Workload Balancing on Agents for Business Process Efficiency Based on Stochastic Model

Abstract

BPMS (Business Process Management Systems) is a revolutionary information system that supports designing, administrating, and improving the business processes systematically. BPMS enables execution of business processes by assigning tasks to human or computer agents according to the predefined definitions of the processes. In this paper, we model business processes and agents using a queueing network and propose a task assignment algorithm to maximize overall process efficiency under the limitation of agents capacity. We first transform the business processes into queueing network models, in which the agents are considered as servers. With this complete, workloads of agents are calculated as server utilization and the task assignment policy can be determined by balancing the workloads. This will serve to minimize the workloads of all agents, thus achieving overall process efficiency. Another application of these results can be capacity planning of agents in advance and business process optimization in reengineering context. The simulation results and comparisons with other well-known dispatching policies show the effectiveness of our algorithm.