Abstract
This paper describes our experience with a simple modeling and programming approach for increasing the amount of constraint propagation in the constraint solving process. The idea, although similar to redundant constraints, is based on the concept of redundant modeling. We introduce the notions of CSP model and model redundancy, and show how mutually redundant models can be combined and connected using channeling constraints. The combined model contains the mutually redundant models as sub-models. Channeling constraints allow the sub-models to cooperate during constraint solving by propagating constraints freely amongst the sub-models. This extra level of pruning and propagation activities becomes the source of execution speedup. real-life nurse rostering system. We perform two case studies to evaluate the effectiveness and efficiency of our method. The first case study is based on the simple and well-known n-queens problem, while the second case study applies our method in the design and construction of a real-life nurse rostering system. Experimental results provide empirical evidence in line with our prediction.
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References
Aggoun, A. (1994). A good value-ordering heuristics for the n-queens problem. Private Communication.
Baptiste, P. and C. Le Pape. (1995). Disjunctive constraints for manufacturing scheduling: Principles and extensions. In Proceedings of the Third International Conference on Computer Integrated Manufacturing, Singapore.
Beldiceanu, N. and E. Contejean. (1994). Introducing global constraints in CHIP. Journal of Mathematical and Computer Modelling, 20(12): 97–123.
Benson Jr., B.W. and E.C. Freuder. (1992). Interchangeability preprocessing can improve forward checking search. In Proceedings of the 10th European Conference on Artificial Intelligence, pages 28–30.
Bessière, C. and M. Cordier. (1993). Arc-consistency and arc-consistency again. In Proceedings of AAAI-93, pages 108–113.
Bitner, J. and E.M. Reingold. (1985). Backtrack programming techniques. Communications of the ACM, 18: 651–655.
Caseau, Y. (1989).. A formal system for producing demons from rules. In Proceedings of the 1989 International Conference on Deductive and Object-Oriented Databases, pages 203–219.
Caseau, Y. (1991). An object-oriented deductive language. Annals of Mathematics and Artificial Intelligence.
Caseau, Y. and P. Koppstein. (1992). A rule-based approach to a time-constrained traveling salesman problem. Unpublished manuscript.
Cheng, B.M.W., J.H.M. Lee, and J.C.K. Wu. (1996). A constraint-based nurse rostering system using a redundant modeling approach. In Proceedings of the Eighth IEEE International Conference on Tools with Artificial Intelligence, pages 140–148.
Cheng, B.M.W., J.H.M. Lee, and J.C.K. Wu. (1996). Speeding up constraint propagation by redundant modeling. In Proceedings of the Second International Conference on Principles and Practice of Constraint Programming, pages 91–103.
Cheng, B.M.W., J.H.M. Lee, and J.C.K. Wu. (1997). Anurse rostering system using constraint programming and redundant modeling. IEEE Transactions in Information Technology in Biomedicine, 1(1): 44–54.
Cormen, T.H. (1990). C.E. Leiserson, and R.L. Rivest. Introduction to Algorithms. The MIT Press.
Dechter, R. and J. Pearl. (1988). Network-based heuristics for constraint-satisfaction problems. Artificial Intelligence, 38:1–38.
Deville, Y. and P. Van Hentenryck. (1991). An efficient arc consistency algorithm for a class of CSP algorithm. In Proceedings of IJCAI 1991, pages 325–330.
Dincbas, M. H. Simonis, and P. Van Hentenryck. (1988). Solving the car-sequencing problem in constraint logic programming. In Proceedings of the European Conference on Artificial Intelligence, pages 290–295.
Dincbas, M., P. Van Hentenryck, H. Simonis, A. Aggoun, and T. Graf. (1988). Applications of CHIP to industrial and engineering problems. In Proceedings of the 1st International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems, pages 887–892.
Dincbas, M., P. Van Hentenryck, H. Simonis, A. Aggoun, T. Graf, and F. Berthier. (1988). The constraint logic programming language CHIP. In Proceedings of the International Conference on Fifth Generation Computer Systems (FGCS'88), pages 693–702, Tokyo, Japan.
Eaton, P.S. and E.C. Freuder. (1996). Agent cooperation can compensate for agent ignorance in constraint satisfaction. In Proceedings of the 1996 AAAI Workshop on Agent Modeling, pages 24–29. AAAI Press. Technical Report WS–96–02.
Ellman, T. (1993). Abstraction via approximate symmetry. In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, pages 916–921.
Freuder, E.C. (1982). A sufficient condition for backtrack-free search. Journal of the ACM, 29:24–32.
Freuder, E.C. and D. Sabin. (1995). Interchangeability supports abstraction and reformation for constraint satisfaction. In Proceedings of the Symposium on Abstraction, Reformulation and Approximation.
Gaschnig, J. (1977). A general backtrack algorithm that eliminates most redundant tests. In Proceedings of the Fifth International Joint Conference on Artificial Intelligence.
Gaschnig, J. (1978). Experimental case studies of backtrack versus Waltz-type versus new algorithms for satisfying assignment problems. In Proceedings of the Second Biennial Conference of the Canadian Society for Computational Studies of Intelligence. Canadian Information Processing Society.
