Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix (Classic Reprint) - Tapa dura

Sinopsis

Excerpt from Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix

We are interested in developing sequential quadratic programming methods which maintain an approximation to second derivative information projected onto the tangent space of the constraints. The main motivation for our work is that only the projected matrix enters into the optimality conditions for the nonlinear problem.

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