Abstract
Lagrangian functions are the basis of many of the more successful methods for nonlinear constraints in optimization calculations. Sometimes they are used in conjunction with linear approximations to the constraints and sometimes penalty terms are included to allow the use of algorithms for unconstrained optimization. Much has been discovered about these techniques during the last eight years and this paper gives a view of the progress and understanding that has been achieved and its relevance to practical algorithms. A particular method is recommended that seems to be more powerful than the author believed to be possible at the beginning of 1976.
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Powell, M.J.D. Algorithms for nonlinear constraints that use lagrangian functions. Mathematical Programming 14, 224–248 (1978). https://doi.org/10.1007/BF01588967
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DOI: https://doi.org/10.1007/BF01588967