‎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...

We present an interior point method for the min-cost flow problem that uses arc contractions and deletions to steer clear from the boundary of the polytope when path-following methods come too close. We obtain a randomized algorithm running in expected Õ(m) time that only visits integer lattice points in the vicinity of the central path of the polytope. This enables us to use integer arithmetic...

We present implicit surface reconstruction algorithms for point clouds. We view the implicit surface reconstruction as a three dimensional binary image segmentation problem that segments the entire space R3 or the computational domain into an interior region and an exterior region while the boundary between these two regions fits the data points properly. The key points with using an image segm...

we present a modified version of the infeasible-interior- we present a modified version of the infeasible-interior-point algorithm for monotone linear complementary problems introduced by mansouri et al. (nonlinear anal. real world appl. 12(2011) 545--561). each main step of the algorithm consists of a feasibility step and several centering steps. we use a different feasibility step, which targ...

We study two different decomposition algorithms for the general (nonconvex) partially separable nonlinear program (PSP): bilevel decomposition algorithms (BDAs) and Schur interior-point methods (SIPMs). BDAs solve the problem by breaking it into a master problem and a set of independent subproblems, forming a type of bilevel program. SIPMs, on the other hand, apply an interior-point technique t...

We describe and analyze an interior-point method to decide feasibility problems of second-order conic systems. A main feature of our algorithm is that arithmetic operations are performed with finite precision. Bounds for both the number of arithmetic operations and the finest precision required are exhibited.