New Form of Lagrangian Multiplier Methods
Aifen Feng, Cuixia Xu, Dingguo Pu
Abstract
Aifen Feng, Cuixia Xu, Dingguo Pu
Abstract
The Lagrangian multiplier method is one of the important methods of solving nonlinear constraints programming. In this paper, a new class of augmented Lagrangian functions with a new NCP function is proposed for the minimization of a smooth function subject to smooth equation and inequality constraints. Under certain conditions, We prove 1-1 corresponding relationship of optimality solution between the primal constrained problem and the new unconstrained problem. Then a Algorithm is constructed to solve nonlinear constraints problem, and also prove the convergence of the algorithm.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The Lagrangian multiplier method is one of the important methods of solving nonlinear constraints programming. In this paper, a new class of augmented Lagrangian functions with a new NCP function is proposed for the minimization of a smooth function subject to smooth equation and inequality constraints. Under certain conditions, We prove 1-1 corresponding relationship of optimality solution between the primal constrained problem and the new unconstrained problem. Then a Algorithm is constructed to solve nonlinear constraints problem, and also prove the convergence of the algorithm.
Key concepts: Augmented Lagrangian method, Lagrange multiplier, Lagrangian, Multiplier (economics), Mathematics, Mathematical optimization, Lagrangian relaxation, Convergence (economics)