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A New Algorithm for Linear and Integer Feasibility in Horn Constraints

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6697))

Abstract

In this paper, we detail a new algorithm for the problem of checking linear and integer feasibility of a system of Horn constraints. For certain special cases, the new algorithm is faster than the “Lifting Algorithm” described in [1]. Moreover, the new approach is based on different ideas and in fact exploits several properties of Horn constraint systems (HCS) which are not known to be part of the literature. In the case of constraints of bounded width (corresponding to “loosely coupled” systems), our algorithm can be modified to run in \(O(n^3 + m \cdot n + \frac{m\cdot n^2}{\log (\max (m,n))})\) time. Our main result establishes that checking the feasibility of an HCS can be reduced to three subproblems: negative-cost cycle detection in networks (NCCD), matrix-vector multiplication (MV), and the conversion of an HCS to a non-redundant set of difference constraints (H2D). The MV and NCCD problems have been extremely well-studied, and specialized, fast algorithms exist for relevant special cases. We have identified a new problem, H2D, which warrants future research, since improved algorithms for H2D could be implemented in our algorithm to decrease the running time.

This research was supported in part by the National Science Foundation through Award CCF-0827397.

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References

  1. Chandrasekaran, R., Subramani, K.: A combinatorial algorithm for horn programs. In: Dong, Y., Du, D.-Z., Ibarra, O. (eds.) ISAAC 2009. LNCS, vol. 5878, pp. 1114–1123. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  2. Nemhauser, G.L., Wolsey, L.A.: Integer and Combinatorial Optimization. John Wiley & Sons, New York (1999)

    MATH  Google Scholar 

  3. Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms. MIT Press, Cambridge (2001)

    MATH  Google Scholar 

  4. Lever, J., Wallace, M., Richards, B.: Constraint logic programming for scheduling and planning. British Telecom Technology Journal 13, 73–80 (1995)

    Google Scholar 

  5. Truemper, K.: Personal communication (2003)

    Google Scholar 

  6. Miné, A.: The Octagon Abstract Domain. Higher-Order and Symbolic Computation 19, 31–100 (2006)

    Article  Google Scholar 

  7. Cousot, P., Cousot, R.: Abstract interpretation: A unified lattice model for static analysis of programs by construction or approximation of fixpoints. In: POPL, pp. 238–252 (1977)

    Google Scholar 

  8. Homer, S., Selman, A.L.: Computability and Complexity Theory. Springer, Heidelberg (2001)

    Book  Google Scholar 

  9. de Moura, L., Owre, S., Rueß, H., Rushby, J., Shankar, N.: The ICS decision procedures for embedded deduction. In: Basin, D., Rusinowitch, M. (eds.) IJCAR 2004. LNCS (LNAI), vol. 3097, pp. 218–222. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  10. Ford, J., Shankar, N.: Formal verification of a combination decision procedure. In: CADE, pp. 347–362 (2002)

    Google Scholar 

  11. Duterre, B., de Moura, L.: The yices smt solver. Technical report, SRI International (2006)

    Google Scholar 

  12. Harvey, W., Stuckey, P.J.: A unit two variable per inequality integer constraint solver for constraint logic programming. In: Proceedings of the 20th Australasian Computer Science Conference, pp. 102–111 (1997)

    Google Scholar 

  13. Lewis, H.R., Papadimitriou, C.H.: Symmetric space-bounded computation. Theor. Comput. Sci. 19, 161–187 (1982)

    Article  MathSciNet  Google Scholar 

  14. Cousot, P., Halbwachs, N.: Automatic discovery of linear restraints among variables of a program. In: Proceedings of the 5th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages, POPL 1978, pp. 84–96. ACM, New York (1978)

    Google Scholar 

  15. Jeavons, P.G., Cooper, M.C.: Tractable constraints on ordered domains. Artif. Intell. 79, 327–339 (1995)

    Article  MathSciNet  Google Scholar 

  16. van Maaren, H., Dang, C.: Simplicial pivoting algorithms for a tractable class of integer programs. J. Comb. Optim. 6, 133–142 (2002)

    Article  MathSciNet  Google Scholar 

  17. Tardos, E.: A strongly polynomial algorithm to solve combinatorial linear programs. Oper. Res. 34, 250–256 (1986)

    Article  MathSciNet  Google Scholar 

  18. Goldberg, A.V.: Scaling algorithms for the shortest paths problem. SIAM Journal on Computing 24, 494–504 (1995)

    Article  MathSciNet  Google Scholar 

  19. Liberty, E., Zucker, S.W.: The mailman algorithm: A note on matrix–vector multiplication. Inf. Process. Lett. 109, 179–182 (2009)

    Article  MathSciNet  Google Scholar 

  20. Seshia, S.A., Subramani, K., Bryant, R.E.: On solving boolean combinations of UTVPI constraints. Journal on Satisfiability, Boolean Modeling and Computation 3, 67–90 (2007)

    Article  MathSciNet  Google Scholar 

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Subramani, K., Worthington, J. (2011). A New Algorithm for Linear and Integer Feasibility in Horn Constraints. In: Achterberg, T., Beck, J.C. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2011. Lecture Notes in Computer Science, vol 6697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21311-3_21

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  • DOI: https://doi.org/10.1007/978-3-642-21311-3_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21310-6

  • Online ISBN: 978-3-642-21311-3

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