Finding small simple cycle separators for 2-connected planar graphs
Journal of Computer and System Sciences
Network-based heuristics for constraint-satisfaction problems
Artificial Intelligence
A mathematical for periodic scheduling problems
SIAM Journal on Discrete Mathematics
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
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
Graph partitioning for high-performance scientific simulations
Sourcebook of parallel computing
Simultaneous disruption recovery of a train timetable and crew roster in real time
Computers and Operations Research
Solving a periodic single-track train timetabling problem by an efficient hybrid algorithm
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
A demand-responsive decision support system for coal transportation
Decision Support Systems
Computers and Industrial Engineering
Engineering Applications of Artificial Intelligence
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Many problems of theoretical and practical interest can be formulated as Constraint Satisfaction Problems (CSPs). Solving a general CSP is known to be NP-complete; however, distributed models may take advantage of dividing the problem into a set of simpler inter-connected sub-problems which can be more easily solved. The purpose of this paper is three-fold: first, we present a technique to distribute the constraint network by means of selection of tree structures. Thus, the CSP is represented as a meta-tree CSP structure that is used as a hierarchy of communication by our distributed algorithm. Then, a distributed and asynchronous search algorithm (DTS) is presented. DTS is committed to solving the meta-tree CSP structure in a depth-first search tree. Finally, an intra-agent search algorithm is presented. This algorithm takes into account the Nogood_message to prune the search space. We have focused our research on the railway scheduling problem which can be distributed by tree structures. We show that our distributed algorithm outperforms well-known centralized algorithms.