کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
481436 | 1446141 | 2009 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Pattern search ranking and selection algorithms for mixed variable simulation-based optimization
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
The class of generalized pattern search (GPS) algorithms for mixed variable optimization is extended to problems with stochastic objective functions. Because random noise in the objective function makes it more difficult to compare trial points and ascertain which points are truly better than others, replications are needed to generate sufficient statistical power to draw conclusions. Rather than comparing pairs of points, the approach taken here augments pattern search with a ranking and selection (R&S) procedure, which allows for comparing many function values simultaneously. Asymptotic convergence for the algorithm is established, numerical issues are discussed, and performance of the algorithm is studied on a set of test problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 198, Issue 3, 1 November 2009, Pages 878–890
Journal: European Journal of Operational Research - Volume 198, Issue 3, 1 November 2009, Pages 878–890
نویسندگان
Todd A. Sriver, James W. Chrissis, Mark A. Abramson,