I have tried several of the solvers available through OpenOpt and found them to be inferior to MATLAB's fmincon/sqp. I'm looking for something that robustly converges to a local optimum even for challenging problems, and even if it's slightly slower than fmincon(). It's okay if it doesn't guarantee a global optimum ( fmincon() does not). not require the user to provide a Jacobian. ![]() be able to handle nonlinear equality and inequality constraints.Is there a NLP solver with Python bindings that can compete with fmincon()? It must However, most of my code is in Python, and I'd love to do the optimization in Python as well. Currently I use MATLAB's Optimization Toolbox (specifically, fmincon() with algorithm= 'sqp'), which is quite effective. ![]() I have several challenging non-convex global optimization problems to solve.
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