Dual techinques for constrained optimization

Keywords

Augmented Lagrangian method, Mathematical optimization, Convergence (economics), Minification, Conjugate gradient method

References

• The Finite Difference Method in Partial Differential EquationsA. R. Mitchell, David F. Griffiths — 1980
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• A Rapidly Convergent Descent Method for MinimizationR. Fletcher, M. J. D. Powell — 1963
• Algorithms for nonlinear constraints that use lagrangian functionsM. J. D. Powell — 1978
• A globally convergent constrained quasi-Newton method with an augmented lagrangian type penalty functionHiroshi Yamashita — 1982
• Dual Approximations in Optimal ControlWilliam W. Hager, G. Ianculescu — 1984
• Superlinearly convergent variable metric algorithms for general nonlinear programming problemsShih-Ping Han — 1976
• Introduction to linear and nonlinear programmingE. Polak — 1973
• The multiplier method of Hestenes and Powell applied to convex programmingR. T. Rockafellar — 1973
• Matrix computationsGene H. Golub — 1983
• Computational methods in optimization, A unified approach1972
• Numerical Methods for Non-Linear OptimizationS. Vajda, F. A. Lootsma — 1973
• TWO-PHASE ALGORITHM FOR NONLINEAR CONSTRAINT PROBLEMS11This research was supported in part by the National Science Foundation grant MCS 76-23311. Support by the Systems Optimization Lab, Department of Operations Research, Stanford University, during the author's sabbatical leave, is also gratefullyJ. B. Rosen — 1978

Cited by

• Dual techniques for constrained optimizationWilliam W. Hager — 1987

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