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基于中心路径大邻域上的一类非单调线性互补问题的高阶可行内点算法
引用本文:王浚岭.基于中心路径大邻域上的一类非单调线性互补问题的高阶可行内点算法[J].高等学校计算数学学报,2005,27(1):17-27.
作者姓名:王浚岭
作者单位:三峡大学理学院数学系,宜昌,443002
摘    要:In this paper a high-order feasible interior point algorithm for a class of nonmonotonic (P-matrix) linear complementary problem based on large neighborhoods of central path is presented and its iteration complexity is discussed.These algorithms are implicitly associated with a large neighborhood whose size may depend on the dimension of the problems. The complexity of these algorithms bound depends on the size of the neighborhood. It is well known that the complexity of large-step algorithms is greater than that of short- step ones. By using high-order power series (hence the name high-order algorithms), the iteration complexity can be reduced. We show that the upper bound of complexity for our high-order algorithms is equal to that for short-step algorithms.

关 键 词:非单调线性互补问题  高阶  内点算法  邻域  中心  路径

HIGH-ORDER FEASIBLE INTERIOR POINT ALGORITHMS FOR A CLASS OF NONMONOTONIC LINEAR COMPLEMENTARY PROBLEMS BASED ON LARGE NEIGHBORHOODS OF CENTRAL PATH
Wang Junling.HIGH-ORDER FEASIBLE INTERIOR POINT ALGORITHMS FOR A CLASS OF NONMONOTONIC LINEAR COMPLEMENTARY PROBLEMS BASED ON LARGE NEIGHBORHOODS OF CENTRAL PATH[J].Numerical Mathematics A Journal of Chinese Universities,2005,27(1):17-27.
Authors:Wang Junling
Abstract:In this paper a high-order feasible interior point algorithm for a class of nonmonotonic (P-matrix) linear complementary problem based on large neighborhoods of central path is presented and its iteration complexity is discussed. These algorithms are implicitly associated with a large neighborhood whose size may depend on the dimension of the problems. The complexity of these algorithms bound depends on the size of the neighborhood. It is well known that the complexity of large-step algorithms is greater than that of short- step ones. By using high-order power series (hence the name high-order algorithms), the iteration complexity can be reduced. We show that the upper bound of complexity for our high-order algorithms is equal to that for short-step algorithms.
Keywords:linear complementary problem  high-order feasible interior point algorithm  P-matrix  large neighborhood  iteration complexity  
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