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Convexification of bilinear forms through non-symmetric lifting

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Abstract

We efficiently treat bilinear forms in the context of global optimization, by applying McCormick convexification and by extending an approach of Saxena et al. (Math Prog Ser B 124(1–2):383–411, 2010) for symmetric quadratic forms to bilinear forms. A key application of our work is in treating “structural convexity” in a symmetric quadratic form.

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References

  1. Al-Khayyal, A., Falk, J.E.: Jointly constrained biconvex programming. Math. Oper. Res. 8, 273–286 (1983)

    Article  MathSciNet  Google Scholar 

  2. Boland, N., Dey, S.S., Kalinowski, T., Molinaro, M., Rigterink, F.: Bounding the gap between the McCormick relaxation and the convex hull for bilinear functions. Math. Program. Ser. A 162, 523–535 (2017)

    Article  MathSciNet  Google Scholar 

  3. Brimberg, J., Hansen, P., Mladenović, N.: A note on reduction of quadratic and bilinear programs with equality constraints. J. Global Optim. 22(1–4), 39–47 (2002)

    Article  MathSciNet  Google Scholar 

  4. Caprara, A., Locatelli, M., Monaci, M.: Bidimensional packing by bilinear programming. In: Integer Programming and Combinatorial Optimization. Volume 3509 of Lecture Notes in Computer Science, pp. 377–391. Springer, Berlin (2005)

  5. Castro, P.M., Grossmann, I.E.: Optimality-based bound contraction with multiparametric disaggregation for the global optimization of mixed-integer bilinear problems. J. Global Optim. 59(2–3), 277–306 (2014)

    Article  MathSciNet  Google Scholar 

  6. Dey, Santanu S., Santana, Asteroide, Wang, Yang: New SOCP relaxation and branching rule for bipartite bilinear programs. Optim. Eng. 20, 307–336 (2019)

    Article  MathSciNet  Google Scholar 

  7. Fampa, M., Lee, J., Melo, W.: On global optimization with indefinite quadratics. EURO J. Comput. Optim. 5(3), 309–337 (2017)

    Article  MathSciNet  Google Scholar 

  8. Fuentes, V.K., Fampa, M., Lee, J.: Sparse pseudoinverses via LP and SDP relaxations of Moore–Penrose. In: Maturana, S. (ed.) Proceedings of the XVIII Latin-Iberoamerican Conference on Operations Research (CLAIO 2016), pp. 342–350. Instituto Chileno de Investigación Operativa (ICHIO) (2016)

  9. Günlük, O., Lee, J., Leung, J.: A polytope for a product of real linear functions in 0/1 variables. In: Lee, J., Leyffer, S. (eds.) Mixed Integer Nonlinear Programming Volume 154 of IMA Journal of Applied Mathematics, pp. 513–529. Springer, New York (2012)

    Chapter  Google Scholar 

  10. Gupte, A., Ahmed, S., Seok Cheon, M., Dey, S.: Solving mixed integer bilinear problems using MILP formulations. SIAM J. Optim. 23(2), 721–744 (2013)

    Article  MathSciNet  Google Scholar 

  11. Kolodziej, S., Castro, P.M., Grossmann, I.E.: Global optimization of bilinear programs with a multiparametric disaggregation technique. J. Glob. Optim. 57(4), 1039–1063 (2013)

    Article  MathSciNet  Google Scholar 

  12. Locatelli, M.: Polyhedral subdivisions and functional forms for the convex envelopes of bilinear, fractional and other bivariate functions over general polytopes. J. Glob. Optim. 66(4), 629–668 (2016)

    Article  MathSciNet  Google Scholar 

  13. Nahapetyan, A., Pardalos, P.M.: A bilinear relaxation based algorithm for concave piecewise linear network flow problems. J. Ind. Manag. Optim. 3(1), 71–85 (2007)

    MathSciNet  MATH  Google Scholar 

  14. Rebennack, S., Nahapetyan, A., Pardalos, P.M.: Bilinear modeling solution approach for fixed charge network flow problems. Optim. Lett. 3(3), 347–355 (2009)

    Article  MathSciNet  Google Scholar 

  15. Ruiz, J.P., Grossmann, I.E.: Exploiting vector space properties to strengthen the relaxation of bilinear programs arising in the global optimization of process networks. Optim. Lett. 5(1), 1–11 (2011)

    Article  MathSciNet  Google Scholar 

  16. Saxena, A., Bonami, P., Lee, J.: Disjunctive cuts for non-convex mixed integer quadratically constrained programs. In: Integer Programming and Combinatorial Optimization, 13th International Conference, IPCO 2008, Bertinoro, Italy, May 26–28, 2008, Proceedings, pp. 17–33 (2008)

  17. Saxena, A., Bonami, P., Lee, J.: Convex relaxations of non-convex mixed integer quadratically constrained programs: extended formulations. Math. Program. Ser. B 124, 383–411 (2010)

    Article  MathSciNet  Google Scholar 

  18. Saxena, A., Bonami, P., Lee, J.: Convex relaxations of non-convex mixed integer quadratically constrained programs: projected formulations. Math. Program. Ser. B 130, 359–413 (2010)

    Article  MathSciNet  Google Scholar 

  19. Xia, Wei, Vera, Juan C., Zuluaga, Luis F.: Globally solving nonconvex quadratic programs via linear integer programming techniques. INFORMS J. Comput. 32(1), 40–56 (2020)

    Article  MathSciNet  Google Scholar 

  20. Zorn, K., Sahinidis, N.V.: Global optimization of general non-convex problems with intermediate bilinear substructures. Optim. Methods Softw. 29(3), 442–462 (2014)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

The authors are grateful to the anonymous referees for making several points which significantly improved the presentation.

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Correspondence to Jon Lee.

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M. Fampa was supported in part by CNPq Grant 303898/2016-0. J. Lee was supported in part by ONR Grant N00014-17-1-2296. Additionally, part of this work was done while J. Lee was visiting the Simons Institute for the Theory of Computing. It was partially supported by the DIMACS/Simons Collaboration on Bridging Continuous and Discrete Optimization through NSF Grant #CCF-1740425.

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Fampa, M., Lee, J. Convexification of bilinear forms through non-symmetric lifting. J Glob Optim 80, 287–305 (2021). https://doi.org/10.1007/s10898-020-00975-z

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