MANAGING APPROXIMATION MODELS IN OPTIMIZATION

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Reduced-basis techniques for rapid reliable optimization of systems described by affinely parametrized coercive elliptic partial differential equations (2007, background): “Current research thus focuses on decreasing the computational cost (Alexandrov and Dennis 1995; Dennis and Torczon 1997; Patera et al. 2000; Ravindran 1998) and, relatedly, increasing the fidelity and reliability of optimization procedures (Byrd et al. 1999 ;F orsgren et al.2002; Forsgren and Gill”
Review of Metamodeling Techniques in Support of Engineering Design Optimization (2007, methodology): “[115], samples were generated iteratively to update the approximation to maintain the model accuracy.”
A Gaussian Process Surrogate Model Assisted Evolutionary Algorithm for Medium Scale Expensive Optimization Problems (2014, methodology): “In GPEME, we only select the point with the best LCB value for exact function evaluation based on the obtained ranking.”