A MOEAD-Based Approach to Solving the Staff Scheduling Problem

Due to the impact on increase of the utilization efficiency of the staff and decrease of operating cost of enterprises, the staff scheduling problem has attracted the interests of many scholars. Actually, the staff scheduling problem can be considered to be how to assign the right staff to the right shift on the right time period based on constraints, meanwhile the objectives should be optimized. Hence, designing an algorithm to satisfy all the requirements mentioned above is challenging. First, there are prohibitive combinations of assigning the staff to shifts from a sheer numbers perspective; Next, there are potential conflicts among optimization objectives, which means objectives may not reach the optimization at the same time and the optimal schedule can not be found; Finally, rare work about the fairness of optimization objectives has been studied. The existing works usually focus on optimization objectives in total, ignoring the fairness of them. A schedule with best optimization objectives can not provide the highest fairness. Hence, we propose an approach based on multi-objective evolutionary algorithm based on decomposition (MOEAD) to solve the staff scheduling problem in the fairness aspect. A series of experiments are performed and prove that the proposed method can effectively find the schedule with fairness.