Constrained Minimization Conditions

David G. Luenberger and Yinyu Ye
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David G. Luenberger: Stanford University
Yinyu Ye: Stanford University

Chapter Chapter 11 in Linear and Nonlinear Programming, 2016, pp 321-355 from Springer

Abstract: 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.

Keywords: Relative Minimum Point; Second-order Sufficiency Conditions; Active Inequality Constraints; Strict Local Minimum; Lagrangian Relaxation Problem (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/978-3-319-18842-3_11

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