Distributed Constraints for Large-Scale Scheduling Problems

Many problems of theoretical and practical interest can be formulated as Constraint Satisfaction Problems (CSPs). The general CSP is known to be NP-complete; however, distributed models may reduce the exponential complexity by partitioning the problem into a set of subproblems. In this work, we present a distributed model for solving large-scale CSPs in which agents are committed to sets of constraints. Our technique carries out a partition over the constraint network by a graph partitioning software, such as each subproblem is as independent as possible and, it can be solved in a reasonable time. We have focused our research to railway scheduling problem where the resultant CSP maintains thousand of variables and constraints. keywords: Constraint Satisfaction Problems, graph partitioning, railway scheduling problem.