Verifying Integer Programming Results

A computational status update for exact rational mixed integer programming

“…We see an increase in solving time of 56.3% on fpeasy, 22% on numdiff, and of 46% on miplib. This confirms the measurements presented in [13]. The increase is explained mostly by the effort to keep track of the disjunctions created during tree search and print the exact dual multipliers, and in part by an increase in dual bounding time.…”

“…Here, we consider running times for both the solver and the certificate checker, as well as the overhead in the safe dual bounding methods introduced through enabling certificates. This provides an update for the analysis in [13], which was limited to the two bounding methods project-and-shift and exact LP.…”

“…The possibility to log certificates as presented in [13] is available in the new framework and is extended to also work when the dual bounding method bound-shift is active. Presolving must currently be disabled, since PaPILO does not yet support generation of certificates.…”

“…Moreover, we integrate the exact LP solver SoPlex, which follows the recently developed scheme of LP iterative refinement [25], we extend the logging of certificates in the recently developed VIPR format to all available dual bounding methods [13],…”

A Computational Status Update for Exact Rational Mixed Integer Programming

“…Moreover, we integrate the exact LP solver SoPlex, which follows the recently developed scheme of LP iterative refinement [23], we extend the logging of certificates in the recently developed VIPR format to all available dual bounding methods [13], and produce a thoroughly revised implementation of the original framework [16], which improves multiple technical details. Our computational study evaluates the performance of the new algorithmic aspects in detail and indicates a significant overall speedup compared to the original framework.…”