Dynamic Zonal Pricing and Vehicle Dispatching for Hub-Based Demand-Responsive Last-Mile Transit Services

Urban passenger hubs, such as airports and railway stations, generate concentrated last-mile demand from arriving passengers to spatially dispersed urban destinations. Fluctuating passenger arrivals and changing vehicle availability can create a mismatch between accepted demand and available service capacity. This paper aims to coordinate zone-level pricing and vehicle dispatching, so that fare-responsive accepted demand can be better aligned with available vehicle resources, while balancing operator financial performance and service reliability. Under the zonal pricing scheme, the transit operator determines a quoted zone-level fare for each service zone at every decision epoch. Newly arriving service requests accept the service when the quoted fare does not exceed their maximum acceptable per-passenger fare, after which the fare is committed. A rolling-horizon optimization model jointly determines zone-level fares and dispatching plans as request states and vehicle states evolve over time. The fare discretization property reduces the continuous pricing decision to a finite candidate zone-level fare selection problem, and a customized Rolling-Horizon Adaptive Large Neighborhood Search (RH-ALNS) algorithm is developed to solve the resulting problem efficiently. Case studies based on Nanjingnan Railway Station in Nanjing, China, demonstrate the operational value of coordinating pricing and dispatching decisions. In the baseline case, the proposed method achieves a passenger service rate of 76.75%, an accepted-passenger fulfillment rate of 96.07%, and an operating surplus of 1.145 CNY per passenger-kilometer. Holding the RH-ALNS dispatching method fixed, dynamic zonal pricing increases the objective value by 4.39%, the operating surplus per passenger-kilometer by 5.46%, and accepted-passenger fulfillment by 3.63 percentage points relative to fixed zonal fares. The findings indicate that coordinating dynamic zonal pricing with vehicle dispatching can better align accepted demand with available vehicle resources and provide practical guidance for designing reliable, resource-efficient, and financially balanced hub-based demand-responsive last-mile transit services.

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Publication Details

Journal
Sustainability
Published
2026-08-25
DOI
https://doi.org/10.3390/su18178714
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.00

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article

Dynamic Zonal Pricing and Vehicle Dispatching for Hub-Based Demand-Responsive Last-Mile Transit Services

Rong Fu, Chunguang Bai, Jingxu Chen, H Huang
Sustainability
Transportation and Mobility Innovations
article

Dynamic Zonal Pricing and Vehicle Dispatching for Hub-Based Demand-Responsive Last-Mile Transit Services

Rong Fu, Chunguang Bai, Jingxu Chen, H Huang
article en

Abstract

Urban passenger hubs, such as airports and railway stations, generate concentrated last-mile demand from arriving passengers to spatially dispersed urban destinations. Fluctuating passenger arrivals and changing vehicle availability can create a mismatch between accepted demand and available service capacity. This paper aims to coordinate zone-level pricing and vehicle dispatching, so that fare-responsive accepted demand can be better aligned with available vehicle resources, while balancing operator financial performance and service reliability. Under the zonal pricing scheme, the transit operator determines a quoted zone-level fare for each service zone at every decision epoch. Newly arriving service requests accept the service when the quoted fare does not exceed their maximum acceptable per-passenger fare, after which the fare is committed. A rolling-horizon optimization model jointly determines zone-level fares and dispatching plans as request states and vehicle states evolve over time. The fare discretization property reduces the continuous pricing decision to a finite candidate zone-level fare selection problem, and a customized Rolling-Horizon Adaptive Large Neighborhood Search (RH-ALNS) algorithm is developed to solve the resulting problem efficiently. Case studies based on Nanjingnan Railway Station in Nanjing, China, demonstrate the operational value of coordinating pricing and dispatching decisions. In the baseline case, the proposed method achieves a passenger service rate of 76.75%, an accepted-passenger fulfillment rate of 96.07%, and an operating surplus of 1.145 CNY per passenger-kilometer. Holding the RH-ALNS dispatching method fixed, dynamic zonal pricing increases the objective value by 4.39%, the operating surplus per passenger-kilometer by 5.46%, and accepted-passenger fulfillment by 3.63 percentage points relative to fixed zonal fares. The findings indicate that coordinating dynamic zonal pricing with vehicle dispatching can better align accepted demand with available vehicle resources and provide practical guidance for designing reliable, resource-efficient, and financially balanced hub-based demand-responsive last-mile transit services.

SustainabilityVol. 18(17)
Southeast University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 18%
Transportation and Mobility Innovations
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