A novel algorithm for peer-to-peer ridesharing match problem

Ma, Ruimin; Yao, Lifei; Song, Lijun; Jin, Maozhu

doi:10.1007/s00521-018-3733-5

Cited by 13 publications

(4 citation statements)

References 21 publications

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“…Additionally, we introduce a more reasonable cost-saving allocation scheme and incorporate the concept of subsidy to improve the system performance. Ma et al (2019) discussed many-to-one ridesharing matching considering match stability and proposed a heuristic algorithm to establish stable matches. However, in their process of finding the pre-matching set, they only judged the feasibility of many-to-one matches based on the feasibility of one-to-one matching, which is proved unreasonable in this paper.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-rider Ridesharing Stable Matching Optimization

Ke,

2023

Preprint

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The rapid growth of private car ownership has led to significant issues such as traffic congestion and environmental pollution. Ridesharing has emerged as a promising solution to alleviate the negative impacts associated with private car usage. This paper focuses on the stability of ridesharing systems and establishes a single-driver multiple-rider ridesharing matching model. To solve this model, a filtering algorithm for the pre-matching set and a fast-solving algorithm for stable matching scheme are proposed. Furthermore, we introduce the concept of a subsidy distance upper limit into the ridesharing system. Remarkably, our findings indicate that with a limit of 0.1km, the distance saved generated by the subsidy amounts to 560.5% of the total subsidy. To validate our approach, we simulate ridesharing demand data using real taxi data, and design computational experiments to prove the computational efficiency of the filtering algorithm and fast-solving algorithm. The impact of various parameters on ridesharing systems is also explored.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-rider Ridesharing Stable Matching Optimization

Ke,

2023

Preprint

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“…Furthermore, their proposed model was an SDSR problem that was limited to realistic and substantial service. Ma et al ( 21 ) modified the algorithm by introducing the theory of two-sided matching to solve the ride-sharing stable matching problem by considering cases in which a driver may receive identical benefits for a match with a rider which turned the problem into a stable matching problem with incomplete preference. Also, their developed model was an SDMR problem which is more useful than SDSR.…”

Section: Literature Reviewmentioning

confidence: 99%

Developing an Optimal Peer-to-Peer Ride-Matching Problem Algorithm with Ride Transfers

Nickkar

Lee

Meskar

2022

Transportation Research Record: Journal of the Transportation R

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Thanks to recent developments in ride-hailing transit services throughout the world, the peer-to-peer (P2P) ride-matching problem has been actively considered in academia in recent years. P2P ride-matching not only reduces travel costs for riders but also benefits drivers by saving them money in exchange for their additional travel time. However, assigning riders to drivers in an efficient way is a complex problem that requires focusing on maximizing the benefits for both riders and drivers. This study aims to formulate a multi-driver multi-rider (MDMR) P2P ride-matching problem, based on rational preferences and cost allocation for both driver and rider, which also allows riders to transfer between multiple drivers for their travels if needed. Tabu Search (TS) for system-optimal ride-matching and a Greedy Matching (GM) algorithm for stable ride-matching were developed to solve ride-matching cases. The results show that the developed algorithm can successfully solve the proposed P2P MDMR ride-matching problem. MDMR P2P ride-matching can be used in areas where not much demand for ride-sharing exists, or for long-distance travel. Also it can be applied to designs for a more efficient on-demand transit network which can allow for transfers between routes. Moreover, the comparison of results between two implemented approaches shows that system-optimal centralized ride-matching can bring more cost savings for all participants in the system, although it may not always be stable when riders and drivers can choose their ride-matching for their own maximum benefit.

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“…Furthermore, the authors of [56] introduced two-sided matching in building a singledriver multiple-rider ridesharing problem with consideration of a system-wide optimal and stable matching. The recursive algorithm and a delete operator are proposed as the solution method in solving the ridesharing model.…”

Section: One-to-many Ridesharing Problemmentioning

confidence: 99%

Shared Mobility Problems: A Systematic Review on Types, Variants, Characteristics, and Solution Approaches

et al. 2021

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The Shared Mobility Problems (SMP) with the rideshare concept based on sharing a vehicle are fast becoming a trend in many urban cities around the world. Examples of these problems are like ridesharing, carpooling, taxisharing, buspooling, vanpooling, and multi-modal ridesharing. This is the new way to access transportation services by those who are propelling the sharing economy, where access rather than ownership is the new norm. This paper provides a systematic review of SMP using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method. A total of 110 papers from the last decade are selected from 12 abstracts and citation databases to be reviewed and classified. This is done based on the problem types, variants, characteristics, and solution approaches. The current trends and analysis of the survey findings are also summarised. From this systematic review, it is observed that both the time window and multi-objective problems are popular among the researchers, while the minimisation of the total cost is the main concern in the literature of the SMP. Both static and dynamic cases of the SMP are the most researched where heuristic and metaheuristic approaches are widely adopted by the researchers in the literature. Finally, challenges and suggestions for future work are discussed and highlighted.

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A novel algorithm for peer-to-peer ridesharing match problem

Cited by 13 publications

References 21 publications

Multi-rider Ridesharing Stable Matching Optimization

Multi-rider Ridesharing Stable Matching Optimization

Developing an Optimal Peer-to-Peer Ride-Matching Problem Algorithm with Ride Transfers

Shared Mobility Problems: A Systematic Review on Types, Variants, Characteristics, and Solution Approaches

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