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Saddle-Point Criteria in an η-Approximation Method for Nonlinear Mathematical Programming Problems Involving Invex Functions

机译:包含凸函数的非线性数学规划问题的η逼近方法中的鞍点准则

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摘要

In this paper, the η-approximation method introduced by Antczak (Ref. 1) for solving a nonlinear constrained mathematical programming problem involving invex functions with respect to the same function η is extended. In this method, a so-called η-approximated optimization problem associated with the original mathematical programming problems is constructed; moreover, an η-saddle point and an η-Lagrange function are defined. By the help of the constructed η-approximated optimization problem, saddle-point criteria are obtained for the original mathematical programming problem. The equivalence between an η-saddle point of the η-Lagrangian of the associated η-approximated optimization problem and an optimal solution in the original mathematical programming problem is established.
机译:在本文中,扩展了由Antczak(参考文献1)引入的η逼近方法,用于解决相对于同一函数η的涉及凸函数的非线性约束数学规划问题。在这种方法中,构造了与原始数学程序设计问题相关的所谓的η近似优化问题。此外,定义了一个鞍点和一个拉格朗日函数。借助于构造的η近似优化问题,可以为原始数学规划问题获得鞍点准则。建立了相关的η近似优化问题的η-Lagrangian的η鞍点与原始数学规划问题的最优解之间的等价关系。

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