Convexification techniques for linear complementarity constraints

Authors:
Trang T. Nguyen;Mohit Tawarmalani;Jean-Philippe P. Richard
Affiliations:
Department of Industrial and Systems Engineering, University of Florida;Krannert School of Management, Purdue University;Department of Industrial and Systems Engineering, University of Florida
Venue:
IPCO'11 Proceedings of the 15th international conference on Integer programming and combinatoral optimization
Year:
2011

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Abstract

We develop convexification techniques for linear programs with linear complementarity constraints (LPCC). In particular, we generalize the reformulation-linearization technique of [9] to complementarity problems and discuss how it reduces to the standard technique for binary mixed-integer programs. Then, we consider a class of complementarity problems that appear in KKT systems and show that its convex hull is that of a binary mixed-integer program. For this class of problems, we study further the case where a single complementarity constraint is imposed and show that all nontrivial facet-defining inequalities can be obtained through a simple cancel-and-relax procedure. We use this result to identify special cases where McCormick inequalities suffice to describe the convex hull and other cases where these inequalities are not sufficient