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A trust region-based approach to optimize triple response systems

机译:基于信任区域的方法来优化三重响应系统

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This article presents a new computing procedure for the global optimization of the triple response system (TRS) where the response functions are non-convex quadratics and the input factors satisfy a radial constrained region of interest. The TRS arising from response surface modelling can be approximated using a nonlinear mathematical program that considers one primary objective function and two secondary constraint functions. An optimization algorithm named the triple response surface algorithm (TRSALG) is proposed to determine the global optimum for the non-degenerate TRS. In TRSALG, the Lagrange multipliers of the secondary functions are determined using the Hooke-Jeeves search method and the Lagrange multiplier of the radial constraint is located using the trust region method within the global optimality space. The proposed algorithm is illustrated in terms of three examples appearing in the quality-control literature. The results of TRSALG compared to a gradient-based method are also presented.
机译:本文为三重响应系统(TRS)的全局优化提供了一种新的计算程序,其中响应函数为非凸二次方,输入因子满足径向受约束区域的要求。响应面建模产生的TRS可以使用考虑一个主要目标函数和两个次要约束函数的非线性数学程序来近似。提出了一种称为三重响应面算法(TRSALG)的优化算法来确定非简并TRS的全局最优。在TRSALG中,使用Hooke-Jeeves搜索方法确定次要函数的拉格朗日乘数,并使用信任区域方法在全局最优空间内确定径向约束的拉格朗日乘数。根据出现在质量控制文献中的三个示例来说明所提出的算法。还介绍了TRSALG与基于梯度的方法相比的结果。

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