Distributed Constraint Satisfaction Problems - A Model and Application

A canonical model for distributed constraint satisfaction problems (DCSP) is presented and algorithms for processing constraints on a DCSP are described. The central idea behind a constraint network that is given as a DCSP is the existence of large dierences between the cost of message passing among dierent components of a DCSP and the cost of local consistency checks within each component. Therefore, algorithms which operate in a multi-agent environment to solve these problems are required to take into consideration these dierences. Four basic algorithms for solving DCSPs that are sound and complete are proposed. Two of these algorithms are sequential and two algorithms operate in parallel and are inherently distributed. The behavior of the proposed algorithms was tested by generating and solving a set of random DCSPs (for a variety of parameters of density and homogeneity). The results show the superiority of the parallel algorithms when the cost variances are large. A series of enhancements of the basic algorithms are presented. These enhancements permit both to extend the scope of the algorithms and their performances. To motivate and test the approach we present a real life problem dealing with Nurses timetabling and transportation in a large multi-department hospital. We compare the results of solving this problem by using the basic algorithms, the enhanced algorithms, and the sequential CSP algorithms.