By Andrew V. Goldberg (auth.), Stefan Arnborg, Lars Ivansson (eds.)
This e-book constitutes the refereed court cases of the sixth Scandinavian Workshop on set of rules conception, SWAT'98, held in Stockholm, Sweden, in July 1998.
The quantity offers 28 revised complete papers chosen from fifty six submissions; additionally integrated are 3 invited contributions. The papers current unique study on algorithms and information constructions in a variety of components together with computational geometry, parallel and disbursed platforms, graph thought, approximation, computational biology, queueing, Voronoi diagrams, and combinatorics in general.
Read or Download Algorithm Theory — SWAT'98: 6th Scandinavian Workshop on Algorithm Theory Stockholm, Sweden, July 8–10, 1998 Proceedings PDF
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Additional resources for Algorithm Theory — SWAT'98: 6th Scandinavian Workshop on Algorithm Theory Stockholm, Sweden, July 8–10, 1998 Proceedings
24 19. R. Panigrahy, “An O(log n) approximation algorithm for the asymmetric p-center problem”, manuscript, 1995. 20. J. Plesnik, “A heuristic for the p-center problem in graphs”, Discrete Applied Mathematics, Vol 17:263–268, (1987) 25, 25, 25, 28 21. R. Ravi, M. X. Goemans, “The constrained minimum spanning tree problem”, SWAT 1996, 66-75. 24 22. D. Serra and V. Marianov, “The P-median problem in a changing network: The case of Barcelona”, paper presented at the International Symposium in Locational Decisions VII, (ISOLDE), Edmonton, Canada, (1996).
Um such that i∈Uj si ≤ 1 for each 1 ≤ j ≤ m. The goal is to find a conflict-free packing with a minimum number m of bins. For any instance I = (G = (V, E), (s1 , . . , sn )), let SIZE(I) = ni=1 si denote the total size of the n items, and let OP T (I) denote the minimum number of unit size bins needed to pack all items without conflicts. For graph classes not defined in this paper we refer to . One application of the problem is the assignment of processes to processors. g. multi media streams) where some of the processes are not allowed to execute on the same processor.
We provide constant-factor approximation algorithms for all these problems when there are two time-slots (this models the situation of “rush hour” and “non-rush hour” travel times). For example, we could declare 7am to 9am and 4pm to 6pm as “rush hour” and all other times as “non-rush hour”. (The rush hour could happen many times during the day. ) We show that even under the simple time-slot model for varying distances, if there are more than two time-slots then no constant approximation is possible.