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约束优化

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A new method for dynamic nonlinear constrained optimization problems is presented.

研究了一类动态非线性约束优化问题的新解法。

Trust region method is a kind of efficient and robust method to solve general constrained optimization.

对于一般的约束优化问题,信赖域方法是一种比较有效的方法。

The key to investigating optimization problems, especially constrained optimization problems, is to design efficient algorithm for solving it.

最优化问题特别是约束优化问题研究的一个核心是设计有效的算法。

In the third chapter we discuss LC1 constrained optimization problem .

第三章讨论了LC~1约束优化问题。

A new adaptive penalty function is presented to solve constrained optimization problems.

提出一种新的自适应惩罚函数法,用来处理约束优化问题。

A new hybrid genetic algorithm was presented to handle constrained optimization.

提出了一种求解约束优化问题的混合遗传算法。

Constrained optimization problems are mathematical programming problems frequently encountered in the disciplines of science and engineering application.

约束优化问题是科学和工程应用领域经常会遇到的一类数学规划问题。

Experimental results indicate that the IPSO is robust and efficient in solving nonlinear constrained optimization problems.

对比数值实验结果表明,该算法能够有效、稳定地求解非线性约束优化问题。

Furthermore, the first-order optimality condition and its equivalent reformulations for generalized semi-infinite max-min programming with a non-compact set are presented using the lower-Hadamard directional derivative and subdifferential.2. Chapter 3 studies the gradient-type methods for unconstrained optimization problems. Section 1 proposes a new class of three-term memory gradient methods. The global convergence property of the method is established. Furthermore, in order to improve the convergence property of the method, a new class of memory gradient projection methods is presented with the property that the whole sequence of iterates converges to a solution to the problem under the conditions such as pseudo-convexity and continuous differentiability of objective function. In section 2, two new classes of methods, called gradient-type method with perturbations and hybrid projection method with perturbations, are proposed. In these methods, non-monotone line search technique is employed, which makes them easily executed in computer.

第3章研究了无约束优化问题的梯度型算法,第1节提出了一类新的三项记忆梯度算法,讨论了算法的全局收敛性,进一步提出了一类新的具有更好收敛性质的记忆梯度投影算法,并证明了该算法在函数伪凸的情况下具有整体收敛性,第2节在非单调步长搜索下提出了带扰动项的梯度型算法及其混合投影算法,这两类算法的一个重要特征就是步长采用线搜索确定而不象许多文献中那样要求步长趋于零,这样更容易在计算机上实现,在较弱的条件下证明了这些算法的全局收敛性,数值算例表明了算法的有效性。

In this paper, we give a new class of adaptive nonmonotone spectral projected gradient technique for convex constrained optimization.

该文给出了求解凸约束优化的一类新的自适应非单调谱投影梯度法,主要思想是通过引入具有自适应性的权重参数,使算法在迭代过程中能自动调节非单调策略。

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