Simulation-based workforce assignment in a multi-organizational social network for alliance-based software development

The development of alliance-based software requires the collaboration of many stakeholders. These different stakeholders across multiple organizations form a complex social network. The goal of this paper is to develop a novel modeling framework, which will help task managers devise optimal workforce assignments considering both short-term and long-term aspects of the software development process. The proposed framework is composed of an assignment module and a prediction module. For a given task, the assignment module first selects a candidate workforce mix. Based on the candidate workforce mix, the prediction module then predicts the short-term performance (productivity) as well as the long-term performance (workforce training and robustness of the organization) of the organization. Then, the assignment module selects another candidate mix, and this iteration continues until an optimal workforce mix is found. The prediction module and the assignment module are based on an agent-based simulation method and a multi-objective optimization model, respectively. The proposed modeling framework is illustrated with a software enhancement request process in Kuali, an alliance-based open source software development project involving 12 organizations. The constructed framework is executed with varying parameters to demonstrate its use and benefit in the software enhancement process.