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Derivative-free optimal experimental design
Chemical Engineering Science, 2008We present a new derivative-free method for the calculation of a planned experiment's information content in optimal experimental design. We will prove that our new approach yields the same result as a calculation with the Fisher information matrix if the mathematical model is linear in the model parameters.
T. Heine, M. Kawohl, R. King
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Openly revisiting derivative-free optimization
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019This paper surveys and compares a wide range of derivative-free optimization algorithms in an open source context. We also propose a genetic variant of differential evolution, an adaptation of population control for the multimodal noise-free case, new multiscale deceptive functions, and as a contribution to the debate on genetic crossovers, a test ...
Jeremy Rapin +6 more
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2011
In many engineering applications it is common to find optimization problems where the cost function and/or constraints require complex simulations. Though it is often, but not always, theoretically possible in these cases to extract derivative information efficiently, the associated implementation procedures are typically non-trivial and time-consuming
Oliver Kramer +2 more
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In many engineering applications it is common to find optimization problems where the cost function and/or constraints require complex simulations. Though it is often, but not always, theoretically possible in these cases to extract derivative information efficiently, the associated implementation procedures are typically non-trivial and time-consuming
Oliver Kramer +2 more
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Derivative-Free Optimization via Classification
Proceedings of the AAAI Conference on Artificial Intelligence, 2016Many randomized heuristic derivative-free optimization methods share a framework that iteratively learns a model for promising search areas and samples solutions from the model. This paper studies a particular setting of such framework, where the model is implemented by a classification model discriminating good solutions from bad ones.
Yang Yu, Hong Qian, Yi-Qi Hu
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Derivative Free Optimization in Higher Dimension
International Transactions in Operational Research, 2001Non‐linear optimizations that do not require explicit or implicit derivative information of an objective function are an alternate search strategy when the derivative of the objective function is not available. In factorial design, the number of trials for experimental identification method in Em is about (m+ 1).
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Objective-derivative-free methods for constrained optimization
Mathematical Programming, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
LUCIDI, Stefano, M. Sciandrone, P. Seng
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Derivative-Free Optimization Via Proximal Point Methods
Journal of Optimization Theory and Applications, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hare, W. L., Lucet, Y.
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Derivative-Free Robust Optimization for Circuit Design
Journal of Optimization Theory and Applications, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Angelo Ciccazzo +4 more
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Derivative free optimization methods for optimizing stirrer configurations
European Journal of Operational Research, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Uğur, Ömür +3 more
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Illumination source optimization in optical lithography via derivative-free optimization
Journal of the Optical Society of America A, 2014Illumination source optimization (SO) in optical lithography is generally performed under a simulation model that does not consider critical effects such as the vectorial nature of light and mask topography. When a numerical aperture becomes large and the critical dimension reaches subwavelength, the prediction of this model generally fails; therefore,
Liu, S, Lam, EYM, WU, X, Lyu, W
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