نتایج جستجو برای: interior search algorithm

تعداد نتایج: 1012322  

Journal: :SIAM Journal on Optimization 1998
Jie Sun Gongyun Zhao

An interior point method is proposed to solve variational inequality problems for monotone functions and polyhedral sets. The method has the following advantages. 1. Given an initial interior feasible solution with duality gap 0 , the algorithm requires at most On log(0 ==)] iterations to obtain an-optimal solution. 2. The rate of convergence of the duality gap is q-quadratic. 3. At each iterat...

Journal: :RAIRO - Operations Research 2008
Mohamed El Ghami Kees Roos

In this paper we present a generic primal-dual interior point methods (IPMs) for linear optimization in which the search direction depends on a univariate kernel function which is also used as proximity measure in the analysis of the algorithm. The proposed kernel function does not satisfy all the conditions proposed in [2]. We show that the corresponding large-update algorithm improves the ite...

H. Mansouri

In this paper, we present a new path-following interior-point algorithm for -horizontal linear complementarity problems (HLCPs). The algorithm uses only full-Newton steps which has the advantage that no line searchs are needed. Moreover, we obtain the currently best known iteration bound for the algorithm with small-update method, namely, , which is as good as the linear analogue.

2014
B. KHEIRFAM M. MOSLEMI

In this paper, we propose a large-update interior-point algorithm for linear optimization based on a new kernel function. New search directions and proximity measure are defined based on this kernel function. We show that if a strictly feasible starting point is available, then the new algorithm has log iteration complexity.

2005
Gyeong-mi Cho

In this paper we propose a new large-update primal-dual interior point algorithm for P∗(κ) linear complementarity problems (LCPs). We generalize the analysis of BER’s primal-dual interior point algorithm for LP to P∗(κ) LCPs. New search directions and proximity measures are proposed based on a new kernel function which has linear growth term. We showed that if a strictly feasible starting point...

Journal: :J. Comput. Physics 2010
Heyu Huang Xiaochao Qu Jimin Liang Xiaowei He Xueli Chen Da'an Yang Jie Tian

We propose a novel multi-phase level set algorithm for solving the inverse problem of bioluminescence tomography. The distribution of unknown interior source is considered as piecewise constant and represented by using multiple level set functions. The localization of interior bioluminescence source is implemented by tracing the evolution of level set function. An alternate search scheme is inc...

Journal: :the modares journal of electrical engineering 2015
mahdi sojoodi farzad soleymani

in this paper, we describe our implementation of an interior point algorithm for large scale systems. first we identify system with small and medium methods convex optimization, then we use interior point method for identification. finally we offer an interior point method that uses nonlinear cost function and see that we achieve a good trade-off between error and cpu time. actually, in this pa...

Journal: :bulletin of the iranian mathematical society 2011
m. salahi

2013
Guoqiang Wang Minmin Li Yujing Yue Xinzhong Cai

In this paper, we give a unified analysis for both largeand small-update interior-point methods for the Cartesian P∗(κ )-linear complementarity problem over symmetric cones based on a finite barrier. The proposed finite barrier is used both for determining the search directions and for measuring the distance between the given iterate and theμ-center for the algorithm. The symmetry of the result...

Journal: :bulletin of the iranian mathematical society 2014
behrouz kheirfam n. mahdavi-amiri

‎a full nesterov-todd (nt) step infeasible interior-point algorithm‎ ‎is proposed for solving monotone linear complementarity problems‎ ‎over symmetric cones by using euclidean jordan algebra‎. ‎two types of‎ ‎full nt-steps are used‎, ‎feasibility steps and centering steps‎. ‎the‎ ‎algorithm starts from strictly feasible iterates of a perturbed‎ ‎problem‎, ‎and, using the central path and feasi...

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