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。
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。
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