Matrix models are ubiquitous for constraint problems. Many such problems have a matrix of variablesM, with the same constraint defined by a finitestate automaton A on each row of M and a global cardinality constraint gcc on each column of M. We give two methods for deriving, by double counting, necessary conditions on the cardinality variables of the gcc constraints from the automaton A. The fi...

The stretch constraint occurs in many rostering problems that arise in the industrial and public service sectors. In this paper we present an efficient algorithm for domain consistency propagation of the stretch constraint. Using benchmark and random instances, we show that this stronger consistency sometimes enables our propagator to solve more difficult problems than a previously proposed pro...

The rostering problem consists in finding an optimal assignment of shifts to workers in a given time horizon. When the total workload should be evenly distributed, we have a balanced rostering problem. We consider a practical application to the junk removal company in Crema, Italy. In this case, predefined daily shifts must be assigned to the drivers in a fair way. However, the drivers have lim...

This paper looks at work done on a case-based workforce scheduling application. Generalised patterns of workforce allocation are used to build up a schedule that is then adjusted to remove any problems. Because some constraint elements are incorporated in the case-base, the global problem search space is reduced. The case-base can be maintained either automatically, by generalisation of solutio...

Self-rostering is receiving more and more attention in literature and in practice. With self-rostering, employees propose the schedule they prefer to work during a given planning horizon. However, these schedules often do not match with the staffing demand as specified by the organization. We present an approach to support creating feasible schedules that uses the schedules proposed by the empl...

Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimization Algorithm (BOA) for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each nurse’s assignment. Based on the idea of using probabilistic models, the BOA builds a Bayesian network f...

This special volume is focused upon a selection of the papers that were presented at the 9th International Conference on the Practice and Theory of Automated Timetabling (PATAT) in Son, Norway, between 28th and 31st August, 2012. The PATAT conferences are held biennially. This is the third occasion that we have employed the Annals of Operations Research as the forum for a revised and selected c...

One significant task addressed during software development project is to determine which features should be covered by the application that is being developed. This problem is known as the Next Release Problem (NRP) and has been solved using metaheuristic search techniques. We show how to apply these techniques by its embedding into a requirement management tool as an assistant functionality. W...