Adaptive scheduling in dynamic environments

We present a method for fair agent scheduling in transportation scenarios. The approach is designed to first ensure the scheduling of all required task locations and, once this is achieved, focus on a balancing the workload across the population of transportation units. This, while almost certainly sub-optimal in the context of efficiency, facilitates the speedy allocation of new geographically located tasks due to the distribution of the remaining capacity across the agent population. We discuss our method, present results from simulations and discuss the advantages and disadvantages of the approach.