Using hybrid scheduling for the semi-autonomous formation of expert teams

• Assignment and scheduling of expert teams is modeled as a hybrid scheduling problem.
• The hybrid scheduling formulation is often faster to solve and yields good solutions.
• The application uncovered opportunities for improving hybrid scheduling algorithms.
• Human insights can improve solutions by incrementally introducing constraints.

Selecting and scheduling human experts to cooperatively solve a problem can be a highly complex task, given various constraints (such as what expertise is needed and when) and preferences (such as which expertise an expert most prefers to exercise). Computational agents can thus greatly help users form and schedule expert teams. This paper introduces a new formulation of the team formation and scheduling problem as a Hybrid Scheduling Problem (HSP) and compares the performance of an agent using the HSP formulation to a prior agent-based approach. We empirically demonstrate the promise of the HSP formulation and highlight how the application of HSP techniques to this problem has led us to identify important modifications to mechanisms that improve HSP solving. Finally, we summarize how the HSP formulation can support human-agent collaboration during the process of forming and scheduling expert teams.