This note demonstrates how the distributed auction algorithm can be modified to assign mobile agents to spatially distributed tasks despite communication delays and the fact that agent movement may cause the benefit associated with each possible agent-task assignment to vary during the execution of the algorithm. Bounds on the convergence time of the algorithm and the sub-optimality of the resulting solution are provided. Monte Carlo simulations are provided to show the conditions under which the modified distributed auction can outperform centralized calculation.