Investigating the scope for integrating uncrewed aerial vehicles (UAVs) into mixed-mode fleets to support national health service (NHS) logistics operations

Abstract

Local healthcare logistics systems carry a variety of cargoes to ensure patient care is maintained, though they account for a significant proportion of the total healthcare emissions footprint. Legislation and self-defined targets are driving the UK's National Health Service (NHS) to make their carbon impact net-zero; thus, this research investigated the scope for a multi-modal logistics network with vans, bikes, and uncrewed aerial vehicles/UAVs to support this goal. The unique contributions of this study include new approaches to solving the heterogeneous two-echelon vehicle routing problems associated with the collection of diagnostic specimens from community clinics. After initial investigations using a column generation heuristic, an adaptation of the Clarke and Wright Savings Algorithm with a bin packing algorithm was developed to evaluate the scope for integrating multi-mode fleets. The implications of good distribution practices and dangerous goods regulations were also explored, and new procedures were proposed. Meanwhile, an analysis of weather reliability criteria found that a 14 m/s peak gust tolerance would be essential for UAVs to match business-as-usual performance levels. Accounting for practicalities around payloads and delivery site constraints, case study data from the Solent region (UK) were applied to the algorithm. In a baseline case, 76 doctor's surgeries were served by 4 vans, costing £190k and generating 7.7 T CO₂-eq. per year. It was found that introducing a mixed-mode system with 1 van and 10 UAVs could enable transit time reductions of up to 84% (209 mins to 33 mins), however, the resulting increase in operating costs (+133%, +£253k per year) and emissions (+211%, +19.5 T CO₂-eq. per year) may prove difficult to justify. Furthermore, the absolute time savings may be inconsequential to patient care and the wider supply chain. In another case study involving 22 surgeries, van and bike combinations gave the lowest emission outcomes, with CO₂-eq. reductions of up to 7% for a 3% increase in costs.

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Identifiers

ORCID for Andy Oakey: orcid.org/0000-0003-1796-5485

ORCID for Tom Cherrett: orcid.org/0000-0003-0394-5459

ORCID for Toni Martinez Sykora: orcid.org/0000-0002-2435-3113

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