The Chaotic neural network model can be used to solve many multi-dimensioned, discrete, non-convex, nonlinear constrained optimization problems.
基于混沌神经网络模型可以有效地解决高维、离散、非凸的非线性约束优化问题。
In this paper, we consider the nonlinear inequality constrained optimization problems.
在本文中，我们考虑非线性不等式约束优化问题。
This paper presents an algorithm for nonlinear inequality constrained optimization problems which begins at any starting point.
本文给出非线性不等式约束最优化问题的一个初始点可任取的算法。
In this paper, a trust region algorithm for general nonlinear equality constrained optimization problems, is presented. The solution of their subproblems is easy.
对一般非线性等式约束最优化问题提出了一种信赖域算法，其子问题较易求解。
In this paper, a trust region algorithm for general nonlinear equality constrained optimization problems, is presented. The solution of their subproblems is easy.
对一般非线性等式约束最优化问题提出了一种信赖域算法，其子问题较易求解。
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