The conjugate gradient method is one of the most efficient methods for solving unconstrained optimization problems.
共轭梯度法是求解无约束优化问题的一类有效方法。
The idea of conjugate gradient path in unconstrained optimization irradiates us to use this method for solving the linear equality optimization subject to bounds on variables.
无约束优化问题的共轭梯度路径构造的思想启迪我们用其来解带线性等式约束和有界变量约束的优化问题。
Pr conjugate gradient method is one of the efficient methods for solving large scale unconstrained optimization problems, however, its global convergence has not been solved for a long time.
PR共轭梯度法是求解大型无约束优化问题的有效算法之一，但是算法的全局收敛性在理论上一直没有得到解决。
Conjugate gradient method is an efficient method in solving problems with unconstrained optimization, which is especially efficient in dealing large dimension.
共轭梯度法是求解大规模无约束优化问题的一种有效方法。
Finally, wo present a descent method for solving VIP and study a global error bound for unconstrained optimization reformulation in order to discuss the convergence of itinerative method.
最后给出了一个求解的下降法，并考察了最优化问题的误差界问题，以分析叠代法的收敛性。
Particle swarm optimization (PSO) algorithm is one of the most powerful methods for solving unconstrained and constrained global optimization problems.
粒子群优化算法(PSO)是一种有效的随机全局优化技术。
Particle swarm optimization (PSO) algorithm is one of the most powerful methods for solving unconstrained and constrained global optimization problems.
粒子群优化算法(PSO)是一种有效的随机全局优化技术。
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