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Linear and Nonlinear Programming pp 321–355Cite as

Constrained Minimization Conditions

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 228))

Abstract

We turn now, in this final part of the book, to the study of minimization problems having constraints. We begin by studying in this chapter the necessary and sufficient conditions satisfied at solution points. These conditions, aside from their intrinsic value in characterizing solutions, define Lagrange multipliers and a certain Hessian matrix which, taken together, form the foundation for both the development and analysis of algorithms presented in subsequent chapters.

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Authors and Affiliations

  1. Department of Management Science and Engineering, Stanford University, Stanford, CA, USA

    David G. Luenberger & Yinyu Ye

Authors
  1. David G. Luenberger
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  2. Yinyu Ye
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© 2016 Springer International Publishing Switzerland

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Luenberger, D.G., Ye, Y. (2016). Constrained Minimization Conditions. In: Linear and Nonlinear Programming. International Series in Operations Research & Management Science, vol 228. Springer, Cham. https://doi.org/10.1007/978-3-319-18842-3_11

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