DagSemProc.05031.18.pdf
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New Old Algorithms for Stochastic Scheduling
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Dagstuhl Seminar Proceedings, Volume 5031
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2005-06-17
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Andreas S. Schulz. New Old Algorithms for Stochastic Scheduling. In Algorithms for Optimization with Incomplete Information. Dagstuhl Seminar Proceedings, Volume 5031, pp. 1-9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)
https://doi.org/10.4230/DagSemProc.05031.18
https://doi.org/10.4230/DagSemProc.05031.18
Abstract
We consider the stochastic identical parallel machine scheduling problem and its online extension, when the objective is to minimize the expected total weighted completion time of a set of jobs that are released over time. We give randomized as well as deterministic online and offline algorithms that have the best known performance guarantees in either setting, online or offline and deterministic or randomized. Our analysis is based on a novel linear programming relaxation for stochastic scheduling problems that can be solved online.
Keywords
- stochastic scheduling
- online algorithms
- competitive analysis
- approximation algorithms
- linear programming relaxations
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