A merit function is a scalar objective function used by an iterative constrained algorithm to balance objective reduction and feasibility. It permits a line search or other acceptance test even when the original objective function alone is insufficient to judge progress. Quadratic penalty methods and the augmented Lagrangian method give two constructions with different treatments of multiplier information.
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