We combine mixed integer linear programming (MILP) and constraint programming (CP) to minimize tardiness in planning and scheduling. Tasks are allocated to facilities using MILP and scheduled using CP, and the two are linked via logic-based Benders decomposition. We consider two objectives: minimizing the number of late tasks, and minimizing total tardiness. Our main theoretical contribution is a relaxation of the cumulative scheduling subproblem, which is critical to performance. We obtain substantial computational speedups relative to the state of the art in both MILP and CP. We also obtain much better solutions for problems that cannot be solved to optimality. We address a planning and scheduling problem that occurs frequently in manufacturing and supply chain contexts. Tasks must be assigned to facilities and scheduled on each facility subject to release dates and due dates. Tasks assigned to a given facility may run in parallel if desired, subject to a resource constraint (cumulat...
John N. Hooker