Scheduling project networks with resource constraints and time windows
Annals of Operations Research
Artificial Intelligence - Special issue on knowledge representation
Generating feasible schedules under complex metric constraints
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
An iterative sampling procedure for resource constrained project scheduling ith time windows
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Universal plans for reactive robots in unpredictable environments
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
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Increasing attention is being dedicated to the problem of schedule execution management. This has encouraged research focused on the analysis of strategies for the execution of plans in real working environments. To this aim, much work has been recently done to devise scheduling procedures which increase the level of robustness of the produced solutions. Yet, these results represent only the first step in this direction: in order to improve confidence in the theoretical results, it is also necessary to conceive experimental frameworks where the devised measures may find confirmation through empirical testing. This approach also has the advantage of unveiling possible counter-intuitive insights of the proposed scheduling strategies, which otherwise might remain concealed. This paper presents: (a) an experimental platform designed to tackle the problem of schedule execution with uncertainty; (b) an analysis of a variety of schedule execution tests performed under variable environmental conditions.