1) constrained optimization problem
约束优化问题
1.
Immune chaotic algorithm for constrained optimization problems;
约束优化问题的免疫混沌算法
2.
Particle swarm optimization algorithm of equation constrained optimization problem;
有等式约束优化问题的粒子群优化算法
3.
Hybrid algorithm based on particle swarm optimization for solving constrained optimization problems;
一种基于粒子群算法求解约束优化问题的混合算法
2) constrained optimization
约束优化问题
1.
The new technique treats constrained optimization as a two-objective optimization.
新的演化算法将约束优化问题转换成两个目标优化问题,其中一个为原问题的目标函数,另一个为违反约束条件的程度函数。
2.
In trying to solve constrained optimization problems using genetic algorithms, the method to handle the constraints is the key factor to success.
在用遗传算法求解约束优化问题时 ,处理好约束条件是取得好的优化效果的关键 。
3.
Sequential Quadratic Programming(SQP) Algorithm is one of the most effective methods for solving nonlinear constrained optimization problems.
序列二次规划(SQP)算法是目前公认的求解非线性约束优化问题的最有效的算法之一。
3) constrained optimization problems
约束优化问题
1.
Study on the productive method on the initial population by using genetic algorithms to solve the constrained optimization problems;
用遗传算法求解约束优化问题时初始种群产生方法的探讨
2.
Artificial Fish-Swarm Algorithm for solving constrained optimization problems;
求解约束优化问题的人工鱼群算法
3.
Real-coded immune-tabu hybrid algorithm to solve constrained optimization problems
约束优化问题的实数制免疫-禁忌混合算法
4) unconstrained optimization problem
无约束优化问题
1.
One Method for Unconstrained Optimization Problems;
一种无约束优化问题的算法
2.
A new conjugate gradient method is proposed for solving unconstrained optimization problems to update and prove the method with Wolfe line search convergece globally.
提出了求解无约束优化问题的一种新的共轭梯度法,修正了βk,并在Wolfe线搜索下证明了它的全局收敛性。
3.
Then the simplex algorithm is applied for the solution of unconstrained optimization problem.
针对球约束凸二次规划问题,利用Lagrange对偶将其转化为无约束优化问题,然后运用单纯形法对其求解,获得原问题的最优解。
5) unconstrained optimization problems
无约束优化问题
1.
This paper,based on BFGS method,presents an artificial neural network model for unconstrained optimization problems,and some stability properties of the neural network are discussed.
提出了一种基于BFGS算法的求解无约束优化问题的人工神经网络模型,并对该模型的稳定性作了理论分析。
2.
In this thesis,the equivalence between a class of variational inequalities problems,which are in condition of some generalized convexity,and a class of unconstrained optimization problems is mainly studied.
本文主要研究了一类变分不等式问题在满足一定的广义凸性的前提下,与一类无约束优化问题的等价性关系。
3.
It can be applied to construct limited memory quasi-Newton method for unconstrained optimization problems when a vector is specially chosen.
提出一族紧凑格式的拟牛顿矩阵修正公式,适当选择其中某个向量情况下,该族可以很方便的用于构造求解大型无约束优化问题的有限存储拟牛顿算法。
6) LC~1 constrained optimization problem
LC1约束优化问题
1.
A construct algorithm was proposed,which can confirm globally and superlinear convergence of the inexact generalized Newtion s method for nonlinear LC~1 constrained optimization problem,and the problem was solved through solving semismooth equations reformulated from KKT conditions.
通过将非线性LC1约束优化问题的KKT条件转化成半光滑方程组,提