Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

pySOT and POAP: An event-driven asynchronous framework for surrogate optimization



David Eriksson , David Bindel , Christine A. Shoemaker


   Access Paper or Ask Questions

Efficient Multi-Objective Optimization through Population-based Parallel Surrogate Search



Taimoor Akhtar , Christine A. Shoemaker

* Submitted to IEEE Transactions on Evolutionary Computation. This work is supported by the National Research Foundation, Prime Minister's Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme and by the National Science Foundation (NSF) grant CISE 1116298 

   Access Paper or Ask Questions

Sensitivity Analysis for Computationally Expensive Models using Optimization and Objective-oriented Surrogate Approximations



Yilun Wang , Christine A. Shoemaker


   Access Paper or Ask Questions

A General Stochastic Algorithmic Framework for Minimizing Expensive Black Box Objective Functions Based on Surrogate Models and Sensitivity Analysis



Yilun Wang , Christine A. Shoemaker


   Access Paper or Ask Questions