caa a22 4500 475769155 CHVBK 20180406123615.0 cr unu---uuuuu 170329e20000101xx s 000 0 eng 10.1007/s101079900111 doi (NATIONALLICENCE)springer-10.1007/s101079900111 A non-interior predictor-corrector path following algorithm for the monotone linear complementarity problem [Elektronische Daten] [Jim Burke, Song Xu] Abstract. : We present a predictor-corrector non-interior path following algorithm for the monotone linear complementarity problem based on Chen-Harker-Kanzow-Smale smoothing techniques. Although the method is modeled on the interior point predictor-corrector strategies, it is the first instance of a non-interior point predictor-corrector algorithm. The algorithm is shown to be both globally linearly convergent and locally quadratically convergent under standard hypotheses. The approach to global linear convergence follows the authors' previous work on this problem for the case of (P 0+R 0) LCPs. However, in this paper we use monotonicity to refine our notion of neighborhood of the central path. The refined neighborhood allows us to establish the uniform boundedness of certain slices of the neighborhood of the central path under the standard hypothesis that a strictly positive feasible point exists. Springer-Verlag Berlin Heidelberg, 2000 Mathematics Subject Classification (1991): 90C33 nationallicence Burke Jim Department of Mathematics, University of Washington, Seattle WA 98195, USA, US aut Xu Song University of Waterloo, Department of Combinatorics and Optimization, Faculty of Mathematics, Waterloo, Ontario N2L 3G1, Canada, CA aut https://doi.org/10.1007/s101079900111 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s101079900111 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Burke Jim Department of Mathematics, University of Washington, Seattle WA 98195, USA, US aut NATIONALLICENCE 700 1- Xu Song University of Waterloo, Department of Combinatorics and Optimization, Faculty of Mathematics, Waterloo, Ontario N2L 3G1, Canada, CA aut Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer