Parallelization of the FICO Xpress-Optimizer

Many optimization problems arising in practice can be modeled as mixed integer programs (MIPs). In this paper, we present the new parallelization concept for the state-of-the-art MIP solver FICO Xpress-Optimizer. A natural precondition to achieving reasonabling speedups from parallelization is maintaining a high workload of the available computational resources. At the same time, reproducibility and reliability are key requirements for mathematical optimization software; solvers like the FICO Xpress-Optimizer are expected to be deterministic. The resulting synchronization latencies render the goal of a satisfying workload a challenge in itself.