A two-stage parallel branch and bound algorithm for mixed integer programs

Mixed integer programming (MIP) models are extensively used to aid strategic and tactical decision making in many business sectors. Solving MIP models is a computationally intensive process and there is a need to develop solution approaches that enable larger models to be solved within acceptable timeframes. In this paper, we describe the implementation of a two-stage parallel branch and bound (PB & B) algorithm for MIP. In stage 1 of the algorithm, a multiple heuristic search is implemented in which a number of alternative search trees are investigated using a forest search in the hope of finding a good solution quickly. In stage 2, the search is reorganized so that the branches of a chosen tree are investigated in parallel. A new heuristic is introduced, based on a best projection criterion, which evaluates alternative B & B trees in order to choose one for investigation in stage 2 of the algorithm. The heuristic also serves as a way of implementing a quality load balancing scheme for stage 2 of the algorithm. The results of experimental investigations are reported for a range of models taken from the MIPLIB library of benchmark problems.