In this paper we analyze computational performance of dual trigonometric generating functions on some integer programming problems. We show that if the number of equality constraints is fixed, then this technique allows to solve the problems in time, which is polynomial in the dimension of the...

In this paper, we propose a second-order corrector interior-point algorithm for semidefinite programming (SDP). This algorithm is based on the wide neighborhood. The complexity bound is $${O(\sqrt{n}L)}$$ for the Nesterov-Todd direction, which coincides with the best known complexity results for...

In this paper, we propose a second-order corrector interior-point algorithm for semidefinite programming (SDP). This algorithm is based on the wide neighborhood. The complexity bound is <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$${O(\sqrt{n}L)}$$</EquationSource> </InlineEquation> for the Nesterov-Todd direction, which coincides with the best known complexity results...</equationsource></inlineequation>

In a computer network where nodes can fail, multipath transmission can be used to increase the probability of successful transmission. However, even multipath transmission has a probability of failure, which depends on the selected paths. Hence, estimating this probability of failure is of great...

In this paper, we propose a second order interior point algorithm for symmetric cone programming using a wide neighborhood of the central path. The convergence is shown for commutative class of search directions. The complexity bound is $${O(r^{3/2}\,\log\epsilon^{-1})}$$ for the NT methods, and...

In this paper, we propose a second order interior point algorithm for symmetric cone programming using a wide neighborhood of the central path. The convergence is shown for commutative class of search directions. The complexity bound is <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$${O(r^{3/2}\,\log\epsilon^{-1})}$$</EquationSource> </InlineEquation> for the NT methods,...</equationsource></inlineequation>

Recently, using the framework of self-regularity, Salahi in his Ph.D. thesis proposed an adaptive single step algorithm which takes advantage of the current iterate information to find an appropriate barrier parameter rather than using a fixed fraction of the current duality gap. However, his...

Kernel functions play an important role in interior point methods (IPMs) for solving linear optimization (LO) problems to define a new search direction. In this paper, we consider primal-dual algorithms for solving Semidefinite Optimization (SDO) problems based on a new class of kernel functions...