Sequential quadratic programming is the best NLP method for scalar optimisation
problem solution. This method has a strong theoretical basis in KKT conditions.
How does this method work? We create a quadratic approximation to the Langrangian function, linear approximation to the constraints, then we solve a quadratic problem in order to find the search direction. This method is able to perform a very fast optimisation. Obviously the first and second derivatives of the objective functions must exist.
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