Sequential quadratic programming

The graph of a strictly concave quadratic function is shown in blue, with its unique maximum shown as a red dot. Below the graph appears the contours of the function: The level sets are nested ellipses.

Sequential quadratic programming (SQP) is an iterative method for nonlinear optimization. SQP methods are used on mathematical problems for which the objective function and the constraints are twice continuously differentiable.

SQP methods solve a sequence of optimization subproblems, each of which optimizes a quadratic model of the objective subject to a linearization of the constraints. If the problem is unconstrained, then the method reduces to Newton's method for finding a point where the gradient of the objective vanishes. If the problem has only equality constraints, then the method is equivalent to applying Newton's method to the first-order optimality conditions, or Karush–Kuhn–Tucker conditions, of the problem. SQP methods have been implemented in many packages, including KNITRO, NPSOL, SNOPT, NLPQL, OPSYC, OPTIMA, MATLAB, GNU Octave, SQP and SciPy.

单词	SQP
释义	SQP 英汉-汉英词典逐次二次规划词组 \| 习惯用语您要查找的是不是： skip vi. 跳绳；遗漏；跳读；跳跃 vt. 遗漏；跳过 sip n. 抿；小口喝；[计]单列直插式组件 vi. 啜饮 sap n. 树液；活力；坑道；精力，元气 vt. 使衰竭，使伤元气；挖掘以破坏基础 sup v. 啜；小口地喝；供给晚饭 n. 一小口 sop 小恩小惠，小安慰品网络短语: SQP subproblem SQP子问题 SQP method SQP方法 SQP methods SQP方法 SQP 接近开关; 序列二次规划; 序列二次规划法; 二次规划法; SQP iteration SQP迭代 cell sqp 胞液 SQP ServiceQueryPacket 服务查询数据分组 pile SQP 基桩SQP法 SQP algorithm SQP算法 SQP operator SQP算子英语百科 Sequential quadratic programming Sequential quadratic programming (SQP) is an iterative method for nonlinear optimization. SQP methods are used on mathematical problems for which the objective function and the constraints are twice continuously differentiable. SQP methods solve a sequence of optimization subproblems, each of which optimizes a quadratic model of the objective subject to a linearization of the constraints. If the problem is unconstrained, then the method reduces to Newton's method for finding a point where the gradient of the objective vanishes. If the problem has only equality constraints, then the method is equivalent to applying Newton's method to the first-order optimality conditions, or Karush–Kuhn–Tucker conditions, of the problem. SQP methods have been implemented in many packages, including KNITRO, NPSOL, SNOPT, NLPQL, OPSYC, OPTIMA, MATLAB, GNU Octave, SQP and SciPy.
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SQP

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网络短语:

Sequential quadratic programming