This project implements an algorithm that lower bounds a given mixed-integer nonlinear programming (MINLP) Synheat instance. The algorithm models the MINLP formulation as a mixed-integer linear programming relaxation and iteratively tightens by adding cutting planes for convex functions and breakpoints for piecewise approximations.
The following paper describes the method.
- Mistry, M., Misener, R. 2016. Optimising heat exchanger network synthesis using convexity properties of the logarithmic mean temperature difference. Computers & Chemical Engineering. 94, 1-17.
- Python 3.5.2
- Pyomo 5.0.1
- PyLatex 1.0.0 (optional)
- Gurobi
To find out how to use the code, run from terminal:
cd <directory>
python iterative.py -hwhere directory is one of:
- adaptive_model_mixer,
- beta_adaptive_model_mixer.
These two directories contain the two algorithm mentioned in the associated paper.
Put it in the datafiles directory and give it the extension .dat.
The contents of the datafile should be similar to that of those already in the datafiles directory.
Assuming that the new datafile is called example.dat, running the following should work.
cd adaptive_model_mixer
python iterative.py example anyAlphaNumericThingCanGoHere