Abstract
This paper investigates the performance of a set of greedy algorithms for solving the Multi-Capacitated Metric Scheduling Problem (MCM-SP). All algorithms considered are variants of ESTA (Earliest Start Time Algorithm), previously proposed in [3]. The paper starts with an analysis of ESTA’s performance on different classes of MCM-SP problems. ESTA is shown to be effective on several of these classes, but is also seen to have difficulty solving problems with heavy resource contention. Several possibilities for improving the basic algorithm are investigated. A first crucial modification consists of substituting ESTA’s pairwise analysis of resource conflicts with a more aggregate and thus more powerful Minimal Critical Set (MCS) computation. To cope with the combinatorial task of enumerating MCSs, several approximate sampling procedures are then defined. Some systematic sampling strategies, previously shown effective on a related but different class of scheduling problem, are found to be less effective on MCM-SP. On the contrary, a randomized MCS sampling technique is introduced, forming a variant of ESTA that is shown to be quite powerful on highly constrained problems.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Amedeo Cesta and Angelo Oddi’s work is supported by Italian Space Agency, by CNR Committee 12 on Information Technology (Project SCI*SIA), and CNR Committee 4 on Biology and Medicine. Stephen F. Smith’s work has been sponsored in part by the National Aeronautics and Space Administration under contract NCC 2-976, by the US Department of Defense Advanced Research Projects Agency under contract F30602-97-20227, and by the CMU Robotics Institute.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Baptiste, P., Le Pape, C., Nuijten, W.P.M.: Satifiability Tests and Time-Bound Adjustments for Cumulative Scheduling Problems. Technical report, Univerity of Compiégnie, in Annals of Operations Research (1997) (to appear)
Bartusch, M., Mohring, R.H., Radermacher, F.J.: Scheduling Project Networks with Resource Constraints and Time Windows. Annals of Operations Research 16, 201–240 (1988)
Cesta, A., Oddi, A., Smith, S.F.: Profile Based Algorithms to Solve Multiple Capacitated Metric Scheduling Problems. In: Proceedings of the Fourth Int. Conf. on Artificial Intelligence Planning Systems, AIPS 1998 (1998)
Cesta, A., Oddi, A., Smith, S.F.: Scheduling Multi-Capacitated Resources under Complex Temporal Constraints. Technical Report CMU-RI-TR-98-17, Robotics Institute, Carnegie Mellon University (1998)
Cesta, A., Oddi, A., Smith, S.F.: An Iterative Sampling Procedure for Resource Constrained Project Scheduling with Time Windows. In: Proceedings of the 16th Int. Joint Conference on Artificial Intelligence, IJCAI 1999 (1999)
Cheng, C., Smith, S.F.: Generating Feasible Schedules under Complex Metric Constraints. In: Proceedings 12th National Conference on AI, AAAI 1994 (1994)
Laborie, P., Ghallab, M.: Planning with Sharable Resource Constraints. In: Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI 1995 (1995)
Nuijten, W.P.M.: Time and Resource Constrained Scheduling - A Constraint Satisfaction Approach. PhD thesis, Eindhoven University of Technology, The Netherlands (1994)
Nuijten, W.P.M., Aarts, E.H.L.: A Computational Study of Constraint Satisfaction for Multiple Capacitated Job Shop Scheduling. European Journal of Operational Research 90(2), 269–284 (1996)
Oddi, A., Smith, S.F.: Stochastic Procedures for Generating Feasible Schedules. In: Proceedings 14th National Conference on AI, AAAI 1997 (1997)
Taillard, E.: Benchmarks for Basic Scheduling Problems. European Journal of Operational Research 64, 278–285 (1993)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cesta, A., Oddi, A., Smith, S.F. (2000). Greedy Algorithms for the Multi-capacitated Metric Scheduling Problem. In: Biundo, S., Fox, M. (eds) Recent Advances in AI Planning. ECP 1999. Lecture Notes in Computer Science(), vol 1809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10720246_17
Download citation
DOI: https://doi.org/10.1007/10720246_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67866-3
Online ISBN: 978-3-540-44657-6
eBook Packages: Springer Book Archive