Skip to main content
Log in

Algorithmic Power from Declarative Use of Redundant Constraints

  • Published:
Constraints Aims and scope Submit manuscript

Abstract

Interval constraints can be used to solve problems in numerical analysis. In this paper we show that one can improve the performance of such an interval constraint program by the declarative use of constraints that are redundant in the sense of not needed to define the problem. The first example shows that computation of an unstable recurrence relation can be improved. The second example concerns a solver of nonlinear equations. It shows that, by adding as redundant constraints instances of Taylor's theorem, one can obtain convergence that appears to be quadratic.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Alefeld, G., & Herzberger, J. (1983). Introduction to Interval Computations. Academic Press.

  2. Beldiceanu, N., & Contejean, E. (1994). Introducing global constraints in CHIP. Mathematical and Computer Modelling, 20:97–123.

    Google Scholar 

  3. Benhamou, F., McAllester, D., & Van Hentenryck, P. (1994). CLP(Intervals) revisited. In Logic Programming: Proc. 1994 International Symposium, 124–138.

  4. Benhamou, F., Bouvier, P., Colmerauer, A., Garetta, H., Giletta, B., Massat, J-L., Narboni, G. A., N'Dong, S., Pasero, R., Pique, J-F., Touraïvane, Van Caneghem, M., & Vétillard, E. (1996). Le manuel de Prolog IV. Technical report, PrologIA, Parc Technologique de Luminy, Marseille, France.

    Google Scholar 

  5. Benhamou, F., & Older, W. J. (1997). Applying interval arithmetic to real, integer, and Boolean constraints. Journal of Logic Programming, 32:1–24.

    Google Scholar 

  6. BNR. (1988). BNR Prolog user guide and reference manual.

  7. Bol, R., & Degerstedt, L. (1993). Tabulated resolution for well-founded semantics. In Proc. of the Symposium on Logic Programming.

  8. Chen, W., & Warren, D. S. (1996). Tabled evaluation with delaying for general logic programs. Journal of the ACM, 43(1):20–74.

    Google Scholar 

  9. Cheng, B. M. W., Lee, J. H. M., & Wu, J. C. K. (1996). Speeding up constraint propagation by redundant modelling. In Lecture Notes in Computer Science, volume 1118, pages 91–103. Springer-Verlag.

    Google Scholar 

  10. Cleary, J. G. (1987). Logical arithmetic. Future Computing Systems, 2:125–149.

    Google Scholar 

  11. Coolidge, A. S. (1932). A quantum mechanics treatment of the water molecule. Physical Review, 42:189–209.

    Google Scholar 

  12. Hansen, E. (1992). Global Optimization Using Interval Analysis. Marcel Dekker.

  13. Van Hentenryck, P. (1989). Constraint Satisfaction in Logic Programming. MIT Press.

  14. Van Hentenryck, P., Michel, L., & Deville, Y. (1997). Numerica: A Modeling Language for Global Optimization. MIT Press.

  15. Hille, E. (1964). Analysis, Volume I. Blaisdell.

  16. Mackworth, A. K. (1977). Consistency in networks of relations. Artificial Intelligence, 8:99–118.

    Google Scholar 

  17. Michie, D. (1968). Memo functions and machine learning. Nature, 218:19–22.

    Google Scholar 

  18. Montanari, U. (1974). Networks of constraints: Fundamental properties and applications to picture processing. Information Science, 7(2):95–132.

    Google Scholar 

  19. Montanari, U., & Rossi, F. (1991). Constraint relaxation may be perfect. Artificial Intelligence, 48:143–170.

    Google Scholar 

  20. Moore, R. E. (1966). Interval Analysis. Prentice-Hall.

  21. Neumaier, A. (1990). Interval Methods for Systems of Equations. Cambridge University Press.

  22. Older, W. (1992). Constraints in BNR Prolog.

  23. Older, W. J. (1993). Using interval arithmetic for non-linear constrained optimization. Bell-Northern Research Technical Report.

  24. Older, W. J. (1989). The application of relation arithmetic to X-ray diffraction crystallography. Bell-Northern Research Technical Report.

  25. Older, W. J., Swinkels, G. M., & van Emden, M. H. (1995). Getting to the real problem: Experience with BNR Prolog in OR. In Leon Sterling, editor, Proceedings of the Third International Conference on the Practical Application of Prolog, pages 465–478. Alinmead Software Ltd.

  26. Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1992). Numerical Recipes in C, Second Edition. Cambridge University Press.

  27. Sagonas, K., Swift, T., & Warren, D. S. (1994). XSB as an efficient deductive database engine. In Proc. of SIGMOD 1994 Conference. ACM.

  28. Semenov, A. L. (1996). Solving optimization problems with help of the Unicalc solver. In R. Baker Kearfott and Vladik Kreinovich, editors, Application of Interval Computations, pages 211–224. Kluwer Academic Publishers.

  29. Tamaki, H., & Sato, T. (1986). OLDT resolution with tabulation. In Third International Conference on Logic Programming, 84–98.

  30. van Emden, M. H. Finding nonzeroes of nonlinear functions. In preparation.

  31. van Emden, M. H. (1997). Value constraints in the CLP Scheme. Constraints, 2:163–183.

    Google Scholar 

  32. Waltz, D. (1975). Understanding line drawings in scenes with shadows. In Patrick Henry Winston, editor, The Psychology of Computer Vision, pages 19–91. McGraw-Hill.

  33. Zhou, J. (1997). Calcul de plus petits produits cart´esiens d'intervalles. Ph.D. thesis, Laboratoire d'Informatique de Marseille.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

van Emden, M.H. Algorithmic Power from Declarative Use of Redundant Constraints. Constraints 4, 363–381 (1999). https://doi.org/10.1023/A:1009821007410

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1009821007410

Navigation