Second Order Behavior of Pattern Search Algorithms
| dc.contributor.author | Abramson, Mark A. | en_US |
| dc.date.accessioned | 2018-06-18T17:52:01Z | en_US |
| dc.date.available | 2018-06-18T17:52:01Z | en_US |
| dc.date.issued | 2004-01 | en_US |
| dc.date.note | January 2004 | en_US |
| dc.description.abstract | Previous analyses of pattern search algorithms for unconstrained and linearly constrained minimization have focused on proving convergence of a subsequence of iterates to a limit point satisfying either directional or first-order necessary conditions for optimality, depending on the smoothness of the objective function in a neighborhood of the limit point. Even though pattern search methods require no derivative information, we are able to prove some limited directional second-order results. Although not as strong as classical second-order necessary conditions, these results are stronger than the first order conditions that many gradient-based methods satisfy. Under fairly mild conditions, we can eliminate from consideration all strict local maximizers and an entire class of saddle points. | en_US |
| dc.format.extent | 16 pp | en_US |
| dc.identifier.citation | Abramson, Mark A.. "Second Order Behavior of Pattern Search Algorithms." (2004) <a href="https://hdl.handle.net/1911/102016">https://hdl.handle.net/1911/102016</a>. | en_US |
| dc.identifier.digital | TR04-03 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/102016 | en_US |
| dc.language.iso | eng | en_US |
| dc.title | Second Order Behavior of Pattern Search Algorithms | en_US |
| dc.type | Technical report | en_US |
| dc.type.dcmi | Text | en_US |
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