Sven Oliver Krumke

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In the online traveling salesman problem requests for visits to cities (points in a metric space) arrive online while the salesman is traveling. The salesman moves at no more than unit speed and starts and ends his work at a designated origin. The objective is to find a routing for the salesman which finishes as early as possible. Performance of algorithms(More)
Models and Approximation Algorithms for Channel Assignment in Radio Networks Sven O. Krumke a; Madhav V. Marathe b; S. S. Ravi ; a Konrad-Zuse-Zentrum für Informationstechnik Berlin, Takustr. 7, 14195 Berlin, Germany. Email: krumke@zib.de. b P.O. Box 1663, MS M997, Los Alamos National Laboratory, Los Alamos, NM 87545. Email: marathe@lanl.gov. University at(More)
The traveling repairman problem (TRP) is a variant of the famous traveling salesman problem (TSP). The objective for the TRP is to minimize the latency, that is, the the weighted sum of completion times of the cities, where the completion time of a city is defined to be the time in the tour before the city is reached. In the online traveling repairman(More)
We study a generalization of the p{Center Problem, which we call the {Neighbor p{Center Problem (p{Center ()). Given a complete edge{ weighted network, the goal is to minimize the maximum distance of a client to its nearest neighbors in the set of p centers. We show that in general nding a O(2 poly(jV j)){approximation for p{ Center () is NP{hard, where jV(More)
We investigate the complexity and approximability of network ow improvement problems. In these problems, one incurs costs for increasing the capacity of an edge, while the goal is to achieve a ow of maximum value through the network. We study several improvement strategies. Furthermore, we investigate the relationship of network ow improvement problems to(More)
We consider the problem of placing a speciied number (p) of facilities on the nodes of a network so as to minimize some measure of the distances between facilities. This type of problem models a number of problems arising in facility location, statistical clustering , pattern recognition, and processor allocation problems in multiprocessor systems. We(More)