信阳师范学院学报（自然科学版）
信暘師範學院學報（自然科學版）
신양사범학원학보（자연과학판）
JOURNAL OF XINYANG NORMAL UNIVERSITY(NATURAL SCIENCE EDITION)
2013年
3期
324-326
,共3页
无约束优化%曲线搜索%全局收敛%线性收敛速度
無約束優化%麯線搜索%全跼收斂%線性收斂速度
무약속우화%곡선수색%전국수렴%선성수렴속도
unconstrained optimization%curve search%global convergence%linear convergence rate
提出一个新的求解无约束优化问题的超记忆梯度法。该算法在每步迭代中充分利用前面迭代点的信息产生下降方向，利用曲线搜索产生步长，并且在每步迭代中不需计算和存储矩阵，适于求解大规模优化问题。在较弱的条件下证明了算法具有全局收敛性和线性收敛速度。数值实验表明该算法是有效的。
提齣一箇新的求解無約束優化問題的超記憶梯度法。該算法在每步迭代中充分利用前麵迭代點的信息產生下降方嚮，利用麯線搜索產生步長，併且在每步迭代中不需計算和存儲矩陣，適于求解大規模優化問題。在較弱的條件下證明瞭算法具有全跼收斂性和線性收斂速度。數值實驗錶明該算法是有效的。
제출일개신적구해무약속우화문제적초기억제도법。해산법재매보질대중충분이용전면질대점적신식산생하강방향，이용곡선수색산생보장，병차재매보질대중불수계산화존저구진，괄우구해대규모우화문제。재교약적조건하증명료산법구유전국수렴성화선성수렴속도。수치실험표명해산법시유효적。
A new super-memory gradient method for solving unconstrained optimization problems was proposed .A new search direction was generated by using the current and previous multi -step iterative information in the proposed method, and the step-size at each iteration was defined by a curve search rule , which can be used to solve large scale unconstrained optimization problems because it avoids the computation and storage of some matrices .Furthermore, the global convergence and the convergence rate of the new algorithm were proved under some weak conditions .Finally, numerical results showed that the proposed algorithm is effective .
