Human resource behaviour simulation in business processes The structure and dynamics of a modern business environment are very hard to model using traditional methods. Such complexity raises challenges to effective business analysis and improvement. The importance of applying business process simulation to analyze and improve business activities has been widely recognized. However, one remaining challenge is the development of approaches to human resource behavior simulation. To address this problem, we describe a novel simulation approach where intelligent agents are used to simulate human resources by performing allocated work from a workflow management system. The behavior of the intelligent agents is driven a by state transition mechanism called a Hierarchical Task Network (HTN). We demonstrate and validate our simulator via a medical treatment process case study. Analysis of the simulation results shows that the behavior driven by the HTN is consistent with design of the workflow model. We believe these preliminary results support the development of more sophisticated agentbased human resource simulation systems.

Evaluating P2P Human Resource Allocation Strategies Through MultiAgent Simulation Workloads fluctuate in many small and mediumsized enterprises (SMEs). Managing human resources in these conditions can be difficult for companies. In busy periods, workers struggle to complete all the work, but in idle periods, workers may not have enough to do. Various employment methods exist to address this issue, such as temporary staff and outsourcing services. However, it is still important for organizations to be able to fully utilize their regular employees. The aim of this study is to explore a new way to level out employee work hours by using an intercompany, peertopeer (P2P), human resource sharing platform. This platform allows companies experiencing idle periods to offer their employees to companies in busy periods using an automated negotiation technology. The effectiveness of this new platform will be evaluated and verified using multiagent simulation. Our simulation results showed that a single negotiation by each company agent per share cycle was adequate and that the manner in which idle and busy company agents were matched was not important.