An assignment-based continuous-time MILP model for the resource-constrained project scheduling problem

The widely studied resource-constrained project scheduling problem consists of determining the start times for a set of precedence-related project activities requiring time and scarce resources during execution such that the total project duration is minimized. In the literature, in addition to a large variety of specific solution approaches, various mixed-integer linear programming (MILP) models have been proposed for this problem. We present a novel MILP model that is based on explicit assignment and sequencing variables; we enhance the performance of the model by eliminating some symmetric solutions from the search space and by modifying the sequencing constraints for pairs of activities that cannot be processed in parallel. Our computational results for four standard test sets from the literature indicate that this novel model outperforms two state-of-the-art models, particularly when resources are very scarce.