Convergence of mesh adaptive direct search to second-order stationary points

被引:64
作者
Abramson, Mark A.
Audet, Charles
机构
[1] USAF, Dept Math & Stat, Inst Technol, Wright Patterson AFB, OH 45433 USA
[2] Ecole Polytech, Dept Math & Genie Ind, Montreal, PQ H3C 3A7, Canada
[3] GERAD, Montreal, PQ H3C 3A7, Canada
关键词
nonlinear programming; mesh adaptive direct search; derivative-free optimization; convergence analysis; second-order optimality conditions;
D O I
10.1137/050638382
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
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.
引用
收藏
页码:606 / 619
页数:14
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