Combinatorial Benders' Cuts for Mixed-Integer Linear Programming

Mixed-Integer Programs (MIP's) involving logical implications modelled through big-M coefficients, are notoriously among the hardest to solve. In this paper we propose and analyze computationally an automatic problem reformulation of quite general applicability, aimed at removing the model dependency on the big-M coefficients. Our solution scheme defines a master Integer Linear Problem (ILP) with no continuous variables, which contains combinatorial information on the feasible integer variable combinations that can be "distilled" from the original MIP model. The master solutions are sent to a slave Linear Program (LP), which validates them and possibly returns combinatorial inequalities to be added to the current master ILP. The inequalities are associated to minimal (or irreducible) infeasible subsystems of a certain linear system, and can be separated efficiently in case the master solution is integer. The overall solution mechanism resembles closely the Benders'...

• Type: Journal
• Year: 2006
• Where: IOR
• Authors: Gianni Codato, Matteo Fischetti
• Keywords: Big-M Coefficients, IOR 2006, Original Mip, Original Mip Model