Constraint satisfaction in logic programming
Constraint satisfaction in logic programming
An algorithm for solving the job-shop problem
Management Science
Communications of the ACM
Constraint satisfaction using constraint logic programming
Artificial Intelligence - Special volume on constraint-based reasoning
Constraint arithmetic on real intervals
Constraint logic programming
A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Improved CLP scheduling with task intervals
Proceedings of the eleventh international conference on Logic programming
A New Approach to Computing Optimal Schedules for the Job-Shop Scheduling Problem
Proceedings of the 5th International IPCO Conference on Integer Programming and Combinatorial Optimization
Generating Feasible Schedules for a Pick-Up and Delivery Problem
CP '98 Proceedings of the 4th International Conference on Principles and Practice of Constraint Programming
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Visopt ShopFloor: On the Edge of Planning and Scheduling
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
A Position-Based Propagator for the Open-Shop Problem
CPAIOR '07 Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Computing leximin-optimal solutions in constraint networks
Artificial Intelligence
Visopt shopfloor: going beyond traditional scheduling
ERCIM'02/CologNet'02 Proceedings of the 2002 Joint ERCIM/CologNet international conference on Constraint solving and constraint logic programming
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In this paper, we deal with the famous job-shop schedulingproblem, which has been being a constant subject of study formany years due to its high computational complexity (NP-hardin the strong sense). We present a permutation-based scheme forsolving the problem, which in the abstraction level differs fromthe classical one of Jacques Carlier and Eric Pinson.In particular, we specify the differences both in the fashionof stating the constraints (the use of the generalized sortingconstraint) and in the search strategy (splitting intervals oftask orders). We will first give a constraint program for solvingthe problem, which involves only primitive constraints and whichis clean and simple to understand. We then study some specialtechniques based on testing variable bounds that allow us tosolve two hard instances la21 and la38.These two instances have been open problems recommended in apaper of David Applegate and William Cook in 1991.