Error bounds for mixed integer linear optimization problems

We introduce computable a-priori and a-posteriori error bounds for optimality and feasibility of a point generated as the rounding of an optimal point of the LP relaxation of a mixed integer linear optimization problem. Treating the mesh size of integer vectors as a parameter allows us to study the effect of different ‘granularities’ in the discrete variables on the error bounds. Our analysis mainly bases on the construction of a so-called grid relaxation retract. Relations to proximity results and the integer rounding property are highlighted.

• Type: Journal
• Year: 2016
• Where: MP
• Authors: Oliver Stein
• Keywords: Information Technology, MP 2016