What are the handiest optimization parsers out there? Is COIN-OR's PyPy being used actively? I am currently trying to do an optimization project in Python, but I am used to using MATLAB + YALMIP combination, so I need some advice!
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asked Nov 19 '19 at 14:38
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$\begingroup$ PuLP hands down (if linear) $\endgroup$ – Kuifje Nov 19 '19 at 20:38
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Given you are a MATLAB+Yalmip user you may prefer Cvxpy. Cvxpy is particularly useful if you do nonlinear models. Mosek also includes 2 Python interfaces where the so called Fusion interface may be the most interesting for you.
Here you find a comparison of Cvxpy, Pyomo and Fusion for some large scale problems.
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$\begingroup$ I tried it, that's really like YALMIP. I was overwhelmed with the notation of other parsers, this works great! Note: The documentation of CVXPY says MOSEK can not solve Exponential Cone problems, which is not true anymore I guess, so just flagging here... $\endgroup$ – independentvariable Nov 20 '19 at 23:25
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Handiest optimization package in python is Pyomo(in my opinion). I recommend that because of the following specifications:
- There is a google group ( in addition to se and or.se) that you can ask for help if you stacked.
- You can use all the pythonic facilities to write your model
- There are enough books, tutorials and documents about it.
- Pyomo is an active and well developed package.
- You can also use many available solvers to solve your model written in Pyomo.
- You can easily use solvers on Neos server to solve the model.
answered Nov 19 '19 at 15:06
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$\begingroup$ Thanks much!! How can I find examples with Gurobi? Do you know any resourcse? $\endgroup$ – independentvariable Nov 19 '19 at 16:42
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1$\begingroup$ In this address(pyomo.readthedocs.io/en/stable/working_models.html) it’s explained how to use different solvers to solve your model. $\endgroup$ – Oguz Toragay Nov 19 '19 at 17:25
