Scheduling hours and staff per crew are optimized with Genetic Algorithms to meet daily and hourly changing work demands in a 24/7 operation as displayed in the illustration below.
Goal is to reduce both Under- and Over staffing at any time during the week, and thereby improve both response times of the staff and overall performance. Further, schedules must meet legal and chronotypical requirements, that is schedules must contain appropriate rest phases and rotation patterns.
The next figure illustrates the optimisation of mis-scheduled working hours with GA during the optimization generations:
The resulting schedules are presented to the clients.