Skip to main content

Cliques for Multi-Term Linearization of 0–1 Multilinear Program for Boolean Logical Pattern Generation

  • Conference paper
  • First Online:
Optimization of Complex Systems: Theory, Models, Algorithms and Applications (WCGO 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 991))

Included in the following conference series:

Abstract

0–1 multilinear program (MP) holds a unifying theory to Boolean logical pattern generation. For a tighter polyhedral relaxation of MP, this note exploits cliques in the graph representation of data under analysis to generate valid inequalities for MP that subsume all previous results and, collectively, provide a much stronger relaxation of MP. A preliminary numerical study demonstrates strength and practical benefits of the new results.

\({}^{1}\)This work was supported by National Natural Science Foundation of China (Grant Number: 61806095.)

\({}^{2}\)Corresponding author. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant Number: 2017R1D1A1A02018729.)

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. IBM Corp.: IBM ILOG CPLEX Optimization Studio CPLEX User’s Manual Version 12 Release 8 (2017). https://www.ibm.com/support/knowledgecenter/SSSA5P_12.8.0/ilog.odms.studio.help/pdf/usrcplex.pdf. Accessed 12 Dec 2018

  2. Crama, Y.: Concave extensions for nonlinear 0–1 maximization problems. Math. Program. 61, 53–60 (1993)

    Google Scholar 

  3. Del Pia, A., Khajavirad, A.: A polyhedral study of binary polynomial programs. Math. Oper. Res. 42(2), 389–410 (2017)

    Google Scholar 

  4. Del Pia, A., Khajavirad, A.: The multilinear polytope for acyclic hypergraphs. SIAM J. Optim. 28(2), 1049–1076 (2018)

    Google Scholar 

  5. Fortet, R.: L’algèbre de boole dt ses applications en recherche opérationnelle. Cahiers du Centre d’Études de Recherche Opérationnelle 1(4), 5–36 (1959)

    Google Scholar 

  6. Fortet, R.: Applications de l’algèbre de boole en recherche opérationnelle. Revue Française d’Informatique et de Recherche Opérationnelle 4(14), 17–25 (1960)

    Google Scholar 

  7. Glover, F., Woolsey, E.: Converting the 0–1 polynomial programming problem to a 0–1 linear program. Oper. Res. 12(1), 180–182 (1974)

    Google Scholar 

  8. Granot, F., Hammer, P.: On the use of boolean functions in 0–1 programming. Methods Oper. Res. 12, 154–184 (1971)

    Google Scholar 

  9. Lichman, M.: UCI Machine Learning Repository (2013). http://archive.ics.uci.edu/ml. Accessed 12 Dec 2018

  10. McCormick, G.: Computability of global solutions to factorable nonconvex programs: part I-convex underestimating problems. Math. Program. 10, 147–175 (1976)

    Google Scholar 

  11. Moon, J.W., Moser, L.: On cliques in graphs. Isr. J. Math. 3(1), 23–28 (1965)

    Google Scholar 

  12. Rikun, A.: A convex envelope formula for multilinear functions. J. Glob. Optim. 10, 425–437 (1997)

    Google Scholar 

  13. Ryoo, H.S., Jang, I.Y.: MILP approach to pattern generation in logical analysis of data. Discret. Appl. Math. 157, 749–761 (2009)

    Google Scholar 

  14. Ryoo, H.S., Sahinidis, N.: Analysis of bounds for multilinear functions. J. Glob. Optim. 19(4), 403–424 (2001)

    Google Scholar 

  15. Yan, K., Ryoo, H.S.: 0–1 multilinear programming as a unifying theory for LAD pattern generation. Discret. Appl. Math. 218, 21–39 (2017)

    Google Scholar 

  16. Yan, K., Ryoo, H.S.: Strong valid inequalities for Boolean logical pattern generation. J. Glob. Optim. 69(1), 183–230 (2017)

    Google Scholar 

  17. Yan, K., Ryoo, H.S.: A multi-term, polyhedral relaxation of a 0-1 multilinear function for Boolean logical pattern generation. J. Glob. Optim. https://doi.org/10.1007/s10898-018-0680-8. (In press)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hong Seo Ryoo .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yan, K., Ryoo, H.S. (2020). Cliques for Multi-Term Linearization of 0–1 Multilinear Program for Boolean Logical Pattern Generation. In: Le Thi, H., Le, H., Pham Dinh, T. (eds) Optimization of Complex Systems: Theory, Models, Algorithms and Applications. WCGO 2019. Advances in Intelligent Systems and Computing, vol 991. Springer, Cham. https://doi.org/10.1007/978-3-030-21803-4_38

Download citation

Publish with us

Policies and ethics