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Projection Heuristics for Binary Branchings Between Sum and Product

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12831))

Abstract

We consider a fundamental problem in the theory of branching heuristics for tree-based solvers, applicable e.g. to SAT, #SAT, CSP, #CSP. Such tree-based solvers are used as the cubing-part in the Cube-and-Conquer paradigm, and are thus of renewed interest for general (#)SAT solving. These solvers build at least implicitly a branching (backtracking) tree, with the goal to minimise tree-size. The heuristics are based on evaluating the progress made in a transition from an instance F to some “simplified” \(F'\) by a distance \(d(F,F')\) (the bigger the more progress). When a branching \((F'_1, \dots , F'_k)\) is to be chosen for F, for each possibility we consider its branching tuple t given by \(t_i = d(F, F'_i)\), project it to a single number \(\pi (t)\), and choose a branching with minimal \(\pi (t)\). This paper investigates the choices for \(\pi (t)\), in a theoretical framework. The general theory is reviewed, together with the theoretical result on the “canonical projection” \(\pi (t) = \tau (t)\). Focusing then on binary branchings (\(k=2\), \(t = (a,b)\)), we analyse the asymptotics of \(\tau (a,b)\), and reflect on the whole possible range of binary projections, arriving at first practical possibilities for dynamic heuristics.

O. Kullmann and O. Zaikin—Supported by EPSRC grant EP/S015523/1.

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References

  1. Ahmed, T., Kullmann, O., Snevily, H.: On the van der Waerden numbers \(\rm w(2; 3, t)\). Disc. Appl. Math. 174, 27–51 (2014). https://doi.org/10.1016/j.dam.2014.05.007

    Article  MATH  Google Scholar 

  2. Anderson, D., Bodic, P.L., Morgan, K.: Further results on an abstract model for branching and its application to mixed integer programming. Math. Program. (2020). https://doi.org/10.1007/s10107-020-01556-4

  3. Biere, A., Heule, M.J.H., van Maaren, H., Walsh, T. (eds.): Handbook of Satisfiability, volume 185 of Frontiers in Artificial Intelligence and Applications. IOS Press (2009)

    Google Scholar 

  4. Bodic, P.L., Nemhauser, G.L.: An abstract model for branching and its application to mixed integer programming. Math. Program. 166(1–2), 369–405 (2017). https://doi.org/10.1007/s10107-016-1101-8

    Article  MathSciNet  MATH  Google Scholar 

  5. Bulhões, T., Sadykov, R., Uchoa, E.: A branch-and-price algorithm for the minimum latency problem. Comput. Oper. Res. 93, 66–78 (2018). https://doi.org/10.1016/j.cor.2018.01.016

    Article  MathSciNet  MATH  Google Scholar 

  6. Davis, M., Logemann, G., Loveland, D.: A machine program for theorem-proving. Commun ACM 5(7), 394–397 (1962). https://doi.org/10.1145/368273.368557

    Article  MathSciNet  MATH  Google Scholar 

  7. Fomin, F.V., Kratsch, D.: Exact Exponential Algorithms. TTCSAES, Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16533-7

    Book  MATH  Google Scholar 

  8. Golovnev, A., Kulikov, A.S., Smal, A.V., Tamaki, S.: Gate elimination: circuit size lower bounds and #SAT upper bounds. Theor. Comput. Sci. 719, 46–63 (2018). https://doi.org/10.1016/j.tcs.2017.11.008

    Article  MathSciNet  MATH  Google Scholar 

  9. Marijn J. H. Heule and Hans van Maaren. Look-ahead based SAT solvers. In Biere et al. [3], chapter 5, pages 155–184. https://doi.org/10.3233/978-1-58603-929-5-155

  10. Heule, M.J.H., Kullmann, O.: The science of brute force. Commun. ACM 60(8), 25–34 (2017). https://doi.org/10.1145/3107239

    Article  Google Scholar 

  11. Heule, M.J.H., Kullmann, O., Biere, A.: Cube-and-conquer for satisfiability. In: Handbook of Parallel Constraint Reasoning, pp. 31–59. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-63516-3_2

    Chapter  Google Scholar 

  12. Hoorfar, A., Hassani, M.: Inequalities on the Lambert \({W}\) function and hyperpower function. J. Inequalities Pure Appl. Math. 9(2), 1–5 (2008). https://www.emis.de/journals/JIPAM/article983.html

  13. Pinelis, I.: A certain generalisation of the golden ratio. MathOverflow. https://mathoverflow.net/users/36721/iosif pinelis, https://mathoverflow.net/q/320595

  14. Knuth, D.E.: The Art of Computer Programming, Satisfiability (Fascicle 6), vol. 4. Addison-Wesley, Boston (2015). ISBN-13 978–0134397603

    Google Scholar 

  15. Kullmann, O.: Obere und untere Schranken für die Komplexität von aussagenlogischen Resolutionsbeweisen und Klassen von SAT-Algorithmen. Master’s thesis, Johann Wolfgang Goethe-Universität Frankfurt am Main (1992). (Upper and lower bounds for the complexity of propositional resolution proofs and classes of SAT algorithms (in German); Diplomarbeit am Fachbereich Mathematik)

    Google Scholar 

  16. Kullmann, O.: Fundaments of branching heuristics. In: Biere et al. [3], chap. 7, pp. 205–244 (2007). https://doi.org/10.3233/978-1-58603-929-5-205

  17. Marques-Silva, J., Lynce, I., Malik, S.: Conflict-driven clause learning SAT solvers. In: Biere et al. [3], chap. 4, pp. 131–153 (1996). https://doi.org/10.3233/978-1-58603-929-5-131

  18. Olver, F.W.J., Lozier, D.W., Boisvert, R.F., Clark, C.W. (eds.): NIST Handbook of Mathematical Functions. NIST and Cambridge University Press, Cambridge (2010). ISBN 978-0-521-19225-5

    Google Scholar 

  19. Pecin, D., Pessoa, A.A., Poggi, M., Uchoa, E.: Improved branch-cut-and-price for capacitated vehicle routing. Math. Program. Comput. 9(1), 61–100 (2017). https://doi.org/10.1007/s12532-016-0108-8

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Oliver Kullmann or Oleg Zaikin .

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Kullmann, O., Zaikin, O. (2021). Projection Heuristics for Binary Branchings Between Sum and Product. In: Li, CM., Manyà, F. (eds) Theory and Applications of Satisfiability Testing – SAT 2021. SAT 2021. Lecture Notes in Computer Science(), vol 12831. Springer, Cham. https://doi.org/10.1007/978-3-030-80223-3_21

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  • DOI: https://doi.org/10.1007/978-3-030-80223-3_21

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