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I am working on surrogate-based optimization, where the surrogate model is generated by the Gaussian processes regression method in scikit-learn. For the optimization part I have been using scipy.minimize, but I really want to use Pyomo as it offers more robust solvers and the possibility of solving problems with integer variables. Use the following link to see an example posted in overflow: https://stackoverflow.com/questions/68905789/integration-between-gp-scikit-learn-and-pyomo