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Simulation-based stochastic black-box optimization under uncertainty using Stochastic Kriging and Monte Carlo simulation

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MCSKopt

MOSKopt

Process simulation-based design space optimizer with embedded Monte Carlo-based uncertainty quantification.

MOSKopt is a MATLAB-based simulation-based optimizer developed for performing design space optimization under uncertainty in the following paper.

Stochastic simulation-based superstructure optimization framework for process synthesis and design under uncertainty

Installing MOSKopt

Downloading and adding the folder path to your current MATLAB session will suffice to make use of the full functionality of the optimizer. Alternatively, you can also run install.m file in your MATLAB session.

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License

MOSKopt is released under the MIT License.

Acknowledgements

This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no.675251.

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View slides showing examples

MOSKopt

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Simulation-based stochastic black-box optimization under uncertainty using Stochastic Kriging and Monte Carlo simulation

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