Response surface methodology for constrained simulation optimization: An overview
Response surface methodology for constrained simulation optimization: An overview
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DOI：
10.1016/j.simpat.2007.10.001
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发表时间：
2008-01-01
影响因子：
4.2
通讯作者：
Kleijnen, Jack P. C.
中科院分区：
文献类型：
--
作者：
Kleijnen, Jack P. C.
本文对Box和Wilson的响应面法（RSM）进行了扩展，提出了广义响应面法（GRSM）。GRSM允许多个随机响应，选择一个响应作为目标，其他响应作为约束变量。GRSM和RSM都估计局部梯度以搜索最优值。这些梯度基于局部一阶多项式近似。GRSM将这些梯度与数学规划结果相结合，以估计比RSM使用的最陡上升方向更好的搜索方向。此外，这些梯度用于自举过程中，用于测试估计的解决方案是否确实是最优的。本文的重点是模拟（而不是真实的）系统的优化。(c)2007 Elsevier B.V.保留所有权利。
This article summarizes 'generalized response surface methodology' (GRSM), extending Box and Wilson's 'response surface methodology' (RSM). GRSM allows multiple random responses, selecting one response as goal and the other responses as constrained variables. Both GRSM and RSM estimate local gradients to search for the optimum. These gradients are based on local first-order polynomial approximations. GRSM combines these gradients with Mathematical Programming findings to estimate a better search direction than the steepest ascent direction used by RSM. Moreover, these gradients are used in a bootstrap procedure for testing whether the estimated solution is indeed optimal. The focus of this paper is the optimization of simulated (not real) systems. (c) 2007 Elsevier B.V. All rights reserved.