Journal
SIAM JOURNAL ON OPTIMIZATION
Volume 26, Issue 2, Pages 951-967Publisher
SIAM PUBLICATIONS
DOI: 10.1137/15M1031631
Keywords
nonlinear programming; complexity; approximate KKT point
Categories
Funding
- Brazilian agency FAPESP [2010/10133-0, 2013/03447-6, 2013/05475-7, 2013/07375-0, 2013/23494-9]
- Brazilian agency CNPq [304032/2010-7, 309517/2014-1, 303750/2014-6, 490326/2013-7]
- Belgian National Fund for Scientific Research (FNRS)
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The evaluation complexity of general nonlinear, possibly nonconvex, constrained optimization is analyzed. It is shown that, under suitable smoothness conditions, an epsilon-approximate first-order critical point of the problem can be computed in order O(epsilon(1-2(p+1)/p)) evaluations of the problem's functions and their first p derivatives. This is achieved by using a two-phase algorithm inspired by Cartis, Gould, and Toint [SIAM J. Optim., 21 (2011), pp. 1721-1739; SIAM J. Optim., 23 (2013), pp. 1553-1574]. It is also shown that strong guarantees (in terms of handling degeneracies) on the possible limit points of the sequence of iterates generated by this algorithm can be obtained at the cost of increased complexity. At variance with previous results, the epsilon-approximate first-order criticality is defined by satisfying a version of the KKT conditions with an accuracy that does not depend on the size of the Lagrange multipliers.
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