A Genetic Algorithm for Personnel Scheduling in Vacation Seasons

For workplaces with a preference or need for staffing around the clock, employees commonly work in shifts, which are work sessions that span different parts of the day. The scheduling of these shifts is a multi-objective optimization problem with both hard and soft constraints. The reduction in the available workforce when employees go on vacation makes the problem especially constrained. We describe a method that uses a genetic algorithm to generate shift schedules, for teams of employees and time periods with vacations. The method supports a staffing demand that can be met with one of multiple combinations of shifts. The genetic algorithm features specialized crossovers, together with a repair step aimed at maintaining staffing that fulfils the staffing requirements. A software implementation of the method is evaluated on three real-life problem instances. For two of them, it can produce schedules that are feasible, but subpar to those constructed manually by an experienced personnel scheduling professional. Several ideas to improve the program are presented