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An approximate bundle method for solving nonsmooth equilibrium problems

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Abstract

We present an approximate bundle method for solving nonsmooth equilibrium problems. An inexact cutting-plane linearization of the objective function is established at each iteration, which is actually an approximation produced by an oracle that gives inaccurate values for the functions and subgradients. The errors in function and subgradient evaluations are bounded and they need not vanish in the limit. A descent criterion adapting the setting of inexact oracles is put forward to measure the current descent behavior. The sequence generated by the algorithm converges to the approximately critical points of the equilibrium problem under proper assumptions. As a special illustration, the proposed algorithm is utilized to solve generalized variational inequality problems. The numerical experiments show that the algorithm is effective in solving nonsmooth equilibrium problems.

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References

  1. Bertsekas, D.P.: Nonlinear Programming, 2nd edn. Athena Scientific, Belmont (1999)

    MATH  Google Scholar 

  2. Bigi, G., Pappalardo, M., Passacantando, M.: Optimization tools for solving equilibrium problems with nonsmooth data. J. Optim. Theory Appl. 170(3), 887–905 (2016)

  3. Blum, E., Oettli, W.: From optimization and variational inequalities to equilibrium problems. Math. Stud. 63(1), 123–145 (1994)

    MathSciNet  MATH  Google Scholar 

  4. Correa, R., Lemaréchal, C.: Convergence of some algorithms for convex minimization. Math. Program. 62(1), 261–275 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  5. Emiel, G., Sagastizábal, C.: Incremental-like bundle methods with applications to energy planning. Comput. Optim. Appl. 46(2), 305–332 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  6. Han, D., Lo, H.K.: Two new self-adaptive projection methods for variational inequality problems. Comput. Math. Appl. 43(12), 1529–1537 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  7. Hare, W., Sagastizábal, C., Solodov, M.: A proximal bundle method for nonsmooth nonconvex functions with inexact information. Comput. Optim. Appl. 63(1), 1–28 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  8. Harker, P.T., Pang, J.S.: A damped-newton method for the linear complementarity problem. Lect. Appl. Math. 26(2), 265–284 (1990)

    MathSciNet  MATH  Google Scholar 

  9. Hintermüller, M.: A proximal bundle method based on approximate subgradients. Comput. Optim. Appl. 20(3), 245–266 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  10. Iusem, A.N., Sosa, W.: Iterative algorithms for equilibrium problems. J. Optim. 52(3), 301–316 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  11. Iusem, A.N., Sosa, W.: New existence results for equilibrium problems. Nonlinear Anal. Theory Methods Appl. 52(2), 621–635 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  12. Iusem, A.N., Sosa, W.: On the proximal point method for equilibrium problems in Hilbert spaces. J. Optim. 59(8), 1259–1274 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  13. Kiwiel, K.C.: An algorithm for nonsmooth convex minimization with errors. Math. Comput. 45(171), 173–180 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  14. Kiwiel, K.C.: A proximal bundle method with approximate subgradient linearizations. SIAM J. Optim. 16(4), 1007–1023 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  15. Kiwiel, K.C.: Bundle Methods for Convex Minimization with Partially Inexact Oracles. Technical Report, Systems Research Institute, Polish Academy of Sciences (April 2010)

  16. Konnov, I.V.: The application of a linearization method to solving nonsmooth equilibrium problems. Russ. Math. 40(12), 54–62 (1996)

    Google Scholar 

  17. Konnov, I.V.: Combined Relaxation Methods for Variational Inequalities. Springer, Berlin (2001)

    Book  MATH  Google Scholar 

  18. Li, X., Tomasgard, A., Barton, P.: Nonconvex generalized benders decomposition for stochastic separable mixed-integer nonlinear programs. J. Optim. Theory Appl. 151(3), 425–454 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  19. Li, X.B., Li, S.J., Chen, C.R.: Lipschitz continuity of an approximate solution mapping to equilibrium problems. Taiwan. J. Math. 16(3), 1027–1040 (2012)

