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Some reasons to connect your solvers to OpenOpt

(Information for optimization software owners/developers)

NB! Connecting C/C++/Fortran code to Python via f2py, ctypes, SWIG is much easier than, for example, using MATLAB MEX-functions.

1. You could use OpenOpt for your own purposes, particularly for easy benchmarking other algorithms v.s. yours, implemented in connected solvers.

2. You can use OpenOpt solvers as solvers for you optimization subproblems, for example LP solvers connected to you MILP solver, or box-bounded NLP solvers (scipy_tnc, scipy_lbfgsb) for your general constrained NLP solver.

3. OpenOpt graphical output can be easily connected to your solver(s).

4. Maybe, you have grantee programs as well as reports on them. So connecting your solver(s) to OpenOpt could become another one essential chapter in your report.

5. OpenOpt doesn't contain your code, but provides URL for download instead. So, your site visitors number will be increased.

See Also

Why OpenOpt? (is one of best choices for users) >>>