On a Homogeneous Algorithm for the Monotone Complementarity problem

Erling D. Andersen and Yinyu Ye

We present a generalization of a homogeneous self-dual linear programming (LP) algorithm to solving the monotone complementarity problem (MCP). The algorithm does not need to use any ``big-M'' parameter or two-phase method, and it generates either a solution converging towards feasibility and complementarity simultaneously or a certificate proving infeasibility. Moreover, if the MCP is polynomially solvable with an interior feasible starting point, then it can be polynomially solved without using or knowing such information at all. To our knowledge, this is the first interior-point and infeasible-starting algorithm that possesses these desired features for solving the MCP. Preliminary computational results are presented.