Analysis of generalized pattern searches

被引:716
作者
Audet, C
Dennis, JE
机构
[1] Ecole Polytech, Dept Math & Genie Ind, Montreal, PQ H3C 3A7, Canada
[2] Rice Univ, Dept Computat & Appl Math, Houston, TX 77005 USA
关键词
pattern search algorithm; linearly constrained optimization; surrogate-based optimization; nonsmooth optimization; derivative-free convergence analysis;
D O I
10.1137/S1052623400378742
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper contains a new convergence analysis for the Lewis and Torczon generalized pattern search (GPS) class of methods for unconstrained and linearly constrained optimization. This analysis is motivated by a desire to understand the successful behavior of the algorithm under hypotheses that are satisfied by many practical problems. Specifically, even if the objective function is discontinuous or extended-valued, the methods find a limit point with some minimizing properties. Simple examples show that the strength of the optimality conditions at a limit point depends not only on the algorithm, but also on the directions it uses and on the smoothness of the objective at the limit point in question. The contribution of this paper is to provide a simple convergence analysis that supplies detail about the relation of optimality conditions to objective smoothness properties and to the de ning directions for the algorithm, and it gives previous results as corollaries.
引用
收藏
页码:889 / 903
页数:15
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