Mathematics of Operations Research
On quadratic and OnL convergence of a predictor-corrector algorithm for LCP
Mathematical Programming: Series A and B
A superquadratic infeasible-interior-point method for linear complementarity problems
Mathematical Programming: Series A and B
On the extended linear complementarity problem
Mathematical Programming: Series A and B
Convergence of interior point algorithms for the monotone linear complementarity problem
Mathematics of Operations Research
Mathematics of Operations Research
Mathematics of Operations Research
High Order Infeasible-Interior-Point Methods for Solving Sufficient Linear Complementarity Problems
Mathematics of Operations Research
Infeasible-interior-point paths for sufficient linear complementarity problems and their analyticity
Mathematical Programming: Series A and B
Mathematics of Operations Research
SIAM Journal on Optimization
SIAM Journal on Optimization
Computational Optimization and Applications
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A simple and unified analysis is provided on the rate of local convergence for a class of high-order-infeasible-path-following algorithms for the P_*-linear complementarity problem (P_*-LCP). It is shown that therate of local convergence of a ν-order algorithm with a centering step is ν + 1 if there is a strictly complementary solution and(ν + 1)/2 otherwise. For the ν-order algorithm without thecentering step the corresponding rates are ν and ν/2, respectively. The algorithm without a centering step does not follow the fixed traditional central path.Instead, at each iteration, it follows a new analyticpath connecting the current iterate with an optimal solution to generate the next iterate. An advantage of this algorithm is that it does not restrict iterates in a sequence of contracting neighborhoods of the central path.