Abstract
Quadratic programming (QP) is a family of methods, techniques, and algorithms that can be used to minimize quadratic objective functions subject to linear constraints. QP shares many combinatorial features with linear programming (LP) and it is often used as the basis of constrained nonlinear programming. An important branch of QP is convex QP where the objective function is a convex quadratic function.
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Antoniou, A., Lu, WS. (2021). Quadratic, Semidefinite, and Second-Order Cone Programming. In: Practical Optimization. Texts in Computer Science. Springer, New York, NY. https://doi.org/10.1007/978-1-0716-0843-2_13
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