Just-In-Time Scheduling with Constraint Programming

This paper considers Just-In-Time Job-Shop Scheduling, in which each activity has an earliness and a tardiness cost with respect to a due date. It proposes a constraint programming approach, which includes a novel filtering algorithm and dedicated heuristics. The filtering algorithm uses a machine relaxation to produce a lower bound that can be obtained by solving a Just-In-Time Pert problem. It also includes pruning rules which update the variable bounds and detect precedence constraints. The paper presents experimental results which demonstrate the effectiveness of the approach over a wide range of benchmarks.

• Type: Conference
• Year: 2009
• Where: AIPS
• Authors: Jean-Noël Monette, Yves Deville, Pascal Van Hentenryck
• Keywords: AIPS 2009, Artificial Intelligence, Constraint Programming Approach, Just-In-Time Job-Shop Scheduling, Just-In-Time Pert Problem