Toward Baggage-Free Airport Terminals: A Case Study of London City Airport

Yirui Jiang, Runjin Yang, Chenxi Zang, Zhiyuan Wei, John Thompson, Trung Hieu Tran, Adriana Encinas-Oropesa and Leon Williams
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Yirui Jiang: School of Water, Energy and Environment, Cranfield University, Bedfordshire MK43 0AL, UK
Runjin Yang: School of Water, Energy and Environment, Cranfield University, Bedfordshire MK43 0AL, UK
Chenxi Zang: School of Water, Energy and Environment, Cranfield University, Bedfordshire MK43 0AL, UK
Zhiyuan Wei: School of Water, Energy and Environment, Cranfield University, Bedfordshire MK43 0AL, UK
John Thompson: School of Water, Energy and Environment, Cranfield University, Bedfordshire MK43 0AL, UK
Trung Hieu Tran: School of Water, Energy and Environment, Cranfield University, Bedfordshire MK43 0AL, UK
Adriana Encinas-Oropesa: School of Water, Energy and Environment, Cranfield University, Bedfordshire MK43 0AL, UK
Leon Williams: School of Water, Energy and Environment, Cranfield University, Bedfordshire MK43 0AL, UK

Sustainability, 2021, vol. 14, issue 1, 1-24

Abstract: Nowadays, the aviation industry pays more attention to emission reduction toward the net-zero carbon goals. However, the volume of global passengers and baggage is exponentially increasing, which leads to challenges for sustainable airports. A baggage-free airport terminal is considered a potential solution in solving this issue. Removing the baggage operation away from the passenger terminals will reduce workload for airport operators and promote passengers to use public transport to airport terminals. As a result, it will bring a significant impact on energy and the environment, leading to a reduction of fuel consumption and mitigation of carbon emission. This paper studies a baggage collection network design problem using vehicle routing strategies and augmented reality for baggage-free airport terminals. We use a spreadsheet solver tool, based on the integration of the modified Clark and Wright savings heuristic and density-based clustering algorithm, for optimizing the location of logistic hubs and planning the vehicle routes for baggage collection. This tool is applied for the case study at London City Airport to analyze the impacts of the strategies on carbon emission quantitatively. The result indicates that the proposed baggage collection network can significantly reduce 290.10 tonnes of carbon emissions annually.

Keywords: network design; vehicle routing problem; baggage free airport terminal; carbon emission; augmented reality (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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