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.
Production of FT transporta- tion fuels from biomass; technical options, process analysis and optimisation, and development potential
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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.