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URN: urn:nbn:de:0030-drops-1924
URL: http://drops.dagstuhl.de/opus/volltexte/2005/192/
Hoogeveen, Han ; Van den Akker, Marjan

Getting rid of stochasticity: applicable sometimes

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Abstract

We consider the single-machine scheduling problem of minimizing the number of late jobs. This problem is well-studied and well-understood in case of deterministic processing times. We consider the problem with stochastic processing times, and we show that for a number of probability distributions the problem can be reformulated as a deterministic problem (and solved by the corresponding algorithm) when we use the concept of minimum success probabilities, which is, that we require that the probability that a job complete on time is `big enough'. We further show that we can extend our approach to the case of machines with stochastic output.

BibTeX - Entry

@InProceedings{hoogeveen_et_al:DSP:2005:192,
  author =	{Han Hoogeveen and Marjan Van den Akker},
  title =	{Getting rid of stochasticity: applicable sometimes},
  booktitle =	{Algorithms for Optimization with Incomplete Information},
  year =	{2005},
  editor =	{Susanne Albers and Rolf H. M{\"o}hring and Georg Ch. Pflug and R{\"u}diger Schultz},
  number =	{05031},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Internationales Begegnungs- und Forschungszentrum f{\"u}r Informatik (IBFI), Schloss Dagstuhl, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2005/192},
  annote =	{Keywords: Scheduling , sequencing , single machine , number of late jobs , stochastic processing times , minimum success probability , dynamic programming}
}

Keywords: Scheduling , sequencing , single machine , number of late jobs , stochastic processing times , minimum success probability , dynamic programming
Freie Schlagwörter (deutsch): unreliable machines
Seminar: 05031 - Algorithms for Optimization with Incomplete Information
Issue date: 2005
Date of publication: 17.06.2005

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