کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4959557 | 1445954 | 2017 | 35 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparison of Kriging-based algorithms for simulation optimization with heterogeneous noise
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In this article we investigate the unconstrained optimization (minimization) of the performance of a system that is modeled through a discrete-event simulation. In recent years, several algorithms have been proposed which extend the traditional Kriging-based simulation optimization algorithms (assuming deterministic outputs) to problems with noise. Our objective in this paper is to compare the relative performance of a number of these algorithms on a set of well-known analytical test functions, assuming different patterns of heterogeneous noise. We also apply the algorithms to a popular inventory test problem. The conclusions and insights obtained may serve as a useful guideline for researchers aiming to apply Kriging-based algorithms to solve engineering and/or business problems, and may be useful in the development of future algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 261, Issue 1, 16 August 2017, Pages 279-301
Journal: European Journal of Operational Research - Volume 261, Issue 1, 16 August 2017, Pages 279-301
نویسندگان
Hamed Jalali, Inneke Van Nieuwenhuyse, Victor Picheny,