Convex Programming

Robert J. Vanderbei
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Robert J. Vanderbei: Princeton University

Chapter Chapter 25 in Linear Programming, 2014, pp 379-388 from Springer

Abstract: Abstract In the last chapter, we saw that small modifications to the primal–dual interior-point algorithm allow it to be applied to quadratic programming problems as long as the quadratic objective function is convex. In this chapter, we shall go further and allow the objective function to be a general (smooth) convex function. In addition, we shall allow the feasible region to be any convex set given by a finite collection of convex inequalities.

Keywords: Primal-dual Interior-point Algorithms; Merit Function; Successive Quadratic Programming Algorithm; First-order Optimality Conditions; Quadratic Approximation (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-1-4614-7630-6_25

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