GPU-accelerated Logistics Optimisation for Biomass Production with Multiple Simultaneous Harvesters Tours, Fields and Plants
Mogens Graf Plessen

TL;DR
This paper introduces a GPU-accelerated heuristic for optimizing complex biomass logistics involving multiple harvesters, fields, and biogas plants, improving efficiency and balancing completion times.
Contribution
It presents a novel GPU-based heuristic search algorithm for multi-level biomass logistics optimization, addressing interconnected assignment and routing problems.
Findings
GPU acceleration significantly reduces computation time.
Allowing flexible field-to-BP assignment improves path length savings.
Optimized scheduling exploits weather windows effectively.
Abstract
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…
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