Gaschnig, J. (1979). Performance Measurement and Analysis of Certain Search Algorithms. PhD thesis, Department of Computer Science, Carnegie-Mellon University, Pittsburgh, U.S.A.
Gaschnig, J. (1979). Performance measurement and analysis of certain search algorithms. Technical Report CMU-CS-79-124, Carnegie-Mellon University.
Geelen, P.A. (1992). Dual viewpoint heuristics for binary constraint satisfaction problem. In Proceedings of the 10th European Conference on Artificial Intelligence, pages 31–35.
Gervet, C. (1994). Conjunto: Constraint logic programming with finite set domains. In Logic Programming: Proceedings of the 1994 International Symposium, pages 339–358.
Gervet, C. (1997). Interval propagation to reason about sets: definition and implementation of a practical language. CONSTRAINTS, 1(3):191–244.
Haralick, R.M. and G.L. Elliot. (1980). Increasing tree search efficiency for constraint satisfaction problems. Artificial Intelligence, 14:263–313.
ILOG. (1995). ILOG SOLVER: Reference Manual Version 3.0.
ILOG. (1995). ILOG SOLVER: User Manual Version 3.0.
ILOG. (1997). ILOG SOLVER: Reference Manual Version 4.0.
Jourdan, J. (1995). Concurrent constraint multiple models in CLP and CC languages: toward a programming methodology by modelling. In Proceedings of the INFORMS Conference, New Orleans, USA.
Jourdan, J. (1995). Concurrent constraint multiple models inCLPandCClanguages: Toward a programming methodology by modelling. PhD thesis, Denis Diderot University, Paris VII.
Kökény, T. (1995). Constraint satisfaction problems with order-sorted domains. International Journal on Artificial Intelligence Tools, 4(1&2):55–72.
Kumar, V. (1992). Algorithms for constraint-satisfaction problems: A survey. AI Magazine, 13:32–44.
Le Pape, C. (1994). Implementation of resource constraints in ILOG SCHEDULE: Alibrary for the development of constraint-based scheduling systems. Intelligent Systems Engineering, 3:55–66.
Le Pape, C. (1995). Resource constraints in a library for constraint-based scheduling. In Proceedings of the INRIA/IEEE Conference on Emerging Technologies and Factory Automation, Paris, France.
Lee, J.H.M., H.F. Leung, P. Stuckey, V. Tam, and H.W. Won. (1996). Using stochastic methods to guide search in CLP: a preliminary report. In Proceedings of the 1996 Asian Computing Science Conference, pages 43–52.
Liu and K. Sycara, J. (1993). Emergent constraint satisfaction through multi-agent coordinated interaction. In Proceedings of MAAMAW'93, Neuchatel, Switzerland.
Mackworth, A.K. (1977). Consistency in networks of relations. AI Journal, 8(1):99–118.
Mackworth, A.K., J.A. Mulder, and W.S. Havens. (1985). Hierarchical arc consistency: Exploiting structured domains in constraint satisfaction problems. Computational Intelligence, 1:118–126.
Marti, P. and M. Rueher. (1995). Adistributed cooperating constraints solving system. International Journal on Artificial Intelligence Tools, 4(1&2):93–113.
Minton, S., M.D. Johnston, A.B. Philips, and P. Laird. (1992). Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling. Artificial Intelligence, 58:161–205.
Mohr, R. and T.C. Henderson. (1986). Arc and path consistency revisited. Artificial Intelligence, 28:225–233.
Nadel, B.A. (1989). Constraint satisfaction algorithms. Computational Intelligence, 5:188–224.
Perrett, M. (1991). Using constraint logic programming techniques in container port planning. ICL Technical Journal, 7(3):537–545.
Prosser, P. (1993). Hybrid algorithms for the constraint satisfaction problem. Computational Intelligence, 9(3):268–299.
Tsang, E.P.K. (1993). Foundations of Constraint Satisfaction. Academic Press.
van Beek, P. (1992). On the minimality and decomposability of constraint networks. In Proceedings of the Tenth National Conference on Artificial Intelligence, pages 447–452.
Van Hentenryck, P. (1989). Constraint Satisfaction in Logic Programming. The MIT Press.
Van Hentenryck, P., Y. Deville, and C.M. Teng. (1992). A generic arc-consistency algorithm and its specializations. Artificial Intelligence, 57:291–321, 1992.
Wallace, R. (1996). Partial models in redundant modeling. Private Communication at CP96.
Waltz, D. (1975). Understanding line drawings of scenes with shadows. In P.H. Winston, editor, The Psychology of Computer Vision, pages 19–91. McGraw-Hill.
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Cheng, B.M.W., Choi, K.M.F., Lee, J.H.M. et al. Increasing Constraint Propagation by Redundant Modeling: an Experience Report. Constraints 4, 167–192 (1999). https://doi.org/10.1023/A:1009894810205
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DOI: https://doi.org/10.1023/A:1009894810205