A mathematical for periodic scheduling problems
SIAM Journal on Discrete Mathematics
On the conversion between non-binary constraint satisfaction problems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Algorithms for Distributed Constraint Satisfaction: A Review
Autonomous Agents and Multi-Agent Systems
The Distributed Constraint Satisfaction Problem: Formalization and Algorithms
IEEE Transactions on Knowledge and Data Engineering
A Survey of Optimization Models for Train Routing and Scheduling
Transportation Science
Distributed Constraint Satisfaction Algorithm for Complex Local Problems
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Simultaneous disruption recovery of a train timetable and crew roster in real time
Computers and Operations Research
Introduction: special issue on distributed constraint satisfaction
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Asynchronous aggregation and consistency in distributed constraint satisfaction
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Domain-dependent distributed models for railway scheduling
Knowledge-Based Systems
Towards an abstract recursive agent
Integrated Computer-Aided Engineering
DFS-tree based heuristic search
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
Distributed CSPs: why it is assumed a variable per agent?
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
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A distributed constraint satisfaction problem (DisCSP) is a CSP in which variables and constraints are distributed among multiple automated agents. Many researchers have developed techniques for solving DisCSPs. They assume for simplicity that each agent has exactly one variable. For real planning and scheduling problems, these techniques require a large number of messages passing among agents, so these problems are very difficult to solve. In this paper, we present a general distributed model for solving real-life scheduling problems. This distributed model is based on the idea of holonic systems. Furthermore, we propose some guidelines for distributing large-scale problems. Finally, we present two case studies in which two scheduling problems are distributed by using our model.