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Performance of a comprehensive and efficient constraint library based on local search

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Advanced Topics in Artificial Intelligence (AI 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1502))

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Abstract

Constraint satisfaction is one of the major areas in AI that has important real-life applications. Lee et al. propose E-GENET, a stochastic solver for general constraint solving based on iterative repair. Performance figures show that E-GENET compares favorably against tree-search based solvers in many hard problems. On the other hand, global constraints have been shown to be very effective in modeling complicated CSP’s. They have also improved substantially the efficiency of tree-search based solvers in solving real-life problems. In this paper, we present a comprehensive and efficient library of elementary and global constraints for E-GENET. Such a library is essential for applying E-GENET to complex real-life applications. We first present the improved performance of some constraints that appear in our previous papers, followed by the implementation details of three additional global constraints available in the CHIP constraint language. Experimental results, using standard benchmarks and a real-life problem, confirm empirically that the E-GENET architecture is comparable to, if not better than, state of the art in constraint solver technology.

This project is supported in part by a CUHK Direct Grant.

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References

  1. J. Adams, E. Balas, and D. Zawack. The Shifting Bottleneck Procedure for Job Shop Scheduling. Management Science, 34:391–401, 1988.

    MATH  MathSciNet  Google Scholar 

  2. A. Aggoun and N. Beldiceanu. Extending CHIP in order to Solve Complex Scheduling and Placement Problems. Journal of Mathematical and Computer Modelling, 17(7):57–73, 1993.

    Article  Google Scholar 

  3. N. Beldiceanu and E. Contejean. Introducing Global Constraints in CHIP. Journal of Mathematical and Computer Modeling, 20(12):97–123, 1994.

    Article  MATH  Google Scholar 

  4. P. Codognet and D. Diaz. Compiling Constraints in clp(FD). Journal of Logic Programming, 27(3):185–226, 1996.

    Article  MATH  MathSciNet  Google Scholar 

  5. A. Davenport, E. Tsang, C.J. Wang, and K. Zhu. GENET: A Connectionist Architecture for Solving Constraint Satisfaction Problems by Iterative Improvement. In Proceedings of Twelfth National Conference on Artificial Intelligence, pages 325–330, 1994.

    Google Scholar 

  6. M. Dincbas, H. Simonis, and P. Van Hentenryck. Solving Car Sequencing Problem in Constraint Logic Programming. In Proceedings of Eighth European Conference on Artificial Intelligence, pages 290–295, 1988.

    Google Scholar 

  7. M. Dincbas, P. Van Hentenryck, H. Simonis, A. Aggoun, T. Graf, and F. Berthier. The constraint logic programming language CHIP. In Proceedings of International Conference on Fifth Generation Computer Systems, pages 693–702, December 1988.

    Google Scholar 

  8. N. Funabiki and Y. Takefuji. A Neural Network Parallel Algorithm for Channel Assignment Problems in Cellular Radio Network. IEEE Transactions on Vehicular Technology, 41(4), 1992.

    Google Scholar 

  9. ILOG. ILOG SOLVER: Reference Manual Version 4.0, 1997.

    Google Scholar 

  10. V. Kumar: Algorithms for Constraint-Satisfaction Problems: A Survey. AI Magazine, 13(1):32–44, 1992.

    Google Scholar 

  11. J.H.M. Lee, H.F. Leung, and H.W. Won. Extending GENET for Non-Binary CSP’s. In Proceedings of Seventh International Conference on Tools with Artificial Intelligence, pages 338–343, Washington DC, USA, November 1995. IEEE Computer Society Press.

    Google Scholar 

  12. J.H.M. Lee, H.F. Leung, and H.W. Won. Towards a More Efficient Stochastic Constraint Solver. In Proceedings of Second International Conference on Principles and Practice of Constraint Programming, LNCS 1118, pages 338–352, Cambridge, Massachusetts, USA, August 1996. Springer-Verlag.

    Google Scholar 

  13. J.K. Lenstra and A.H.G. Rinnooy Kan. Computational Complexity of Discrete Optimization Problems. Annals of Discrete Mathematics, 4:121–140, 1979.

    Article  MATH  MathSciNet  Google Scholar 

  14. A.K. Mackworth. Consistency in Networks of Relations. AI Journal, 8(1):99–118, 1977.

    MATH  Google Scholar 

  15. S. Minton, M.D. Johnston, A.B. Philips, and P. Laird. Minimizing Conflicts: A Heuristic Repair Method for Constraint Satisfaction and Scheduling Problems. Artificial Intelligence, 58:161–205, 1992.

    Article  MATH  MathSciNet  Google Scholar 

  16. P. Morris. The breakout method for escaping from local minima. In Proceeding of the 11th National Conference on Artificial Intelligence, pages 40–45, 1993.

    Google Scholar 

  17. J.F. Muth and G.L. Thompson. Industrial Scheduling. Prentice Hall, Engleclood Cliffs, N.J., 1963.

    Google Scholar 

  18. H. Simonis. Modelling Machine Set-up Times in CHIP. Technical Report COSY/TR/95-2, COSYTEC SA, 1995.

    Google Scholar 

  19. H. Simonis, N. Beldiceanu, P. Charlier, and P. Kay. A Model of TACT. Technical Report COSY/TR/95-5, COSYTEC SA, 1995.

    Google Scholar 

  20. H. Simonis and T. Corenlissens. Modelling Producer/Consumer Constraints. Technical Report COSY/TR/94-2, COSYTEC SA, 1994.

    Google Scholar 

  21. R.H. Storer, S.D. Wu, and R. Vaccari. New Search Spaces for Sequencing Instances with Application to Job Shop Scheduling. Management Science, 38:1495–1509, 1992.

    Article  MATH  Google Scholar 

  22. The COSYTEC Team. CHIP V4.1 User Manuals, 1994.

    Google Scholar 

  23. J. Thornton and A. Sattar. Applied partial constraint satisfaction using weighted iterative repair. In Proceedings of the Tenth Australian Joint Conference on Artificial Intelligence, pages 57–66, 1997.

    Google Scholar 

  24. P. Van Hentenryck. Constraint Satisfaction in Logic Programming. The MIT Press, 1989.

    Google Scholar 

  25. J.P. Walser. Solving linear pseudo-boolean constraint problems with local search. In Proceedings of the Fourteenth National Conference on Artificial Intelligence, pages 269–274, 1997.

    Google Scholar 

  26. J.P. Walser, R. Iyer, and N. Venkatasubramanyan. An integer local search method with application to capacitated production planning. In Proceedings of the Fourteenth National Conference on Artificial Intelligence, 1998.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    J. H. M. Lee, H. F. Leung & H. W. Won

Authors
  1. J. H. M. Lee
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  2. H. F. Leung
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  3. H. W. Won
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Grigoris Antoniou John Slaney

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© 1998 Springer-Verlag Berlin Heidelberg

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Lee, J.H.M., Leung, H.F., Won, H.W. (1998). Performance of a comprehensive and efficient constraint library based on local search. In: Antoniou, G., Slaney, J. (eds) Advanced Topics in Artificial Intelligence. AI 1998. Lecture Notes in Computer Science, vol 1502. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095052

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  • DOI: https://doi.org/10.1007/BFb0095052

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65138-3

  • Online ISBN: 978-3-540-49561-1

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