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A SELF-ADAPTIVE ALGORITHM FOR NONLINEAR LEAST SQUARES WITH LINEAR CONSTRAINTS

A SELF-ADAPTIVE ALGORITHM FOR NONLINEAR LEAST SQUARES WITH LINEAR CONSTRAINTS
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摘要 An algorithm for solving nonlinear least squares problems with general linear inequality constraints is described.At each step,the problem is reduced to an unconstrained linear least squares problem in a subs pace defined by the active constraints,which is solved using the quasi-Newton method.The major update formula is similar to the one given by Dennis,Gay and Welsch (1981).In this paper,we state the detailed implement of the algorithm,such as the choice of active set,the solution of subproblem and the avoidance of zigzagging.We also prove the globally convergent property of the algorithm. An algorithm for solving nonlinear least squares problems with general linear inequality constraints is described.At each step,the problem is reduced to an unconstrained linear least squares problem in a subs pace defined by the active constraints,which is solved using the quasi-Newton method.The major update formula is similar to the one given by Dennis,Gay and Welsch (1981).In this paper,we state the detailed implement of the algorithm,such as the choice of active set,the solution of subproblem and the avoidance of zigzagging.We also prove the globally convergent property of the algorithm.
基金 Supported by The Natural Science Fundations of China and Jiangsu
关键词 nonlinear least SQUARES linear INEQUALITY constraints QUASI-NEWTON METHOD TRUST region METHOD global convergence. nonlinear least squares, linear inequality constraints, quasi-Newton method, trust region method, global convergence.
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