Search

Good rosters have many benefits for an organization, such as lower costs, more effective utilization of resources and fairer workloads and distribution of shifts. The process of constructing optimized work timetables for the personnel is an extremely demanding task, hence the use of decision support systems for workforce scheduling has become increasingly important for both the public sector and private companies. This paper describes an effective method for optimizing large-scale staff rostering instances. The idea is to divide an instance into smaller units, solve them separately and then combine the results together again. A set of artificial and real-world instances derived from the actual instances solved for various companies are presented. We publish the best solutions we have found using our computational intelligence heuristic called the PEAST algorithm. We invite the workforce scheduling community to challenge our results. This research has contributed to better systems for our industry partner. [ABSTRACT FROM AUTHOR]

The focus of this workshop paper is to show that highly constrained scheduling problems can be solved for business use using computational intelligence. We give detailed examples of school timetabling, sports scheduling and staff scheduling problems. The key components of a computational intelligence algorithm are discussed. [ABSTRACT FROM PUBLISHER]