1) minimax assignment problem
极大极小指派问题
2) global-minimum assignment problem
总体极小指派问题
1.
The operations on matrix for both minimax and global-minimum assignment problems of square matrix are applied to those of nonsquare matrix,namely,in the same efficiency with the operations on matrix,both the minimax and global-minimum assignment problems where number of people is unequal to number of tasks are solved.
本文将2类方阵指派问题——极大极小和总体极小指派问题——的矩阵作业解法推广到非方阵情形,即求解任务与人员数目不等的指派问题,且维持矩阵作业法的效率。
3) minimax problem
极大极小问题
1.
An effective approach to deal with the Quadratic Programming (QP) problem is presented, which is to convert QP problem into a minimax problem without constraints by using dual transformation.
利用对偶变换 ,将二次规划问题转化为无约束极大极小问题 ,然后运用极大熵方法 ,将极大极小问题转化为求解一个无约束凸规划极值问题 ,从而能够同时求出原问题及其对偶问题的近似解 。
2.
Minimax problem is a sort of non-differentiable optimization problem and the entropy function method provides a efficient approach to solve such kind of problems.
极大极小问题是一类不可微优化问题,熵函数法是求解这类问题的一种有效算法。
4) minimax problem
极小极大问题
1.
Smoothing Newton method for constrained minimax problems;
约束极小极大问题的光滑化牛顿方法
2.
A trust region algorithm for the Minimax problem;
极小极大问题的一个信赖域方法
3.
Since there are many problems of topological network design that can regard as minimax problems, we solve those problems with entropy method, which is powerful to solve minimax problems.
由于几何拓扑网络设计中许多问题都可以归结为极小极大问题,而熵函数法正是求解极小极大 问题的一个强有力的数学工具,所以本文试图运用熵函数法求解一些几何拓扑网络设计问题,理论分析和试 验结果均表明了熵函数法求解这些问题的有效性。
5) minimax problems
极大极小问题
1.
Solving nonlinear minimax problems by Gray coding genetic algorithm;
解非线性极大极小问题的格雷码加速遗传算法
2.
In the thesis, symmetrically consistent group-wise updating Newton-like methods, inexact Newton methods and inexact symmetrically consistent group-wise updating Newton-like methods for large scale sparse minimax problems are studied.
本文研究求解大型稀疏极大极小问题的对称相容分组修正Newton型方法、不精确牛顿法和不精确对称相容分组修正Newton型方法。
6) max-min problem
极大极小问题
1.
A feasible trust algorithm which used maxim-entropy methods, a class of max-min problems with nonlinear constraints turn into nonlinear programming problems with inequality constraints is proposed.
针对一类非线性约束极大极小问题,利用极大熵方法将转化为带不等式约束的非线性规划问题,给出了一种可行信赖域算法,解决了不等式约束的非线性大系统优化问题,并证明了该算法的全局收敛性。
2.
In this paper, a gradient projection algorithm using maxim-entropy methods is analyzed and a class of max-min problems with nonlinear constraints are changed into nonlinear programming problems with inequality and equality constra.
针对一类非线性约束极大极小问题，利用极大熵方法将其转化为带等式、不等式约束的非线性规划问题，给出了一种梯度投影算法，解决了一般约束的非线性大系统优化问题，该算法初始点可任意；同时证明了该算法的全局收敛性。
补充资料：极大算子和极小算子
极大算子和极小算子
maximal and mnmnal operators
极大算子和极小算子脚.劝加目邵目，汕面司啊呷rators;MaKC班Ma“比戚班M”n皿Ma几I.H丽姐epaT仰址] 由在具有紧支集的函数子空间上给定的微分表示式定义的算子的极大扩张和极小扩张(m助面旧1肚记mj刘h坦1 exte留ions).极大算子和极小算子的定义域可以分为许多情形具体描述，例如，对常微分算子、对椭圆算子、对常系数微分算子.
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条