The Linear Complementarity Problem (LCP) consists of finding vectors z∈Rn and w∈Rn such that w=q+Mz, z∈0, w∈0 and zTw=0, where q∈Rn and M is a square matrix of order n. The LCP is strictly convex if its matrix M is (symmetric or unsymmetric) positive definite. In this paper the use of (single and block) principal pivoting algorithms for the solution of large-scale strictly convex LCPs is discussed. A computational study indicates that block principal pivoting algorithms are highly recommendable to solve these LCPs and are in general superior over other alternative techniques.
