An agile simheuristic for the stochastic team task assignment and orienteering problem: applications to unmanned aerial vehicles

Abstract

Efficient coordination of unmanned aerial vehicles (UAVs) requires the solving of challenging operational problems. One of them is the integrated team task assignment and orienteering problem (TAOP). The TAOP can be seen as an extension of the well-known team orienteering problem (TOP). In the classical TOP, a homogeneous fleet of UAVs has to select and visit a subset of customers in order to maximize, subject to a maximum travel time per route, the total reward obtained from these visits. In the TAOP, a number of different tasks (customer services) have to be assigned to a fleet of heterogeneous UAVs, while the best routing plan must also be determined to cover these services. Since factors such as weather conditions might influence travel times, these are modeled as random variables. Reliability issues are also considered, since random times might prevent a route from being successfully completed before a UAV runs out of battery.