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Randomized Parallel Algorithms for Combinatorial Optimization

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Abstract

In this paper we show some important randomization techniques for the parallel processing of discrete problems. In particular, we present several parallel randomized algorithms frequently used for sorting, packet routing, shortest paths problems, matching problems, depth first search, minimum cost spanning trees, and maximal independent set problems. We also discuss the connection between randomization and approximation, showing how randomization yields approximate solutions and we illustrate this connection by means of network flow problems.

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Author information

Authors and Affiliations

  1. Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, 32611, USA

    Sanguthevar Rajasekaran

  2. Centre Universitaire d’Informatique, University of Geneva, CH, Switzerland

    José D. P. Rolim

Authors
  1. Sanguthevar Rajasekaran
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  2. José D. P. Rolim
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Editor information

Editors and Affiliations

  1. University of Minnesota, Minneapolis, USA

    Ding-Zhu Du

  2. University of Florida, Gainesville, USA

    Panos M. Pardalos

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© 1998 Kluwer Academic Publishers

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Rajasekaran, S., Rolim, J.D.P. (1998). Randomized Parallel Algorithms for Combinatorial Optimization. In: Du, DZ., Pardalos, P.M. (eds) Handbook of Combinatorial Optimization. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0303-9_32

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  • DOI: https://doi.org/10.1007/978-1-4613-0303-9_32

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