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InputUncertainty

Illustrative code for the results produced in the paper

"Bayesian Simulation Optimisation with Input Uncertainty, Michael Pearce, Juergen Branke. Winter Simulation Conference 2017".

@inproceedings{pearce2017bayesian,
  title={Bayesian simulation optimization with input uncertainty},
  author={Pearce, Michael and Branke, Juergen},
  booktitle={2017 Winter Simulation Conference (WSC)},
  pages={2268--2278},
  year={2017},
  organization={IEEE}
}

BayesOpt_InputUncertainty.R

R source code for the expriments, generate a test function with two inputs, collect evaluations from it in order to find the value of the oinput that maximises the average of the funtion over the second input.

TotalData733

R results save file, open file with "Results = readRDS('TotalData733')", this contains 100 repetitions of each data collection method where each repetition has a different test function and noise value. Each of 5 methods was applied 100 times each using two different input uncertainty distributions, uniform, and triangular. The file is a list with 1000 elements, 2 distributions * 5 algoroithms * 100 repetitions = 1000 experiments.

Plot_Results.R

R source code to open and plot the TotalData733 file and reproduce the plots in the paper.

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Code for the results produced in the paper submitted to the Winter sImulation Conference 2017

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