AI Summary & Key Takeaways
AI InsightResultsshow that proposed model gave better results compared with current situation.With the proposed solution method, the workloads of the profile groups workingabove their capacity were transferred to other profile groups with idle capacity.Thus, the capacity utilization rates of the profile groups were more balanced andthe minimum capacity utilization rate was calculated as 41%.
📌 3 Key Takeaways
Abstract
Efficient planning and management of the workforce resources is one of the mostessential requirements for the companies operating in the service sector. For banks,a large number of transactions comes to Central Operations Department from thebranches or directly from the customers and their aim is to provide the bestoperational service with the highest efficiency with the limited workforceresources in the departments. In this study, a real assignment problem wasdiscussed and the problem was considered as Generalized Assignment Problem.For the solution of the problem, related algorithms were listed and examined in theliterature survey section. Then, a two-step method is proposed. First stepprioritizes the task coming to the system by considering the customer types,service level agreement (SLA) times, cut-off times, task type. In the second step,a multi-objective mathematical model was developed to assign task to employeegroups. A preference based optimization method called Linear PhysicalProgramming (LPP) is used to solve the model. Afterward, proposed model wastested on real banking data. For all the tests, GAMS was used as a solver. Resultsshow that proposed model gave better results compared with current situation.With the proposed solution method, the workloads of the profile groups workingabove their capacity were transferred to other profile groups with idle capacity.Thus, the capacity utilization rates of the profile groups were more balanced andthe minimum capacity utilization rate was calculated as 41%.