Employee timetabling, constraint networks and knowledge-based rules: A mixed approach

Abstract

Employee timetabling problems (ETP) usually involve an organization with a set of tasks that need to be fulfilled by a set of employees, each with his/her own qualifications, constraints and preferences. The organization usually enforces some overall constraints and attempts to achieve some global objectives such as a just or equitable division of work. Examples for such problems are: assignment of nurses to shifts in a hospital, or assignment of phone operators to shifts and stations in a service-oriented call-center. One possible approach for solving ETPs is to use constraint processing techniques. Another approach is to model human knowledge into knowledge-based systems for timetabling. The present paper presents an approach to representing and processing employee timetabling problems (ETP) by a combination of explicit representations of some constraints in the network and rule-based processing in which specific heuristics for generic constraints of ETPs are embedded. The mixed-mode approach has been implemented in the form of a commercial software package for defining and solving real world ETPs. Example of a real world ETP is followed through the presentation and is used to experimentally compare standard CSP techniques with the proposed mixed-mode approach.