Large-Neighborhood Infeasible Predictor–Corrector Algorithm for Horizontal Linear Complementarity Problems over Cartesian Product of Symmetric Cones

We present an infeasible interior-point predictor–corrector algorithm, based on a large neighborhood of the central path, for horizontal linear complementarity problem over the Cartesian product of symmetric cones. Throughout the paper, we assume that a certain property holds for the above-mentioned problem. This condition is equivalent to the property of sufficiency for the particular case of horizontal linear complementarity problem. The polynomial convergence is shown for the commutative class of search directions. We specialize our algorithm further by prescribing some scaling elements and also consider the case of feasible starting points. We believe this to be the first interior-point method based on large neighborhoods for the problem in consideration.

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