  Within the context of biomass production, this paper proposes a method for
logistics optimisation. Starting from a headquarter multiple tours are to be
executed simultaneously by groups of harvesting units (HUs) and support units
(SUs) to first harvest biomass from multiple agricultural fields, before
supplying the biomass to multiple biogas plants (BPs) via shuttling SUs. This
problem is relevant on a larger scale in particular for contractors. This
problem is complex since there are three interconnected optimisation levels:
(i) the assignment of BPs to tours and the ordering of BPs assigned to each
tour, (ii) the assignment of fields to BPs and the ordering of fields assigned
to each BP, and (iii) determining the number of HUs and SUs assigned to each
tour, whereby different HUs and SUs may in general have different working rates
and loading capacities. Problem modeling and a solution method are discussed.
For the latter, a GPU-accelerated heuristic search algorithm is proposed. For
the former, an optimisation criterion minimising both total accumulated path
length and the maximum completion time over all harvesters tours, an embedded
local minimisation for the assignment of SUs to tours, and demand fulfilment
constraints for BPs are discussed. In stochastic simulation experiments it is
found that permitting unconstrained assignment of any available field that a
contractor services to any available BP, independent of their ownerships, is
crucial (i) to attain maximum path length savings, and (ii) also to best
balance and minimise uniform completion times over all harvesters tours such
that weather-dependent harvesting windows can be exploited optimally.
