TY - CHAP
T1 - Convex programming
AU - Vanderbei, Robert J.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-030-39415-8_25
DO - 10.1007/978-3-030-39415-8_25
M3 - Chapter
AN - SCOPUS:85090022643
T3 - International Series in Operations Research and Management Science
SP - 433
EP - 443
BT - International Series in Operations Research and Management Science
PB - Springer
ER -