Just-in-time scheduling with constraint programming

Abstract

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. Copyright © 2009, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.