The integrated dial-a-ride problem with timetabled fixed route service

Posada, Marcus; Andersson, Henrik; Häll, Carl Henrik

doi:10.1007/s12469-016-0128-9

Cited by 47 publications

(35 citation statements)

References 22 publications

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“…They used a passenger utility maximisation approach and modelled the assignment to travel requests to vehicles as an Integrated Diala-ride Problem (IDARP). More recently, Posada, Andersson, and Häll (2017), Häll et al (2009), and Salazar et al (2018) used a mathematical programming approach that involves solving the assignment problem as an optimisation problem by assigning travel requests to a fleet of on-demand vehicles. Posada, Andersson, and Häll (2017) and Häll et al (2009) solved the assignment problem as an Integrated Dial-A-Ride Problem (IDARP).…”

Section: Literature Reviewmentioning

confidence: 99%

Fleet size determination for a mixed private and pooled on-demand system with elastic demand

Narayan

Cats

Oort

et al. 2020

Transportmetrica A: Transport Science

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The recent emergence of innovative mobility solutions is changing the mobility landscape in urban areas. However, it remains unknown how the combined operation of private and pooled on-demand services affect service performance and the required dimensioning of the fleet size for such services. This study develops a model to determine the fleet size of an on-demand system offering private service and pooled service, where the demand for these services is an outcome of modal choices. We investigate the fleet size required when taking either the perspective of Transit Planning Authority (Agency) or Service Provider (Operator). The model is implemented for the network of Amsterdam North. Results show that the objectives of Agency and Operator yield different total fleet sizes with the Agency requiring a larger fleet than the Operator and that the optimal scenario for the Agency would be the one where only private on-demand service is offered.

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Section: Literature Reviewmentioning

confidence: 99%

Fleet size determination for a mixed private and pooled on-demand system with elastic demand

Narayan

Cats

Oort

et al. 2020

Transportmetrica A: Transport Science

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“…The differences between the PDPTW-SL and IDARP lie mainly in the human level-of-service perspective inherent to dial-a-ride problems. The formulation in Häll et al (2009) is extended in Posada et al (2017) to the integrated dial-a-ride problem with timetables (IDARP-TT) to also handle timetables for the fixed route service, as well as some further features which aim at making the model more applicable to real-world planning situations. Handling of timetabled fixed route services is essential to be able to synchronize transfers between different travel modes, or different vehicles belonging to the same mode, with the aim to minimize transfer times.…”

Section: Dial-a-ride Planningmentioning

confidence: 99%

“…The solution from the planning algorithm can be evaluated from both the operator's and passenger's perspective. metaheuristic algorithm is chosen over an exact method since it is hard to solve the combinatorial optimization problem associated with an integrated service to optimality for instances of realistic sizes (Posada, Andersson and Häll, 2017).…”

Section: Introductionmentioning

confidence: 99%

A metaheuristic for evaluation of an integrated special transport service

Posada

Häll

2020

International Journal of Urban Sciences

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This work concerns evaluation of integrated demand responsive services, in which certain parts of the passengers' door-to-door journeys are served by fixed route public transport. The purpose of combining a special transport service with a fixed route service is to reduce the high, publicly subsidized, operational costs of the special transport service. To be able to recommend in which situations, or areas, it is beneficial to use an integrated service we present a metaheuristic for solving the routing problem in such a service. The metaheuristic can be implemented as part of an evaluation tool for policy makers and officials, providing insights into the effects of an integrated demand responsive service compared to a non-integrated. The metaheuristic is based on the adaptive large neighbourhood search (ALNS) framework. It is applied to a data set from a real-world, rural, demand responsive special transport service and the fixed route service available in the area. The objective used in our heuristic is to minimize the distance driven by the demand responsive vehicles. The distance driven is strongly related to the operational cost of the service. Our tests show that the distance driven by the demand responsive vehicles is reduced by 16%, giving a substantial cost reduction for the special transport service in the given area. Highlights. Evaluation of integrated demand responsive service. Combining special transport with a fixed route service to reduce operational costs. Metaheuristic, based on the adaptive large neighbourhood search (ALNS) framework. Comparing integrated service to non-integrated ARTICLE HISTORY

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“…In the literature on dial-a-ride problems, Posada et al [41] integrate transfers to and from timetabled public transport into the classical dial-a-ride problem. Decisions on which transfer terminals to use (and thus which public transport line) are made simultaneously with vehicle routing decisions.…”

Section: Research Opportunitiesmentioning

confidence: 99%

Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions

et al. 2019

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Intermodal logistics service providers decide on the routing of demand through their service network. Long-haul routing decisions determine the selected departure and arrival terminals for containers and imply corresponding drayage tasks. Traditionally, given these long-haul routes and fixed drayage tasks, drayage operations are planned in a second phase by establishing truck routes to transport containers to and from terminals by truck. In this paper, operational decisions on local drayage routing in large-volume freight regions with multiple terminals on the one hand, and intermodal long-haul routing on the other hand are merged into an integrated intermodal routing problem. Different long-haul routing decisions imply different drayage tasks to be performed and thus impact total trucking costs. The approach aims at reducing the number of road kilometres and increases bundling opportunities by maximising the long-haul capacity utilisation. In this way, it contributes to the modal shift towards intermodal transport and a more sustainable transport system. As a weekly planning horizon is used, a maximum daily active time and a minimum overnight's rest are included for multi-day drayage routing. A large neighbourhood search heuristic is proposed to solve the integrated intermodal routing problem. This integrated planning approach provides decision support for routing customer orders throughout the intermodal network with the aim of minimising total transport costs and maximising capacity utilisation. Experiments show the added value of the integrated approach, which uses more information to make better-informed decisions and increase the capacity utilisation. The largest savings in trucking costs are obtained for clustered instances with demand characteristics closest to real-life cases. Finally, a real-life case study analyses the impact of tactical service network design decisions on the total operational costs.

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The integrated dial-a-ride problem with timetabled fixed route service

Cited by 47 publications

References 22 publications

Fleet size determination for a mixed private and pooled on-demand system with elastic demand

Fleet size determination for a mixed private and pooled on-demand system with elastic demand

A metaheuristic for evaluation of an integrated special transport service

Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions

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