约束优化(Constrained Optimization),即约束优化问题,是优化问题的分支。它是在一系列约束条件下,寻找一组参数值,使某个或某一组函数的目标值达到最优。其中约束条件既可以是等式约束也可以是不等式约束。寻找这一组参数值的关键可是:满足约束条件和目标值要达到最优。求解约束问题的方法可分为传统方法和进化算法。
有约束优化 [分化] Constrained optimization
多约束优化路径 MCOP
模糊关系约束优化 FRCO
有约束优化装箱 Constraint Container Loading
非线性约束优化 nonlinearly constrained optimization
不等式约束优化问题 Inequality Constrained Optimization Problem
边界约束优化 bound constrained optimization
凸约束优化 Convex constrained optimization ; constrained convex optimization
系统的约束优化问题 the constrained optimization problem
A kind of WC method - constrained optimization (CO) method is proposed.
3) 提出了有约束优化方法,它是一种权值约束法。
参考来源 - 基于先验知识的神经元网络建模与应用The local search ability of linear search can speed up the rate of convergence. To solve nonlinear constraint optimization problems, COA is combined with exact non differentiable penalty function.
结合精确不可微罚函数求解非线性约束优化问题。
参考来源 - 基于线性搜索的混沌优化及其在非线性约束优化问题中的应用The non-linear constrained optimization theory is utilized to solve the problem and get the filter coefficients.
利用非线性约束优化理论对滤波器系数进行求解。
参考来源 - 高频雷达复合调制波形设计与处理·2,447,543篇论文数据,部分数据来源于NoteExpress
在本文中,我们考虑非线性不等式约束优化问题。
In this paper, we consider the nonlinear inequality constrained optimization problems.
通过变换可将该无约束优化问题转化为求解非线性代数方程组的问题。
This unconstrained optimization problem may be transformed into nonlinear algebraic system of equations.
罚函数法(SUMT)是处理约束优化问题时最常用、也是较为成功的一种方法。
Sequential Unconstrained Minimization Techniques (SUMT) are most common and comparatively successful method in constrained optimization.
应用推荐