Complete the square in the augmented Lagrangian method objective:For fixed , the last term is constant in . Thus its minimization is the quadratic penalty method applied to the shifted constraint .
Its practical advantage is that multiplier updates, typically , can drive the original constraint residual to zero while stays moderately sized. The plain quadratic penalty method generally needs very small to produce the same feasibility accuracy, exposing the conditioning problem in part (ii).
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