Mixed integer-linear formulations of cumulative scheduling constraints

This talk introduce two mixed integer linear programming (MILP) models
for the cumulative scheduling constraint and associated pre-processing
filters. We compare standard solver performance for these models on
three sets of problems and for two of them, where tasks have unitary
resource consumption, we also compare them with two models based on a
geometric placement constraint. In the experiments, the solver
performance of one of the cumulative models, is clearly the best and is
also shown to scale very well for a large scale industrial
transportation scheduling problem.