  The ground fixed base stations (BSs) are often deployed inflexibly, and have
high overheads, as well as are susceptible to the damage from natural
disasters, making it impractical for them to continuously collect data from
sensor devices. To improve the network coverage and performance of wireless
communication, unmanned aerial vehicles (UAVs) have been introduced in diverse
wireless networks, therefore in this work we consider employing a UAV as an
aerial BS to acquire data of agricultural Internet of Things (IoT) devices. To
this end, we first formulate a UAV-assisted data collection multi-objective
optimization problem (UDCMOP) to efficiently collect the data from agricultural
sensing devices. Specifically, we aim to collaboratively optimize the hovering
positions of UAV, visit sequence of UAV, speed of UAV, in addition to the
transmit power of devices, to simultaneously achieve the maximization of
minimum transmit rate of devices, the minimization of total energy consumption
of devices, and the minimization of total energy consumption of UAV. Second,
the proposed UDCMOP is a non-convex mixed integer nonlinear optimization
problem, which indicates that it includes continuous and discrete solutions,
making it intractable to be solved. Therefore, we solve it by proposing an
improved multi-objective artificial hummingbird algorithm (IMOAHA) with several
specific improvement factors, that are the hybrid initialization operator,
Cauchy mutation foraging operator, in addition to the discrete mutation
operator. Finally, simulations are carried out to testify that the proposed
IMOAHA can effectively improve the system performance comparing to other
benchmarks.
