Embedding trained neural networks as surrogates in a mixed-integer quadratically constrained program enables simultaneous optimization of discrete process selection and continuous parameters for Fischer-Tropsch kerosene, identifying hybrid ATR-biomass routes as lowest-cost at zero net emissions.
Optimal design of a sector- coupled renewable methanol production amid political goals and expected conflicts: Costs vs. land use
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Superstructure Optimization with Embedded Neural Networks for Sustainable Aviation Fuel Production
Embedding trained neural networks as surrogates in a mixed-integer quadratically constrained program enables simultaneous optimization of discrete process selection and continuous parameters for Fischer-Tropsch kerosene, identifying hybrid ATR-biomass routes as lowest-cost at zero net emissions.