Numerical experiments with two smoothing type-algorithms for nonlinear complementarity problems

Abstract

In this paper we deal with the numerical experiments of two smoothing descent-type algorithms for solving nonlinear complementarity problems (NCP). The first algorithm is due to Kanzow and the second one is due to Peng. These algorithms are both based on the reformulation of (NCP) as unconstrained minimization problems by using some smoothing merit functions including the so-called (NCP)-functions. Under suitable conditions they both showed that any stationary point of these problems are solutions of (NCP). For their numerical performances many strategies are used. Finally, these algorithms are applied to some problems of (NCP) found in the literature.

Keywords

• nonlinear complementarity problems
• smoothing descent-type optimization methods
• merit functions
• (NCP)-functions