Carpooling problem: A new mathematical model, branch-and-bound, and heuristic beam search algorithm

Tamannaei, Mohammad; Irandoost, Iman

doi:10.1080/15472450.2018.1484739

Cited by 30 publications

(16 citation statements)

References 32 publications

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“…In other words: one of the central conclusions of this paper is that requiring some users to walk can be beneficial to everybody and help making these emerging mobility systems to succeed. Moreover, avoiding detours can be a strategic decision when expanding on-demand systems in order to make them part of the public transport network (as studied by Hrn c ı r et al ( 2015) and Mounce et al ( 2018)), when improving the so-called MaaS systems (Hensher, 2017), and for carpooling systems in which different private users share the vehicle of one of them (Li et al, 2020;Tamannaei & Irandoost, 2019). It is worth recalling that the results and methods proposed here can be applied to any of the ridesharing systems that have emerged recently in the literature.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Optimizing a vehicle’s route in an on-demand ridesharing system in which users might walk

Fielbaum

2021

Journal of Intelligent Transportation Systems

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Within the context of a shared on-demand transport system, we study the problem of selecting the stopping points from which passengers should walk to their exact destinations (or from their exact origins). We focus on the single-vehicle case that must follow a predefined order of requests, posing the mathematical program, showing that it can be solved in polynomial time and proposing a heuristic that runs faster. We compare the optimal algorithm, the heuristic, and the routes that visit the exact request points, and we show that avoiding detours can reduce total costs by almost one fifth and vehicle costs by more than one third. The heuristic yields competitive results. Simulations over the real street network from Manhattan show that the time reduction achieved by the heuristic might be crucial to enable the system to operate in real-time.

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Section: Conclusion and Future Researchmentioning

confidence: 99%

Optimizing a vehicle’s route in an on-demand ridesharing system in which users might walk

Fielbaum

2021

Journal of Intelligent Transportation Systems

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“…Moreover, they devised a heuristic method to compute a valid upper bound. Tamannaei and Irandoost (2019) considered another variant of the home-to-work carpooling in which drivers are not known ahead of time and will be determined through optimization. They formulated this problem as an MIP, for which they developed a refined branch-andbound (B&B) algorithm.…”

Section: One-to-many Ride Matchingmentioning

confidence: 99%

Frontiers in Service Science: Ride Matching for Peer-to-Peer Ride Sharing: A Review and Future Directions

2020

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As a consequence of the sharing economy attaining more popularity, there has been a shift toward shared-use mobility services in recent years, especially those that encourage users to share their personal vehicles with others. To date, different variants of these services have been proposed that call for different settings and give rise to different research questions. Peer-to-peer (P2P) ride sharing is one such service that provides a platform for drivers to share their personal trips with riders who have similar itineraries. Unlike ride-sourcing services, drivers in P2P ride sharing have their own individual trips to make and are not driving for the sole purpose of serving rider requests. Unlike traditional carpooling, P2P ride sharing can serve on-demand and one-time trip requests. P2P ride sharing has been identified as a sustainable mode of transportation that results in several individual and societal benefits. The core of a P2P ride-sharing system is a ride-matching problem that determines ride-sharing plans for users. This paper reviews the major studies on the operations of P2P ride-sharing systems, with a focus on modeling and solution methodologies for matching, routing, and scheduling. In this paper, we classify ride-sharing systems based on their operational features and review the existing methodologies for each class. We further discuss a number of important directions for future research.

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“…This approach compares two datasets of suppliers and demanders. Optimal path in the road calculated from sequence of links to a sequence of zones [7].…”

Section: Problem Analysis and The Goal Of Researchmentioning

confidence: 99%

“…In [7] minimizes the costs of travel times. Branchand-Bound (B&B) algorithm find optimal solution of the problem.…”

Section: Problem Analysis and The Goal Of Researchmentioning

confidence: 99%

Geoinformation system for managing non-regular passenger transportation

et al. 2020

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Today there are a large number of different companies involved in non-regular passenger transport. Most of them use special software to reduce the speed of order processing and for better service management. Such programming tools often provide a convenient system for processing orders and a user interface for the contractors. Therefore, such companies have alreadу forced out other competitors from the market of passenger transport. The purpose of the research is to develop and implement an algorithm of driver's path optimization and to develop a decentralized on-line service, oriented on support of the management of nonregular passenger transport, consisting of a service for car ordering, a service for processing and executing orders and a service for managing internal private organizations. Each service is an application accessible from both a web browser and a mobile device. In the paper the theoretical basis of the management of passenger transport has been analyzed and the basic problems have been defined. The route optimization task, which was reduced to the asуmmetrical task of the salesman, was initiated. The Little algorithm for the resolution of this task was used.

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Carpooling problem: A new mathematical model, branch-and-bound, and heuristic beam search algorithm

Cited by 30 publications

References 32 publications

Optimizing a vehicle’s route in an on-demand ridesharing system in which users might walk

Optimizing a vehicle’s route in an on-demand ridesharing system in which users might walk

Frontiers in Service Science: Ride Matching for Peer-to-Peer Ride Sharing: A Review and Future Directions

Geoinformation system for managing non-regular passenger transportation

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