Bayesian Selection Rule for Human-Resource Selection in Business Process Management Systems

Abstract

This study developed a method for selection of available human resources for incomingjob allocation that considers factors affecting resource performance in the business process management (BPM) environment. For many years, resource selection has been treated as a very important issue in scheduling due to its direct influence on the speed and quality of task accomplishment. Even though traditional resource selection can work well in many situations, it might not be the best choice when dealing with human resources. Humanresource performance is easily affected by several factors such as workload, queue, working hours, inter-arrival time, and others. The resource-selection rule developed in the present study considers factors that affect human resource performance. We used a Bayesian Network (BN) to incorporate those factors into a single model, which we have called the Bayesian Selection Rule (BSR). Our simulation results show that the BSR can reduce waiting time, completion time and cycle time.