Multiobjective Optimization for Nurse Scheduling

It is laborious to determine nurse scheduling using human-involved manner in order to account for administrative operations, business benefits, and nurse requests. To solve this problem, a mathematical formulation is proposed where the hospital administrators can set multiple objectives and stipulate a set of scheduling constraints. We then present a multiobjective optimization method based on the cyber swarm algorithm (CSA) to solve the nurse scheduling problem. The proposed method incorporates salient features from particle swarm optimization, adaptive memory programming, and scatter search to create benefit from synergy. Two simulation problems are used to evaluate the performance of the proposed method. The experimental results manifest that the proposed method outperforms NSGA II and MOPSO in terms of convergence and diversity performance measures of the produced results.