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.
Highlights
The International Air Transport Association (IATA) [1] predicts that over 10 billion air passengers will be carried by 2050, which will generate about 1800 megatonnes (Mt) of carbon emissions and lead to challenges of passenger and baggage flow management at airport terminals
Since the location of logistic hubs will be specified in our study, we focus on solving the vehicle routing problem (VRP)
This paper focuses on the VRP with the specified location of logistic hubs for the baggage-free airport terminal (BFAT)’s baggage collection service
Summary
The International Air Transport Association (IATA) [1] predicts that over 10 billion air passengers will be carried by 2050 (approximately traveling 20 trillion kilometers each year), which will generate about 1800 megatonnes (Mt) of carbon emissions and lead to challenges of passenger and baggage flow management at airport terminals. Since the location of logistic hubs will be specified in our study, we focus on solving the vehicle routing problem (VRP). Erdoğan and Miller-Hooks [8] considered EVs into the GVRP models by adding the energy supplement facilities and vehicle travel distance constraints. They provided an effective routing method for EV companies. This paper makes the following contributions: (i) study a baggage collection service network design problem for future BFATs; (ii) adopt a spreadsheet solver tool to find the optimal vehicle routes for baggage collection; (iii) propose an AR-based baggage tag visualization application, which is useful to reduce any mishandling; (iv) apply the model for the case study at the LCY.
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