  Providing Internet service above the clouds is of ever-increasing interest
and in this context aeronautical {\it{ad-hoc}} networking (AANET) constitutes a
promising solution. However, the optimization of packet routing in large ad hoc
networks is quite challenging. In this paper, we develop a discrete $\epsilon$
multi-objective genetic algorithm ($\epsilon$-DMOGA) for jointly optimizing the
end-to-end latency, the end-to-end spectral efficiency (SE), and the path
expiration time (PET) that specifies how long the routing path can be relied on
without re-optimizing the path. More specifically, a distance-based adaptive
coding and modulation (ACM) scheme specifically designed for aeronautical
communications is exploited for quantifying each link's achievable SE.
Furthermore, the queueing delay at each node is also incorporated into the
multiple-objective optimization metric. Our $\epsilon$-DMOGA assisted
multiple-objective routing optimization is validated by real historical flight
data collected over the Australian airspace on two selected representative
dates.
