Robustness in the personnel shift scheduling problem : the modelling and validation of different proactive and reactive strategies

The personnel planning process in any organization aims to ensure that the organization can offer a desired service level to their customers at a minimal personnel cost and maximal personnel satisfaction. This process consists of three hierarchical phases characterized by differing levels of decision freedom and uncertainty about the future personnel demand and availability. In this respect, the personnel planner faces a large and medium level of uncertainty and decision freedom in the strategic staffing phase and the tactical scheduling phase, respectively. In these phases, the personnel planner manages the uncertainty by making assumptions and predictions about the future. Based on these assumptions and predictions, the personnel planner makes decisions about the number of employees to be hired and assigned to work during specific points in time. These decisions constrain the decision freedom in the operational allocation phase, in which the personnel planner obtains the most recent information on the actual personnel demand and availability. This information may differ from the assumptions and predictions, and affect the service level and personnel cost and satisfaction. As such, the moment the personnel planner faces the lowest level of uncertainty, (s)he also has the lowest level of decision freedom. In this respect, this dissertation aims to propose strategies to anticipate and deal with unexpected divergences between the previously established assumptions and predictions, and the actual personnel demand and availability

A memetic algorithm to maximise the employee substitutability in personnel shift scheduling

Personnel rosters are typically constructed for a medium-term period under the assumption of a deterministic operating environment. However, organisations usually operate in a stochastic environment and are confronted with unexpected events in the short term. These unexpected events affect the workability of the personnel roster and need to be resolved efficiently and effectively. To facilitate this short-term recovery, it is important to consider robustness by adopting proactive scheduling strategies during the roster construction. In this paper, we discuss a proactive strategy that maximises the employee substitutability value in a personnel shift scheduling context. We propose a problem-specific population-based approach with local and evolutionary search heuristics to solve the resulting non-linear personnel shift scheduling problem and obtain a medium-term personnel shift roster with a maximised employee substitutability value. Detailed computational experiments are presented to validate the design of our heuristic procedure and the selection of the heuristic operators