摘要
§1.引言 考虑一般非线性规划问题: (P)min{f(x)|x∈S},其中S?R^n为一非空闭集,f:R^n→R^1。 求解(P)的下降算法的基本思想是:在当前点x_k∈S处。
In this paper, by studying some curvilinear search methods and 'accelarating' algorithms.in nonlinear programing, we present the concept of quasi-descent method and extend the im-portant lemma [1, Lemma 3] to quasi-feasible direction methods. On this basis, we give analgorithm model of quasi-feasible direction methods for inequality constrained optimizationand show its global convergence under weak conditions. The paper unifies and extends the co-mmon feasible direction methods on a larger scale. As a special case of our model, we obtaina class of new supermemory descent methods for constrained optimization.
出处
《应用数学学报》
CSCD
北大核心
1993年第1期47-53,共7页
Acta Mathematicae Applicatae Sinica
基金
华中理工大学青年科学基金
