the problem is conjectured to have the integrality(More)
In the shortest superstring problem, we are given a set of strings {s 1 ,. .. , s k } and want to find a string that contains all s i as substrings and has minimum length. This is a classical problem in approximation and the best known approximation factor is 2 1 2 , given by Sweedyk [19] in 1999. Since then no improvement has been made, howerever two other(More)
We present the first 7/8-approximation algorithm for the maximum traveling salesman problem with triangle inequality. Our algorithm is deterministic. This improves over both the random-ized algorithm of Hassin and Rubinstein [3] with expected approximation ratio of 7/8 − O(n −1/2) and the deterministic (7/8 − O(n −1/3))-approximation algorithm of Chen and(More)
In this paper we propose and study a new complexity model for approximation algorithms. The main motivation are practical problems over large data sets that need to be solved many times for different scenarios, e.g., many multicast trees that need to be constructed for different groups of users. In our model we allow a preprocessing phase, when some(More)