摘要

In this paper we propose a new class of Mehrotra-type predictor-corrector algorithm for the monotone linear complementarity problems (LCPs). At each iteration, the method computes a corrector direction in addition to the Ai-Zhang direction (SIAM J Optim 16: 400-417, 2005), in an attempt to improve performance. Starting with a feasible point (x(0), s(0)) in the wide neighborhood N(tau, beta), the algorithm enjoys the low iteration bound of O(root nL), where n is the dimension of the problem and L = log (x(0))(T) s(0)/epsilon with epsilon the required precision. We also prove that the new algorithm can be specified into an easy implementable variant for solving the monotone LCPs, in such a way that the iteration bound is still O(root nL). Some preliminary numerical results are provided as well.