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Nonlinear least squares and nonlinearly constrained optimization

Conference paper
Part of the Lecture Notes in Mathematics book series (LNM, volume 506)

Keywords

Jacobian Matrix Search Direction Lower Triangular Matrix Unconstrained Minimization Quadratic Penalty Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Brown, K.M. and Dennis, J.E. (1970) “New Computational Algorithms for Minimizing a Sum of Squares of Nonlinear Functions” Yale University Report.Google Scholar
  2. Gill, P.E. and Murray, W. (1974a) “Safeguarded Steplength Algorithms for Optimization using Descent Methods” NPL Report NAC 31.Google Scholar
  3. Gill, P.E. and Murray, W. (1974b) “Newton-type Methods for Unconstrained and Linearly Constrained Optimization” Math Prog 7, 311.MathSciNetCrossRefzbMATHGoogle Scholar
  4. Kowalik, J., Osborne, M.R. and Ryan, D.M. (1969) “A New Method for Constrained Optimization Problems”, Operations Research. 17, 973.MathSciNetCrossRefzbMATHGoogle Scholar
  5. Morrison, D.D. (1968) “Optimization by Least Squares” SIAM J. Num. Anal. 5, 83.MathSciNetCrossRefzbMATHGoogle Scholar
  6. Schmit, L.A. and Fox, R.L. (1965) “Advances in the Integrated Approach to Structural Synthesis”, AIAA 6th Ann Struct. and Mat. Conf., Palm Springs.Google Scholar

Copyright information

© Springer-Verlag 1976

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