An Efficient Sequential Optimization Approach Based on the Multivariate Expected Improvement Criterion

2007 ◽  
Vol 19 (4) ◽  
pp. 267-280 ◽  
Author(s):  
Nadine Henkenjohann ◽  
Joachim Kunert
2017 ◽  
Author(s):  
Guillaume Pirot ◽  
Tipaluck Krityakierne ◽  
David Ginsbourger ◽  
Philippe Renard

Abstract. A Bayesian optimization approach to localize a contaminant source is proposed. The localization problem is illustrated with two 2D synthetic cases which display sharp transmissivity contrasts and specific connectivity patterns. These cases generate highly non-linear objective functions that present multiple local minima. A derivative-free global optimization algorithm relying on a Gaussian Process model and on the Expected Improvement criterion is used to efficiently localize the minimum of the objective function which identifies the contaminant source. In addition, the generated objective functions are made available as a benchmark to further allow the comparison of optimization algorithms on functions characterized by multiple minima and inspired by concrete field applications.


2016 ◽  
Vol 68 (3) ◽  
pp. 641-662 ◽  
Author(s):  
Dawei Zhan ◽  
Jiachang Qian ◽  
Yuansheng Cheng

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Hongxia Li ◽  
Yihao Zhang ◽  
Bao Zhu ◽  
Jinying Wu ◽  
Xicheng Wang

The drug release analysis and optimization for drug-eluting stents in the arterial wall are studied, which involves mechanics, fluid dynamics, and mass transfer processes and design optimization. The Finite Element Method (FEM) is used to analyze the process of drug release in the vessels for drug-eluting stents (DES). Kriging surrogate model is used to build an approximate function relationship between the drug distribution and the coating parameters, replacing the expensive FEM reanalysis of drug release for DES in the optimization process. The diffusion coefficients and the coating thickness are selected as design variables. An adaptive optimization approach based on kriging surrogate model is proposed to optimize the lifetime of the drug in artery wall. The adaptive process is implemented by an infilling sampling criterion named Expected Improvement (EI), which is used to balance local and global search and tends to find the global optimal design. The effect of coating diffusivity and thickness on the drug release process for a typical DES is analyzed by means of FEM. An implementation of the optimization method for the drug release is then discussed. The results demonstrate that the optimized design can efficiently improve the efficacy of drug deposition and penetration into the arterial walls.


2019 ◽  
Vol 471 ◽  
pp. 80-96 ◽  
Author(s):  
Ruwang Jiao ◽  
Sanyou Zeng ◽  
Changhe Li ◽  
Yuhong Jiang ◽  
Yaochu Jin

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