This paper introduces a general methodology to perform a comparative evaluation of different approaches to the problem of scheduling with uncertainty. Different proactive (off-line) and reactive (on-line) scheduling policies are evaluated by simulating the execution of a number of baseline schedules under uncertain environmental conditions, and observing the solution behaviors as such schedules get stressed by exogenous events. The analysis aims at assessing the impact of both proactive and reactive scheduling efforts on the robustness of the baseline solutions, against measurable disrupting factors, through reproducible experiments. As the results show, this dynamic approach reveals extremely useful to unveil some subtle aspects, which would have remained undetected through static metric evaluations.

Validating Scheduling Approaches Against Executional Uncertainty

Rasconi R;Cesta A;
2010

Abstract

This paper introduces a general methodology to perform a comparative evaluation of different approaches to the problem of scheduling with uncertainty. Different proactive (off-line) and reactive (on-line) scheduling policies are evaluated by simulating the execution of a number of baseline schedules under uncertain environmental conditions, and observing the solution behaviors as such schedules get stressed by exogenous events. The analysis aims at assessing the impact of both proactive and reactive scheduling efforts on the robustness of the baseline solutions, against measurable disrupting factors, through reproducible experiments. As the results show, this dynamic approach reveals extremely useful to unveil some subtle aspects, which would have remained undetected through static metric evaluations.
2010
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Uncertainty in Scheduling
Reactive
Proactive
Benchmarking
Artificial Intelligence
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/33335
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