并给出集值优化问题的超有效解在广义梯度下的最优条件。
The optimality conditions of (super)-efficient solution of set-valued optimization problems are presented in the sense of generalized gradient.
本文在集值优化的框架下提出了一个二层多目标规划模型(BLMOP)。
This paper presents a bilevel multiobjective programming model (BLMOP) in the framework of set-valued optimization.
集值优化问题的最优性条件与解集的结构理论在集值优化理论中占有重要的地位。
Under the nearly cone-subconvexlike set-valued maps, relations of strong efficient solutions and Kuhn-Tucker saddle point of set-valued optimization problem are dicussed.
该文利用集值映射的三种切上导数概念，给出了向量集值优化问题中严有效点的最优性条件。
In this paper, a few optimality conditions for strictly efficient points of set valued optimization are presented by using the concept of contingent derivatives of set valued mad.
分别在单序列时建立递进灰拟合模型，在多维数据集时利用属性相关性，对插值结果进行学习优化。
An optimization method for reasoning results is presented, such as recursive grey fitting model for single sequence and attribute correlativity model for multi-dimension data.
本文在局部凸空间中对集值映射最优化问题引入超有效解的概念。
In this paper, we introduce a concept of super efficient solution of the optimization problem for a set-valued mapping.
目的研究锥扰动集值映射向量优化问题锥有效解的锥次可微性。
Aim to study the cone subdifferential of the cone efficient solution sets for set valued vector optimization problem with perturbed order.
最后，利用择一性定理，获得了含不等式和等式约束的广义次似凸集值映射向量最优化问题的最优性条件。
Finally, the optimality conditions for vector optimization problems with set valued maps with equality and inequality constraints are obtained with it.
该方法通过在遥感图像上选取局部极值点来构成平面散乱数据点集，并在此基础上进行三角剖分、优化和三角插值曲面构造。
It gets the plane scattered data points through selecting the local extremum points on the remote image, and then triangulates, constructs the triangular interpolating surface on it.
本文对无线传感器网络的节点配置问题的研究方法是一个对建立的目标价值函数的可变参数集进行优化，从中求得最优值的过程。
For the problem of WSN node deployment, this paper's researching approach is a process of optimizing the variable parameter set of object value function and then finding the optimal result.
本文对无线传感器网络的节点配置问题的研究方法是一个对建立的目标价值函数的可变参数集进行优化，从中求得最优值的过程。
For the problem of WSN node deployment, this paper's researching approach is a process of optimizing the variable parameter set of object value function and then finding the optimal result.
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