A new nonlinear stochastic staff scheduling model

This paper presents a new mixed integer nonlinear stochastic staff scheduling model, where the workforce demands are under uncertainty, with a general probability distribution. To validate the proposed model, a simulation technique is employed and an optimization technique is used to solve the resulted model. As the problem is combinatorial, a meta-heuristic approach, i.e. a genetic algorithm, is implemented with tuned parameters, using the Taguchi design of experiment method. The preliminary results indicate that the proposed method of this paper can be effectively used to manage staff schedules for many real-world applications.