Adaptive orienteering problem with stochastic travel times

In this paper, we evaluate the extent to which one can increase the likelihood of collecting greater reward in an orienteering problem with stochastic travel times by adapting paths between reward nodes as travel times are revealed. We evaluate whether this adaptivity impacts the choices of reward nodes to visit in a setting where the agent must commit to reward nodes before commencing operations. We explore the computational challenges of adding adaptive consideration in the selection of reward nodes to visit and examine the extent to which one can capture some of the benefits of adaptivity with a simpler model.