pyomo k_aug interface in Pyomo sensitivity toolbox reports wrong answer

k_aug interface in Pyomo sensitivity toolbox reports wrong answer

Open adowling2 opened this issue 3 years ago • 3 comments

Summary

For the following simple example:

'''
Consider the following optimization problem.
min f:  p1*x1+ p2*(x2^2) + p1*p2
         s.t  c1: x1 + x2 = p1
              c2: x2 + x3 = p2
              0 <= x1, x2, x3 <= 10
              p1 = 10
              p2 = 5
Variables = (x1, x2, x3)
Parameters (fixed variables) = (p1, p2)
'''

The k_aug interface in pyomo/contrib/sensitivity_toolbox/sens.py does not give the correct sensitivity values (which can be calculated analytically).

The k_aug interface in /idaes/apps/uncertainty_propagation/sens.py does give the correct answer.

Moreover, sens.py in Pyomo has been updated in the past few months including improved comments and some code refactorization. There is a larger need to merge these two versions of sens.py (and the IDAES toolbox should use the version in Pyomo).

Steps to reproduce the issue

The code for the example is here: https://github.com/IDAES/idaes-pse/blob/main/idaes/apps/uncertainty_propagation/examples/simple_opt_problem.py

A new .py file to show the inconsistency will be added to the corresponding PR for this issue.

Error Message

No error message, but calculated values do not match the analytic solution.

Information on your system

Pyomo version: Python version: Operating system: How Pyomo was installed (PyPI, conda, source): Solver (if applicable):

Additional information

Sep 08 '21 16:09 adowling2

Two separate issues for minimal working examples in PR #2124 :

(1) get_dfds_dcds() has the same (wrong) behavior for sens.py in IDAES and Pyomo. It is missing a non-zero entry.

(2) get_dsdp() gives different results for sens.py in IDAES and Pyomo. The IDAES version is correct, but the Pyomo version has the code clarity enhancement you have made in the past few months.