Bi Objective Peer-to-Peer Ridesharing Model for Balancing Passengers Time and Costs

Author:

Hasanpour Jesri Seyed OmidORCID,Akbarpour Shirazi Mohsen

Abstract

Ride-sharing services are one of the top growing sustainable transportation trends led by mobility-as-a-service companies. Ridesharing is a system that provides the ability to share vehicles on similar routes for passengers with similar or nearby destinations on short notice, leading to decreased costs for travelers. At the same time, though, it takes longer to get from place to place, increasing travel time. Therefore, a fundamental challenge for mobility service providers should be finding a balance between cost and travel time. This paper develops an integer bi-objective optimization model that integrates vehicle assignment, vehicle routing, and passenger assignment to find a non-dominated solution based on cost and time. The model allows a vehicle to be used multiple times by different passengers. The first objective seeks to minimize the total cost, including the fixed cost, defined as the supply cost per vehicle, and the operating cost, which is a function of the distance traveled. The second objective is to minimize the time it takes passengers to reach their destination. This is measured by how long it takes each vehicle to reach the passenger’s point of origin and how long it takes to get to the destination. The proposed model is solved using the AUGMECON method and the NSGA II algorithm. A real case study from Sioux Falls is presented to validate the applicability of the proposed model. This study shows that ridesharing helps passengers save money using mobility services without significant change in travel time.

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Reference49 articles.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Towards a Greener and Fairer Transportation System: A Survey of Route Recommendation Techniques;ACM Transactions on Intelligent Systems and Technology;2023-12-19

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