New algorithm for constrained nonlinear least-squares problems. Part I
A new Gauss-Newton algorithm is presented for solving nonlinear least squares problems. The problem statement may include simple bounds or more general constraints on the unknowns. The algorithm uses a trust region that allows the objective function to increase with logic for retreating to best values. The computations for the linear problem are done using a least squares system solver that allows for simple bounds and linear constraints. The trust region limits are defined by a box around the current point. In its current form the algorithm is effective only for problems with small residuals, linear constraints and dense Jacobian matrices. Results on a set of test problems are encouraging.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (USA); Jet Propulsion Lab., Pasadena, CA (USA)
- DOE Contract Number:
- AC04-76DP00789
- OSTI ID:
- 5935436
- Report Number(s):
- SAND-83-0936; ON: DE83016773
- Country of Publication:
- United States
- Language:
- English
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