Constraint programming: an efficient and practical approach to solving the job-shop problem

Abstract

Recent improvements in constraint programming have made it possible to tackle hard problems in a practical way. Before this, these problems were solved only by specialized programs often complex to implement. Scheduling problems and more especially the job-shop problem belong to this class. In this paper we explain a relatively simple constraint system, which enables us to solve 10 × 10 problems efficiently. The method described here, based on evaluations which come as close as possible to release and due dates of jobs to be scheduled, requires no prior knowledge of the problem being processed, in particular, no bounds over optimum value (consequently no specific algorithm to find approximate solutions). We also comment on the results of experiments on known problems. As far as we know, the system outlined here is the only one that, using just constraint solving and an exhaustive enumeration strategy, can completely solve orb3[AC91] in less than half an hour computational time.