The Kitchin Research Group

We’ve developed a new kind of decision-tree model that’s both smart and practical for tackling tough engineering problems. First, we take raw data and "lift" it into a richer feature space so we can slice it more cleverly including angular shapes. Next, we grow a friendly “hyperplane” tree that splits data along these angled cuts, fitting simple linear models in each branch. The result is a piecewise-linear surrogate that behaves a lot like the real system but runs orders of magnitude faster. Finally, because each piece is just a linear model, we can plug the whole thing straight into an optimizer that finds the very best solution under complex rules. That means we can design chemical processes, heat exchangers, or any engineering system more reliably and sustainably - saving time, energy, and cost.

@article{sunshine-2025-hyper-decis,
  author =       {Ethan M. Sunshine and Carolina Colombo Tedesco and Sneha A.
                  Akhade and Matthew J. McNenly and John R. Kitchin and Carl D.
                  Laird},
  title =        {Hyperplane Decision Trees As Piecewise Linear Surrogate Models
                  for Chemical Process Design},
  journal =      {Computers \& Chemical Engineering},
  volume =       {},
  number =       {},
  pages =        109204,
  year =         2025,
  doi =          {10.1016/j.compchemeng.2025.109204},
  url =          {https://doi.org/10.1016/j.compchemeng.2025.109204},
  DATE_ADDED =   {Wed Jul 9 14:14:17 2025},
}

Copyright (C) 2025 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 9.8-pre