Solving security staff scheduling by using genetic algorithm - Ang, Shin Yin (2021)
The scheduling problem has been studied for a few decades where many researchers have successfully solved scheduling using different approaches. However, in the new era, flexible working hours is the latest trend compared with the traditional way, fixed working hours. Therefore, in this research, a flexible shift scheduling is studied because the scheduling problem should be humanized to follow the trend. But, it is a complex problem due to the scheduling involving the staff and their preferences. A heuristic method, the genetic algorithm is selected to solve this research problem as it is a powerful tool, shown in addressing the scheduling problem. It is because it is familiar used to solve large scale population and able to produce an optimal solution. This research not only fulfils the demand of shift but also calculates the preference of staff toward shift as the hard constraints. The combination of gender, preferred shift and preferred day off of the staff are represented as the gene while the chromosome represents a schedule. From the existing method, it requires the user to collect and key in the preference of staff manually before generating a result. It may take longer time if there have a larger number of staff. From the result in this research, 76.37% of the staff were allocated at their preferred shift while only 23.63% of staff were not allocated at their preferred shift. This research also proposed an offline system, known as the Flexible Shift Scheduling System to smooth the job. In the sensitivity analysis, the system could provide a satisfactory result in three minutes.