Assigning teams to tasks under time-varying coordination costs

Coordination among workers within a collaborative team environment is a key factor to its success but it is challenging to come up with a general model for relative costs and benefits of coordination. In a typical work environment, teams with sufficient aggregate expertise are selected to work on an incoming sequence of tasks one by one; it is often the case that the cost of coordination among the same set of workers within a team decreases over time for future tasks of similar difficulty since the workers get more familiar with each other. We study the problem of assigning available teams with adequate aggregate expertise to arriving tasks when the coordination cost can vary over time, as long as it does not increase over time. We propose an efficient team-to-task assignment algorithm that minimizes aggregate costs (due to assignment, coordination and context-switching). The algorithm automatically finds the number of times a specific team should be assigned to a task in the sequence by applying dynamic programming iteratively and guarantees a local optimal solution. We also study a strategy for team assembly in this time varying coordination cost scenario.