A new polynomial-time algorithm for linear programming
Combinatorica
On adaptive-step primal-dual interior-point algorithms for linear programming
Mathematics of Operations Research
Mathematical Programming: Series A and B
The largest step path following algorithm for monotone linear complementarity problems
Mathematical Programming: Series A and B
Infeasible-interior-point paths for sufficient linear complementarity problems and their analyticity
Mathematical Programming: Series A and B
A smoothing Gauss-Newton method for the generalized HLCP
Journal of Computational and Applied Mathematics - Special issue on nonlinear programming and variational inequalities
A Full-Newton Step O(n) Infeasible Interior-Point Algorithm for Linear Optimization
SIAM Journal on Optimization
Journal of Computational and Applied Mathematics
Simplified O(nL) infeasible interior-point algorithm for linear optimization using full-Newton steps
Optimization Methods & Software
Polynomial interior-point algorithms for P*(K) horizontal linear complementarity problem
Journal of Computational and Applied Mathematics
Corrector-predictor methods for sufficient linear complementarity problems
Computational Optimization and Applications
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In this paper an interior-point algorithm for P *(驴) horizontal linear complementarity problems is proposed that uses new search directions. The theoretical complexity of the new algorithm is calculated. It is investigated that the proposed algorithm has quadratically convergent with polynomial iteration complexity $O((1+\kappa)\sqrt{n}\log\frac{n}{\varepsilon})$ , coincide with the best known iteration bound for P *(驴) horizontal linear complementarity problems.