High performance integer optimization for crew scheduling

Performance aspects of a Lagrangian relaxation based heuristic for solving large 0-1 integer linear programs are discussed. In particular, we look at its application to airline and railway crew scheduling problems. We present a scalable parallelization of the original algorithm used in production at Carmen Systems AB, G\"oteborg, Sweden, based on distributing the variables and a new sequential \emph{active set strategy} which requires less work and is better adapted to the memory hierachy properties of modern RISC processors. The active set strategy can even be parallelized on networks of workstations