    MathSciNet  MATH  Google Scholar 

  20. Lv, J., Pang, L.P., Wang, J.H.: Special backtracking proximal bundle method for nonconvex maximum eigenvalue optimization. Appl. Math. Comput. 265, 635–651 (2015)

    MathSciNet  Google Scholar 

  21. Malitsky, Y.: Projected reflected gradient methods for monotone variational inequalities. SIAM J. Optim. 25(1), 502–520 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  22. Mordukhovich, B.S., Panicucci, B., Pappalardo, M., Passacantando, M.: Hybrid proximal methods for equilibrium problems. Optim. Lett. 6(7), 1535–1550 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  23. Muu, L.D., Nguyen, V.H., Quy, N.V.: On Nash–Cournot oligopolistic market equilibrium models with concave cost function. J. Glob. Optim. 41(3), 351–364 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  24. Nguyen, T.T., Strodiot, J.J., Nguyen, V.H.: A bundle method for solving equilibrium problems. Math. Program. Ser. B 116(1), 529–552 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  25. Oliveira, W., Sagastizabal, C., Scheimberg, S.: Inexact bundle methods for two-stage stochastic programming. SIAM. J. Optim. 21(2), 517–544 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  26. Pang, L.P., Lv, J., Wang, J.H.: Constrained incremental bundle method with partial inexact oracle for nonsmooth convex semi-infinite programming problems. Comput. Optim. Appl. 64(2), 433–465 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  27. Salmon, G., Strodiot, J.J., Nguyen, V.H.: A bundle method for solving variational inequalities. SIAM J. Optim. 14(3), 869–893 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  28. Santos, P., Scheimberg, S.: An inexact subgradient algorithm for equilibrium problems. Comput. Appl. Math. 30(1), 91–107 (2011)

    MathSciNet  MATH  Google Scholar 

  29. Shen, J., Pang, L.P.: A bundle-type auxiliary problem method for solving generalized variational-like inequalities. Comput. Math. Appl. 55(12), 2993–2998 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  30. Shen, J., Pang, L.P.: An approximate bundle method for solving variational inequalities. Commun. Optim. Theory 1, 1–18 (2012)

    Google Scholar 

  31. Solodov, M.V.: On approximations with finite precision in bundle methods for nonsmooth optimization. J. Optim. Theory Appl. 119(1), 151–165 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  32. Sun, D.F.: A new step-size skill for solving a class of nonlinear projection equations. J. Comput. Math. 13(4), 357–368 (1995)

    MathSciNet  MATH  Google Scholar 

  33. Wang, Y.J., Xiu, N.H., Wang, C.Y.: A new version of extragradient method for variational inequality problems. Comput. Math. Appl. 42, 969–979 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  34. Xiao, B.C., Harker, P.T.: A nonsmooth Newton method for variational inequalities, II: numerical results. Math. Program. 65(1), 195–216 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  35. Yang, Y., Pang, L.P., Ma, X.F., Shen, J.: Constrained nonsmooth nonsmooth optimization via proximal bundle method. J. Optim. Theory Appl. 163, 900–925 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  36. Ye, M.L., He, Y.R.: A double projection method for solving variational inequalities without monotonicity. Comput. Optim. Appl. 60(1), 141–150 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  37. Zhu, D.L., Marcotte, P.: Co-coercivity and its role in the convergence of iterative schemes for solving variational inequalities. SIAM. J. Optim. 6(3), 714–726 (1996)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The authors thank two anonymous referees for a number of valuable and helpful suggestions.

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Correspondence to Li-Ping Pang.

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The research is partially supported by the Natural Science Foundation of China, Grants 11171049, 11301347 and 31271077.

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Meng, FY., Pang, LP., Lv, J. et al. An approximate bundle method for solving nonsmooth equilibrium problems. J Glob Optim 68, 537–562 (2017). https://doi.org/10.1007/s10898-016-0490-9

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