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Quadratic programming (QP) is a special type of mathematical optimization problem. It is the problem of optimizing (minimizing or maximizing) a quadratic function of several variables subject to linear constraints on these variables. ==Problem formulation== The quadratic programming problem with variables and constraints can be formulated as follows.〔.〕 Given: * a real-valued, -dimensional vector , * an -dimensional real symmetric matrix , * an -dimensional real matrix , and * an -dimensional real vector , the objective of quadratic programming is to find an -dimensional vector , that \mathbf^\mathrm Q\mathbf + \mathbf^\mathrm \mathbf |- | subject to | |} where denotes the vector transpose of . The notation means that every entry of the vector is less than or equal to the corresponding entry of the vector . A related programming problem, quadratically constrained quadratic programming, can be posed by adding quadratic constraints on the variables. 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Quadratic programming」の詳細全文を読む スポンサード リンク
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