Sequential quadratic programming (SQP) method is an efficient method for solving smooth constrained optimization problems because of its fast convergence rate.
由于序列二次规划（SQP）算法具有快速收敛速度，所以它是求解光滑约束优化问题的有效方法之一。
Simulation results show that the proposed approach has fast convergence and good optimization ability, and is suitable for solving constrained optimization problems.
实验结果表明，新算法收敛速度快，寻优能力强，能很好地求解约束优化问题。
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。
To solve complex constrained optimization problems, we propose a new immune-genetic algorithm.
提出一种新的求解复杂约束优化问题的免疫遗传算法。
In this paper, we develop a trust region algorithm for convex constrained optimization problems.
本文我们考虑求解凸约束优化问题的信赖域方法。
We present an algorithm for the solution of general inequality constrained optimization problems.
我们提出一个一般不等式约束优化问题的求解算法。
BFGS algorithm is one of the most effective methods in solving the non-constrained optimization problems.
BFGS算法是解无约束优化问题的公认的最有效的算法之一。
In this paper, a trust region method with new conic model for linearly constrained optimization problems is proposed.
本文提出了一个解线性等式约束优化问题的新锥模型信赖域方法。
In this paper, a modified sequential quadratic program (SQP) for inequality constrained optimization problems is presented.
本文对不等式优化问题提出了一个修正的序列二次规划算法(SQP)。
A method for solving minimax problem is presented, which also can be used to solve linear or constrained optimization problems.
提出了一类解极小极大问题的熵函数法，这种方法也可用来解线性或约束优化问题。
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, we are concerned with the sequence quadratic programming (SQP) methods for solving constrained optimization problems.
本文研究求解约束最优化问题的序列二次规划算法(SQP算法)。
We propose a new trust region algorithm for special linear inequality constrained optimization problems with nonnegative bound constraints.
对一类带有非负边界约束的线性不等式约束优化问题进行了研究，提出了一种新的信赖域算法。
Image matching belongs to constrained optimization problems. Whether the system would converge to the global optimum is still an open problem.
图像匹配是一种约束最优化问题，系统是否收敛于全局最优值一直尚未解决。
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。
Simplified fuzzy reasoning method is introduced and a general method to solve constrained optimization problems in fuzzy expert system is proposed.
介绍了简化模糊推理方法，在此基础上提出了求解模糊专家系统中约束最优化问题的一般方法。
The aim of the dissertation is to study second order derivatives based differential equation approaches to nonconvex constrained optimization problems.
本文旨在研究求解非凸约束优化问题的基于二阶导数的微分方程方法。
Chapter 3 constructs a new generalized pattern search method for linear equality constrained optimization problems and gives the proofs of the global convergence.
第3章给出了广义模式搜索算法对线性等式约束最优化问题的一个新解法，并证明了这种算法的全局收敛性。
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。
To solve the equation constrained optimization problems, two new particle swarm optimization algorithms are presented. The experimental results show the algorithms are effective.
提出了求解有等式约束优化问题的两种新粒子群优化算法，数值试验结果表明，算法是有效的。
Novel constrained optimization evolutionary algorithm based on self-adaptive good points set (COEAAGP) is proposed to tackle constrained optimization problems (COPs) in this paper.
提出一种用于求解约束优化问题的自适应佳点集进化算法。
The productive method on the initial population is studied by using genetic algorithms to solve the constrained optimization problems. The study gives the new method of initial population evolution.
针对用遗传算法求解约束优化问题时，初始种群产生的方法进行了研究，提出了初始种群产生的一种新方法。
The productive method on the initial population is studied by using genetic algorithms to solve the constrained optimization problems. The study gives the new method of initial population evolution.
针对用遗传算法求解约束优化问题时，初始种群产生的方法进行了研究，提出了初始种群产生的一种新方法。
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