Abstract
In this paper, we study linear constraint systems in which each constraint is a fractional Horn constraint. A constraint is fractional horn, if it can be written in the form: \(\sum _{i=1}^{n}a_{i}\cdot x_{i}\ge c\), where the \(a_{i}\) and c are integral, and at most one of the \(a_{i}>0\) and all negative \(a_{i}\) are equal to \(-1\). A conjunction of fractional Horn constraints is called a Fractional Horn Systems (FHS). FHSs generalize a number of specialized constraint systems such as Difference Constraint Systems and Horn Constraint Systems. We show that the problem of checking linear feasibility in these systems is in P, whereas the problem of checking lattice point feasibility is NP-complete. We then study a sub-class of fractional horn systems called Binary fractional horn systems (BFHS) in which each constraint has at most two non-zero coefficients with at most one being positive. In this case, we show that the problem of lattice point feasibility is in P.
P. Wojciechowski—This research was supported in part by the National Science Foundation through Award CCF-1305054.
K. Subramani—This work was supported by the Air Force Research Laboratory under US Air Force contract FA8750-16-3-6003. The views expressed are those of the authors and do not reflect the official policy or position of the Department of Defense or the U.S. Government.
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References
Bagnara, R., Hill, P.M., Zaffanella, E.: Weakly-relational shapes for numeric abstractions: improved algorithms and proofs of correctness. Formal Methods Syst. Des. 35(3), 279–323 (2009)
Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms. MIT Press, Cambridge (2001)
Chandrasekaran, R., Subramani, K.: A combinatorial algorithm for horn programs. Discrete Optim. 10, 85–101 (2013)
Hochbaum, D.S., (Seffi) Naor, J.: Simple and fast algorithms for linear and integer programs with two variables per inequality. SIAM J. Comput. 23(6), 1179–1192 (1994)
Jaffar, J., Maher, M.J., Stuckey, P.J., Yap, R.H.C.: Beyond finite domains. In: Borning, A. (ed.) PPCP 1994. LNCS, vol. 874, pp. 86–94. Springer, Heidelberg (1994). doi:10.1007/3-540-58601-6_92
Lagarias, J.C.: The computational complexity of simultaneous Diophantine approximation problems. SIAM J. Comput. 14(1), 196–209 (1985)
Lahiri, S.K., Musuvathi, M.: An efficient decision procedure for UTVPI constraints. In: Gramlich, B. (ed.) FroCoS 2005. LNCS (LNAI), vol. 3717, pp. 168–183. Springer, Heidelberg (2005). doi:10.1007/11559306_9
Schrijver, A.: Theory of Linear and Integer Programming. Wiley, New York (1987)
Veinott, A.F.: Representation of general and polyhedral subsemilattices and sublattices of product spaces. Linear Algebra Appl. 114(115), 681–704 (1989)
Veinott, A.F., LiCalzi, M.: Subextremal functions and lattice programming, July 1992. Unpublished Manuscript
Veinott, A.F., Wagner, H.M.: Optimal capacity scheduing: Parts i and ii. Oper. Res. 10, 518–547 (1962)
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Wojciechowski, P., Chandrasekaran, R., Subramani, K. (2017). On a Generalization of Horn Constraint Systems. In: Weil, P. (eds) Computer Science – Theory and Applications. CSR 2017. Lecture Notes in Computer Science(), vol 10304. Springer, Cham. https://doi.org/10.1007/978-3-319-58747-9_28
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