An Efficient Optimization-Simulation Tool for Distillation Processes

Status: Under Review at The Journal of Supercomputing Submission Date: October 05, 2025

Overview

This repository contains the source code for the research paper "An Efficient Optimization-Simulation Tool for Distillation Processes".

Prerequisites

To run the main simulation and optimization routines, you need:

• Scilab (Version 2025.1.0 or higher recommended).
  • Required Toolboxes: Scibench (for benchmarking).

To run the comparative benchmarks mentioned in the paper:

• Python (Version 3.12.11+).
  • numpy
  • jax (for automatic differentiation and sparse matrix benchmarking).

Note on Hardware: The experiments in the paper were performed on a high-performance server ("Curupira") with Intel Xeon Silver 4214 CPUs and 768 GB RAM, though the code can run on standard workstations.

Authors

• Gustavo Mendes Platt (Corresponding Author)
  • Federal University of Rio Grande (FURG)
  • Email: gmplatt@furg.br
• Francisco Bruno Souza Oliveira
  • State University of Santa Cruz (UESC)
  • Email: fbsoliveira@uesc.br
• Gustavo Barbosa Libotte
  • Rio de Janeiro State University (UERJ)
  • Email: gustavolibotte@iprj.uerj.br
• Fran Sérgio Lobato
  • Federal University of Uberlândia (UFU)
  • Email: fslobato@ufu.br

Citation

If you use this code or methodology in your research, please cite the associated manuscript:

@article{Platt2025,
  title={An Efficient Optimization-Simulation Tool for Distillation Processes},
  author={Platt, Gustavo Mendes and Oliveira, Francisco Bruno Souza and Libotte, Gustavo Barbosa and Lobato, Fran Sérgio},
  journal={The Journal of Supercomputing},
  year={2025},
  note={Submitted/Under Review}
}