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AG Audience

English

45 Minutes

Saarbrücken

In this talk we consider a model for scheduling under uncertainty, which combines the main characteristics of online and stochastic scheduling in a simple and natural way. Job processing times are assumed to be stochastic, but in contrast to traditional stochastic scheduling models, we assume that jobs arrive online, and there is no knowledge about the jobs that will arrive in the future. The model incorporates both, stochastic scheduling and online scheduling as a special case. This talk gives an overview of approximation results and techniques that yield performance guarantees competitive with the best known ones in the traditional online scheduling and stochastic scheduling models, even though we consider a more general setting.

Nicole Megow

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