Optimizing Taxi-Pooling Operations to Enhance Efficiency and Revenue: A Queuing Model Approach

This study investigates the optimization of taxi-pooling operations using the M/M/1/m queuing model, aiming to enhance efficiency and revenue for taxi service platforms. Traditional taxi operations face challenges during peak periods, including inefficiency and increased operational costs. Taxi-pooling, by accommodating multiple passengers with similar travel demands, offers a solution that reduces travel costs, operational expenses, and urban congestion. The study develops an optimization model to balance operational costs and passenger waiting times, identifying the utilization rate of taxis as a critical factor in platform revenue. By modeling the taxi-pooling service as a queuing system, we derive mathematical expressions for passenger waiting times and platform revenue under varying conditions. Our findings highlight the importance of optimal vehicle investment strategies and pricing decisions to maximize revenue. The study provides theoretical support for improving taxi-pooling platforms’ efficiency and competitiveness, contributing to better urban transportation solutions.

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Publication Details

Journal
Mathematics
Published
2024-10-13
DOI
https://doi.org/10.3390/math12203210
Citations
2
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.41
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article

Optimizing Taxi-Pooling Operations to Enhance Efficiency and Revenue: A Queuing Model Approach

Jairus Odawa Malenje, Jingwei Wang, Yi Zhang, Han Yin et al.
2 citations
Mathematics
Transportation and Mobility Innovations
0.41
article

Optimizing Taxi-Pooling Operations to Enhance Efficiency and Revenue: A Queuing Model Approach

Jairus Odawa Malenje, Jingwei Wang, Yi Zhang, Han Yin, Chaojun Wang
article en
2 citations

Abstract

This study investigates the optimization of taxi-pooling operations using the M/M/1/m queuing model, aiming to enhance efficiency and revenue for taxi service platforms. Traditional taxi operations face challenges during peak periods, including inefficiency and increased operational costs. Taxi-pooling, by accommodating multiple passengers with similar travel demands, offers a solution that reduces travel costs, operational expenses, and urban congestion. The study develops an optimization model to balance operational costs and passenger waiting times, identifying the utilization rate of taxis as a critical factor in platform revenue. By modeling the taxi-pooling service as a queuing system, we derive mathematical expressions for passenger waiting times and platform revenue under varying conditions. Our findings highlight the importance of optimal vehicle investment strategies and pricing decisions to maximize revenue. The study provides theoretical support for improving taxi-pooling platforms’ efficiency and competitiveness, contributing to better urban transportation solutions.

MathematicsVol. 12(20)
University of Shanghai for Science and Technology (CN), Shanghai Urban Transportation Design Institute (China) (CN), Huaiyin Institute of Technology (CN), Masinde Muliro University of Science and Technology (KE)
Openalex Percentile: Top 39%
Transportation and Mobility Innovations
0.41
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