Staff scheduling by a genetic algorithm with heuristic operators

This paper has two major goals: 1) to define a workforce scheduling problem with many realistic constraints, and 2) to investigate its solution using a customized genetic algorithm featuring a group of operators which combine stochastic behavior and heuristics. Experiments show that high-quality workforce schedules can be obtained in reasonable time even for large problems