Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both...

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...

This paper presents new formulations for multi-activity shift scheduling problems (MASSP). In these formulations, the rules governing the feasibility of shifts are encoded in state-expanded networks in which nodes are associated with states and arcs represent assignments inducing state...

In this paper, we propose an integrated approach to combine aircraft routing and crew scheduling problem with the consideration of multiple types of fleets where a crew can only fly the specific type of fleet. This method effectively manages the aircraft and crew because it takes aircraft...