Abstract
Given a maximal monotone operator T,we consider a certain ε-enlargement T ε, playing the role of the ε-subdifferential in nonsmooth optimization. We establish some theoretical properties of T ε, including a transportation formula, its Lipschitz continuity, and a result generalizing Brønsted & Rockafellar’s theorem. Then we make use of the ε-enlargement to define an algorithm for finding a zero of T.
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References
F. Bonnans, J.Ch. Gilbert, C.L. Lemaréchal and C.A. Sagastizabal. Optimisation Numérique, aspects théoriques et pratiques. Collection “Mathématiques et applications”, SMAI-Springer-Verlag, Berlin, 1997.
D.P. Bertsekas and S.K. Mitter. A descent numerical method for optimization problems with nondifferentiable cost functionals. SIAM Journal on Control, 11 (4): 637–652, 1973.
A. Brondsted and R.T. Rockafellar. On the subdifferentiability of convex functions. Proceedings of the American Mathematical Society, 16: 605611, 1965.
R.S. Burachik, A.N. Iusem, and B.F. Svaiter. Enlargements of maximal monotone operators with application to variational inequalities. Set Valued Analysis, 5: 159–180, 1997.
R.S. Burachik, C.A. Sagastizabal, and B. F. Svaiter. Bundle methods for maximal monotone operators. Submitted, 1997.
HUL93] J.-B. Hiriart-Urruty and C. Lemaréchal. Convex Analysis and Minimization Algorithms. Number 305–306 in Grund. der math. Wiss. Springer-Verlag, 1993. (two volumes).
A. N. Iusem. An iterative algorithm for the variational inequality problem. Computational and Applied Mathematics, 13: 103–114, 1994.
A. N. Iusem. and B.F. Svaiter. A variant of Korpolevich’s method for variational inequalities with a new search strategy. Optimization, 42: 309321, 1997.
K.C. Kiwiel. Proximity control in bundle methods for convex nondifferentiable minimization. Mathematical Programming, 46: 105–122, 1990.
Kon97] I.V. Konnov. A combined relaxation method for variational inequalities with nonlinear constraints. Mathematical Programming,1997. Accepted for publication.
G.M. Korpelevich. The extragradient method for finding saddle points and other problems. Ekonomika i Matematischeskie Metody, 12: 747–756, 1976.
C. Lemaréchal. Extensions diverses des méthodes de gradient et applications, 1980. Thèse d’Etat, Université de Paris I X.
C. Lemaréchal, A. Nemirovskii, and Yu. Nesterov. New variants of bundle methods. Mathematical Programming, 69: 111–148, 1995.
L.R. Lucambio Pérez. Iterative Algorithms for Nonsmooth Variational Inequalities, 1997. Ph.D. Thesis, Instituto de Matematica Pura e Aplicada, Rio de Janeiro, Brazil.
G.L. Minty. Monotone nonlinear operators in a Hilbert space. Duke Mathematical Journal, 29: 341–346, 1962.
J.J. Moreau. Proximité et dualité dans un espace hilbertien. Bulletin de la Société Mathématique de France, 93: 273–299, 1965.
E.A. Nurminski. E-subgradient mapping and the problem of convex optimization. Cybernetics, 21 (6): 796–800, 1986.
R.T. Rockafellar. Local boundedness of nonlinear monotone operators. Michigan Mathematical Journal, 16: 397–407, 1969.
SS96] M.V. Solodov and B.F. Svaiter. A new projection method for variational inequality problems. Technical Report B-109, IMPA, Brazil, 1996. SIAM Journal on Control and Optimization,submitted.
M.V. Solodov and B.F. Svaiter. A hybrid projection-proximal point algorithm. Technical Report B-115, IMPA, Brazil, 1997.
H. Schramm and J. Zowe. A version of the bundle idea for minimizing a nonsmooth function: conceptual idea, convergence analysis, numerical results. SIAM Journal on Optimization, 2 (1): 121–152, 1992.
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Burachik, R.S., Sagastizábal, C.A., Svaiter, B.F. (1998). ε-Enlargements of Maximal Monotone Operators: Theory and Applications. In: Fukushima, M., Qi, L. (eds) Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods. Applied Optimization, vol 22. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-6388-1_2
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DOI: https://doi.org/10.1007/978-1-4757-6388-1_2
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