Before reaching this guide, you’ll have:
- downloaded the engine.
- installed the engine.
Step 1: Launch a Terminal
Open your terminal of choice. You can search for terminal in your start menu or try the shortcut ctrl+shift+t.
Step 2: Install Python
Pyomo uses the Python language to build models. To check if you already have Python installed, enter:
If the version is not returned, relaunch your terminal and re-enter the command.
If this returns version information for Python (version 3.6 or newer), proceed to the next step.
Otherwise install Python and check again.
Step 3: Install pip
You will need pip to retrieve Pyomo for your Python installation. To check if you already have pip installed, enter:
python3 -m pip --version
If this returns version information for pip, proceed to the next step.
Otherwise install pip and check again.
Step 4: Install Pyomo
python3 -m pip install --user pyomo
Look out for any error messages in the output. To verify that it has been sucessfully installed, enter:
This should output version information for Pyomo if installation is successful. If this fails, refer to the Pyomo installation manual for more detail.
Step 5: Use the Python Interpreter
This will open the Python shell, where you can enter Python commands.
Alternatively, you can use a Python editor of your choice. Save the file as your_file.py and enter:
This will run your Python commands in one step.
Step 6: Start your Model
From now on, all commands will either be entered in the Python shell or in a Python file to be run later.
from pyomo.environ import * model = m = ConcreteModel()
This will import the necessary functions from Pyomo and start an empty model.
Step 7: Fill your Model
x1 = m.x1 = Var(within=Reals, bounds=(0,1), initialize=1) x2 = m.x2 = Var(within=Reals, bounds=(0,1), initialize=1) x3 = m.x3 = Var(within=Reals, bounds=(0,1), initialize=None) x4 = m.x4 = Var(within=Reals, bounds=(0,1), initialize=1) x5 = m.x5 = Var(within=Reals, bounds=(0,1), initialize=None) m.obj = Objective(sense=minimize, expr=42*x1 - 0.5*(100*x1*x1 + 100*x2*x2 + 100*x3*x3 + 100*x4*x4 + 100*x5*x5) + 44*x2 + 45*x3 + 47*x4 + 47.5*x5) m.e2 = Constraint(expr=20*x1 + 12*x2 + 11*x3 + 7*x4 + 4*x5 <= 40)
If you’d prefer to get creative, refer to the list of modeling components for Pyomo.
Step 8: Set the Number of Cores (optional)
To make Octeract Engine solve in parallel, enter:
import os os.environ["octeract_options"] = "num_cores=4"
You can replace 4 with any number of cores offered by your subscription.
Step 9: Solve your Model
Finally, to solve your model, enter:
results = SolverFactory("octeract-engine").solve(m, tee=True, keepfiles=False, load_solutions=False) print(results) m.solutions.load_from(results)
If successful, it will print out the optimal solution for your model.
Alternatively, to skip the printing, instead enter:
SolverFactory("octeract-engine").solve(m, tee=True, keepfiles=False)