I have the analytical first and second derivatives of a (multidimensional) lagrangian ( l = f - λh). X is the vector of variables of the objective function and λ is the single lagrange multiplier.(adsbygoogle = window.adsbygoogle || []).push({});

where f=f(X) is the nonlinear objective function, h is the nonlinear (equality) constraint (i.e. h(X) - ρ = 0 at optimized solution). I'm generally confused about how to solve this (i've read about the "Lagrange-Newton (SOLVER) method" but don't really understand it.

How do I update X and λ? Please try to be as specific as possible. Thanks.

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# Constrained Optimization via Lagrange Multipliers

Can you offer guidance or do you also need help?

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