Benchmarking Five Global Optimization Approaches for Nano-optical Shape Optimization and Parameter Reconstruction
نویسندگان
چکیده
منابع مشابه
Benchmarking Global Optimization and Constraint Satisfaction Codes
A benchmarking suite describing over 1000 optimization problems and constraint satisfaction problems covering problems from different traditions is described, annotated with best known solutions, and accompanied by recommended benchmarking protocols for comparing test results.
متن کاملOptimization of Regularization Parameter for GRAPPA Reconstruction
The effectiveness of regularization to improve SNR in parallel imaging techniques has been reported in previous works [1-2], but how to optimize the regularization parameter remains a problem. The regularization parameter controls the degree of regularization and thereby determines the compromise between SNR and artifacts. Over-regularization causes high level of artifact, while under-regulariz...
متن کاملOn Benchmarking Stochastic Global Optimization Algorithms
Amultitude of heuristic stochastic optimization algorithms have been described in literature to obtain good solutions of the box-constrained global optimization problem often with a limit on the number of used function evaluations. In the larger question of which algorithms behave well on which type of instances, our focus is here on the benchmarking of the behavior of algorithms by applying ex...
متن کاملProgress in Global Optimization and Shape Design
We consider a function to minimize J : Ω → IR with Ω ⊂ IR. We make the following assumptions: J ∈ C2(Ω, IR) and is coercive. Its minimum Jm exists. Most deterministic minimization algorithms can be seen as discrete dynamical systems coming from a discretization of first or second order Cauchy problems. If one knows the infimum Jm, global optimization can be considered as Boundary Value Problem ...
متن کاملBenchmarking Global Optimization Algorithms for Core Prediction Identification
Mathematical modeling has evolved from being a rare event to becoming a standard approach for investigating complex biological interactions. However, variations and uncertainties in experimental data usually result in uncertain estimates of the parameters of the model. It is possible to draw conclusions from the model despite uncertain parameters by using core predictions. A core prediction is ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ACS Photonics
سال: 2019
ISSN: 2330-4022,2330-4022
DOI: 10.1021/acsphotonics.9b00706