Network-based heuristics for constraint-satisfaction problems
Artificial Intelligence
A mathematical for periodic scheduling problems
SIAM Journal on Discrete Mathematics
Agent theories, architectures, and languages: a survey
ECAI-94 Proceedings of the workshop on agent theories, architectures, and languages on Intelligent agents
A multilevel algorithm for partitioning graphs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
A parallel algorithm for multilevel graph partitioning and sparse matrix ordering
Journal of Parallel and Distributed Computing
Algorithms for Distributed Constraint Satisfaction: A Review
Autonomous Agents and Multi-Agent Systems
A Survey of Optimization Models for Train Routing and Scheduling
Transportation Science
Simultaneous disruption recovery of a train timetable and crew roster in real time
Computers and Operations Research
Feasible distributed CSP models for scheduling problems
Engineering Applications of Artificial Intelligence
AC2001-OP: an arc-consistency algorithm for constraint satisfaction problems
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
A knowledge-based problem solving method in GIS application
Knowledge-Based Systems
Dispatching and coordination in multi-area railway traffic management
Computers and Operations Research
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Many combinatorial problems can be modelled as Constraint Satisfaction Problems (CSPs). Solving a general CSP is known to be NP-complete, so closure and heuristic search are usually used. However, many problems are inherently distributed and the problem complexity can be reduced by dividing the problem into a set of subproblems. Nevertheless, general distributed techniques are not always appropriate to distribute real-life problems. In this work, we model the railway scheduling problem by means of domain-dependent distributed constraint models, and we show that these models maintained better behaviors than general distributed models based on graph partitioning. The evaluation is focused on the railway scheduling problem, where domain-dependent models carry out a problem distribution by means of trains and contiguous sets of stations.