Optimization study demonstrates efficient eVTOL fleet routing under dynamic passenger loads and battery constraints, highlighting strategies for scalable urban air mobility.
Urban low-altitude bus operations require coordinated eVTOL route decisions under station time windows, dynamic passenger boarding and alighting, load-dependent energy consumption, opportunity charging, and battery safety requirements. We formulate a mixed-integer programming model for reservation-based shared services that lexicographically minimizes the number of deployed aircraft first and total flight distance second while enforcing passenger-capacity, time-window, charging, and battery-safety constraints. To solve large instances efficiently, an Elite-Pool guided Load-Coupled Energy-aware Adaptive Large Neighborhood Search algorithm (EP-LCE-ALNS) is developed by combining forward load-energy-coupled decoding, multi-start construction, elite-route guidance, and adaptive neighborhood search. Benchmark comparisons show that EP-LCE-ALNS consistently achieves strong solution quality across instances of different scales and outperforms the comparison algorithms on large-scale problems. Sensitivity analyses further show that increasing passenger capacity reduces fleet requirements and flight distance, whereas a larger battery safety margin increases both, providing decision support for fleet configuration, route organization, and safety settings.
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Wu et al. (2026) studied this question.
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