Scheduling with uncertainty: A proactive approach using Partial Order Schedules

AI Communications

Volumn 18, Issue 2, 2005, Pages 165-167

  Policella, Nicola ^a  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL COMPLEXITY; PROBLEM SOLVING;

COMPUTATION TIME; FLEXIBILITY; PARTIAL ORDER SCHEDULE (POS); TEMPORAL CONSTRAINTS;

SCHEDULING;

EID: 24644478739     PISSN: 09217126     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review

References (7)

1. P. Baptiste, C. Le Pape and W. Nuijten, Constraint-Based Scheduling, Vol. 39 of International Series in Operations Research and Management Science, Kluwer Academic Publishers, 2001.
2. M. Bartusch, R.H. Mohring and F.J. Radermacher, Scheduling project networks with resource constraints and time windows, Annals of Operations Research 16 (1988), 201-240.
3. A. Cesta, A. Oddi and S.F. Smith, A Constraint-based method for Project Scheduling with Time Windows, Journal of Heuristics 8(1) (2002), 109-136.
4. R. Dechter, I. Meiri and J. Pearl, Temporal constraint networks, Artificial Intelligence 49 (1991), 61-95.
5. N. Muscettola, Computing the envelope for stepwise-constant resource allocations, in: Principles and Practice of Constraint Programming, 8th International Conference, CP 2002, Vol. 2470 of Lecture Notes in Computer Science, Springer, 2002, pp. 139-154.
6. N. Policella, Scheduling with uncertainty: A proactive approach using Partial Order Schedules, PhD thesis, University of Rome "La Sapienza", March 2005.
7. E.P.K. Tsang, Foundations of Constraint Satisfaction, Academic Press, London and San Diego, 1993.