mchlshort / mchlshort/MExNetS

Not getting good solutions for large problem

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good first issue help wanted
Dominant language
Python
Stars
3
Forks
1
PR merge metrics
No merged PRs in 30d

Description

At the moment the second example has very poor solutions and extremely long solve times. There are a number of potential fixes that may work and would be good to get going in Pyomo:

  1. Initialize the problem with a smaller subset of the discrete variables to make the B&B less time-consuming
  2. Try and get a better implementation for the big-M constraints
  3. Check that the model is working properly regarding the lean stream "L" - currently the model does not guarantee that lean process streams are utilized fully. Fixing the L value of the process streams results in infeasible model
  4. Input the non-isocompositional mixing equations
  5. Try and get BARON or COUENNE working for the problem

These are all potential fixes that would make a good first issue for someone.

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the second example in the Pyomo model and compare its solve behavior with the stated lean stream "L" constraint. Investigate the listed alternatives—discrete-variable initialization, big-M constraints, non-isocompositional mixing equations, and BARON or COUENNE support—and consider the issue done only when the example produces acceptable solutions and solve times.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
backend
Issue type
Bug
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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