The objective of this paper is to characterize classes of problems for which a greedy algorithm finds solutions provably close to optimum. To that end, we introduce the notion of k...
We introduce a new dimension to the widely studied on-line approximate string matching problem, by introducing an error threshold parameter so that the algorithm is allowed to mis...
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
Anton J. Kleywegt, Alexander Shapiro, Tito Homem-d...
Abstract—Hybrid methods are very popular for solving problems from combinatorial optimization. In contrast to this the theoretical understanding of the interplay of different opt...
Tobias Friedrich, Jun He, Nils Hebbinghaus, Frank ...
— We study the problem of computing minimal cost multicast trees in multi-hop wireless mesh networks. This problem is known as the Steiner tree problem, and it has been widely st...