large-scale unconstrained optimization 大规模无约束最优化问题
An adaptive filter trust region method for large scale unconstrained optimization is proposed.
提出一种解大规模无约束优化问题的自适应过滤信赖域法。
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。
Based on successive unconstrained programming methods, the successive bound constrained programming algorithms for large-scale process system optimization are studied in this paper.
基于非线性约束极小化的序列无约束方法，对大规模过程系统稳态优化的序列界约束方法进行了研究。
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