2007Journal of Inequalities and ApplicationsOpen access

Generalized Augmented Lagrangian Problem and Approximate Optimal Solutions in Nonlinear Programming

Zhe Chen, Kequan Zhao, Yuke Chen

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Abstract

We introduce some approximate optimal solutions and a generalized augmented Lagrangian in nonlinear programming, establish dual function and dual problem based on the generalized augmented Lagrangian, obtain approximate KKT necessary optimality condition of the generalized augmented Lagrangian dual problem, prove that the approximate stationary points of generalized augmented Lagrangian problem converge to that of the original problem. Our results improve and generalize some known results.

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We introduce some approximate optimal solutions and a generalized augmented Lagrangian in nonlinear programming, establish dual function and dual problem based on the generalized augmented Lagrangian, obtain approximate KKT necessary optimality condition of the generalized augmented Lagrangian dual problem, prove that the approximate stationary points of generalized augmented Lagrangian problem converge to that of the original problem. Our results improve and generalize some known results.

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Available abstract

We introduce some approximate optimal solutions and a generalized augmented Lagrangian in nonlinear programming, establish dual function and dual problem based on the generalized augmented Lagrangian, obtain approximate KKT necessary optimality condition of the generalized augmented Lagrangian dual problem, prove that the approximate stationary points of generalized augmented Lagrangian problem converge to that of the original problem. Our results improve and generalize some known results.

Key concepts: Augmented Lagrangian method, Karush–Kuhn–Tucker conditions, Lagrangian, Lagrangian relaxation, Mathematics, Mathematical optimization, Nonlinear system, Nonlinear programming

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