Sanity checking the solution

Supply Chain Analytics in Python

Aaren Stubberfield

Supply Chain Analytics Mgr.

solution strategy flow chart

Check the model status

Infeasible: There are no feasible solutions.
- Review the constraints
Unbounded: The object function is not bounded, maximizing or minimizing the objective will tend towards infinity.
- Review the objective function
Undefined: The optimal solution may exist but may not have been found.
- Maybe the best available solution
- Review how you are modeling the problem

Check if results are within expectations

Are the decision variables and value of objective within expected range?

Based on knowledge / understanding of problem
If "Yes", then you have a valid solution
If "No", then review:
- Python code
- Data
- Write the LP File

Write LP

writeLP(filename)

filename = The name of the file to be created

Shows:

Name of problem
Objective function and if minimizing or maximizing
Constraints, including constraints on Decision Variables called Bounds
Decision variables

Code example

\* Aggregate Production Planning *\
Minimize
OBJ: 20 prod_('A',_0) + 17 prod_('A',_1) 
    + 18 prod_('A',_2) + 15 prod_('B',_0) 
    + 16 prod_('B',_1) + 15 prod_('B',_2)
Subject To
_C1: prod_('A',_0) >= 0
_C2: prod_('A',_1) >= 0
_C3: prod_('A',_2) >= 0
_C4: prod_('B',_0) >= 8
_C5: prod_('B',_1) >= 7
_C6: prod_('B',_2) >= 6

Bounds
0 <= prod_('A',_0)
0 <= prod_('A',_1)
0 <= prod_('A',_2)
0 <= prod_('B',_0)
0 <= prod_('B',_1)
0 <= prod_('B',_2)
Generals
prod_('A',_0)
prod_('A',_1)
prod_('A',_2)
prod_('B',_0)
prod_('B',_1)
prod_('B',_2)

Summary

Strategy for Sanity Checking

Check the model status
Check decision variables and objective inside expected range
Use writeLP() if needed

Practice time!

Supply Chain Analytics in Python