Title: Solving Constrained Nonlinear Least Squares Problems by a General Purpose SQP-Method
Abstract: Nonlinear least squares problems are extremely important in many domains of mathematical programming applications, e.g. maximum likelihood estimations, nonlinear data fitting or parameter estimation, respectively. A large number of special purpose algorithms is available in the unconstrained case, but only very few methods were developed for the nonlinearly constrained case. The paper shows that a simple transformation of the original problem and its subsequent solution by a general purpose sequential quadratic programming algorithm retains typical features of special purpose methods, i.e. a combination of a Gauß-Newton and a quasi-Newton search direction. Moreover the numerical investigations indicate that the algorithm can be implemented very easily if a suitable sequential quadratic programming code is available, and that the numerical test results are comparable to that of special purpose programs.
Publication Year: 1988
Publication Date: 1988-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 47
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