Artificial Intelligence - Special issue on knowledge representation
Constraint-directed techniques for scheduling alternative activities
Artificial Intelligence
Scheduling Algorithms
Constraint-Based Scheduling
Iterative Flattening: A Scalable Method for Solving Multi-Capacity Scheduling Problems
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Visopt ShopFloor: On the Edge of Planning and Scheduling
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Automatic Control of Workflow Processes Using ECA Rules
IEEE Transactions on Knowledge and Data Engineering
Nested Precedence Networks with Alternatives: Recognition, Tractability, and Models
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
Temporal Reasoning in Nested Temporal Networks with Alternatives
Recent Advances in Constraints
IBM ILOG CP Optimizer for Detailed Scheduling Illustrated on Three Problems
CPAIOR '09 Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Handling alternative activities in resource-constrained project scheduling problems
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Generating optimal stowage plans for container vessel bays
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Slack-based heuristics for constraint satisfaction scheduling
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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The paper presents a performance prediction and optimisation tool MAK€that allows users to model enterprises in a visually rich and intuitive way. The tool automatically generates a scheduling model describing all choices that users can do when optimising production. This model then goes to the Optimiser Module that generates schedules optimising on-time-in-full performance criterion while meeting the constraints of the firm and the customer demand. Finally, the Performance Manager Module shows the decision maker what is the best possible outcome for the firm given the inputs from the Enterprise Modeller. The Optimiser Module, which is the main topic of this paper, is implemented using constraint-based solving techniques with specific search heuristics for this type of problems. It demonstrates practical applicability of constraint-based scheduling --- one of the killer application areas of constraint programming, a technology originated from AI research.