Abstract

In response to the challenge of optimizing customized passenger transport paths for airport connections while taking carbon emissions constraints into account, this paper proposes an optimization model that minimizes the total cost by addressing passenger time window constraints, determining optimal passenger transport paths, and optimizing factors like the number of drop-off stations and vehicle occupancy rates. The total cost comprises the operational expenses of customized passenger transport businesses and travel time costs per passenger. We develop an annealing genetic algorithm to solve the model and provide a case analysis. Our findings indicate that the algorithm and the model empower decision-makers to swiftly select passenger transport path schemes that minimize the total cost with their specific requirements.

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