A decomposition method in nonconvex mixed-integer programming

Abstract

We develop a finite decomposition method for solving a wide class of non-convex mixed-integer programming problems, including, e.g., mixed-integer concave minimization problems in separable form, the general quadratic integer problem, and problems arisen from the linear complementarity problem or from the fixed-charge network flow problem. The method proposed here belongs to the branch and bound approach, in which the branching procedure is the so-called 'mixed-inter polyhedral partition' actually performed by an 'integral rectangular partition', and the bound estimation is mainly performed by linear programming or linear network flow techniques, respectively. (orig.)Available from TIB Hannover: RR 1843(94-10) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman