填充函数法是一种解无约束全局极小化问题的方法。
The filled function method is an approach for solving unconstrained global minimization problem.
研究了用束方法求解非光滑逐点最大凸函数的极小化问题。
In this paper, a bundle method for the minimization of the convex nonsmooth function in point by point maximum is suggested.
给出总体极小化问题的神经网络模型，分析了网络的电路实现。
Neural networks for problems of the global optimization are proposed in this paper and the global convergence of the equilibrium point set is also proven.
这里考察了求解无约束总体极小化问题的神经网络方法，提出了一种新的网络求解模型。
Neural network method for solving global unconstrained minimized problems was investigated and a new neural network model was then proposed.
在新的控制条件下，证明了二次型极小化问题的迭代算法的有效性，所得结果改进了徐洪坤关于二次型优化的最新结果。
Under new control conditions, we prove convergence of the quadratic minimization problem, which improves the recent results by Xu about quadratic optimization.
考虑并行批加工机上不同尺寸工件的调度问题；目标是极小化最大完工时间。
The problem of scheduling jobs with non-identical sizes on parallel batching machines is considered; the objective is to minimize the maximum completion time (makespan).
通过把单目标最优解模糊化，将双目标模糊优化问题转化为单目标极小化极大问题求解；
The problem of fuzzy optimization of two objectives is transformed into single objective problem by means of the fuzziness of optimum solutions of single objective.
若结合本文的初始化方法一同使用，则收敛更快速，且有可能克服局部极小解问题。
It may be possible to overcome local minima and converge more fast when it is used with the initializing method.
将多级燃气涡轮的设计问题表述为其空气动力学损失和质量为极小化目标的多目标非线性数学规划问题。
The problem of multistage design of gas turbines is formulated as a multiobjective nonlinear programming problem with the objective functions of minimum aerodynamic loss and total mass of the turbine.
在一般情况下，对目标函数为极小化完工时间平方和与极小化总误工数问题分别给出了最优算法。
For the general case, optimal algorithms are presented respectively for minimizing the sum of quadratic completion times and the number of tardy jobs.
基于对问题的分析，证明了这一问题等价于单机调度中极小化类似的延迟量函数。
Through the analysis of the problem, it is proved that the problem is equivalent to a single-machine scheduling for minimizing an analogous function of delay.
用序列无约束极小化方法（SUMT）求解非线性有约束的优化问题。
The non linear optimization problem with constraint has been solved by use of the sequential unconstrained minimization technique (SUMT).
本文借助于变分法中求泛函极小化的方法提出求解超定大地边值问题的新方法。
A new method to solve over-determined geodetic boundary value problem is proposed with the help of minimizing some kinds of functional in variation calculus.
进一步，在问题有解时，通过极小化增益矩阵元素绝对值的和，给出了求解期望低成本输出反馈控制的算法。
Then following the existing path-following method for solving BMI problem, an iterative LMI algorithm is proposed to locally search the desired output-feedback gain.
给出一类求解总体极值问题的填充函数，分析了该填充函数的特性与基于填充函数的总体极小化方法。
The properties of this filled function and a global minimization method based on the filled function are analyzed.
讨论任务的加工是不可中断，机器速度相同且机器具有不同开始加工时间的排序问题，目标函数是极小化最大完工时间。
We discuss the nonpreemptive parallel machine scheduling problem with nonsimultaneous available time, the objective function is to minimize the makespan.
本文基于多值逻辑函数极小化提出一种正例学习问题，并对这一正例学习问题给出一个启发式学习算法。
This paper presents a learning problem from positive examples based on multiple valued minimization paradigm. A new heuristic algorithm for the problem is given.
同现存的极小化方法相比，SWT算法简单，极小化程度高，并可适用于十五个以上输入变元的较复杂问题。
Compared with the existing minimization methods, SWT is the simplest, optimal method and applicable to complicated problems with more than 15 input variables.
同现存的极小化方法相比，SWT算法简单，极小化程度高，并可适用于十五个以上输入变元的较复杂问题。
Compared with the existing minimization methods, SWT is the simplest, optimal method and applicable to complicated problems with more than 15 input variables.
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