期刊
SIAM JOURNAL ON OPTIMIZATION
卷 17, 期 2, 页码 606-619出版社
SIAM PUBLICATIONS
DOI: 10.1137/050638382
关键词
nonlinear programming; mesh adaptive direct search; derivative-free optimization; convergence analysis; second-order optimality conditions
A previous analysis of second-order behavior of generalized pattern search algorithms for unconstrained and linearly constrained minimization is extended to the more general class of mesh adaptive direct search ( MADS) algorithms for general constrained optimization. Because of the ability of MADS to generate an asymptotically dense set of search directions, we are able to establish reasonable conditions under which a subsequence of MADS iterates converges to a limit point satisfying second-order necessary or sufficient optimality conditions for general set-constrained optimization problems.
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