A multi-period dial-a-ride problem with driver consistency

•We propose the first dial-a-ride problem that considers service consistency.•Two formulations are proposed and solved by a tailored Branch-and-Cut algorithm.•A simple metaheuristic generates near-optimal solutions in a short amount of time.•An extensive numerical analysis with more than 1000 instan...

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Veröffentlicht in:Transportation research. Part B: methodological 2016-12, Vol.94, p.355-377
Hauptverfasser: Braekers, Kris, Kovacs, Attila A.
Format: Artikel
Sprache:eng
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Zusammenfassung:•We propose the first dial-a-ride problem that considers service consistency.•Two formulations are proposed and solved by a tailored Branch-and-Cut algorithm.•A simple metaheuristic generates near-optimal solutions in a short amount of time.•An extensive numerical analysis with more than 1000 instances is presented.•Transporting users with 2 drivers is a good compromise between consistency and cost. Dial-a-ride services provide disabled and elderly people with a personalized mode of transportation to preserve their mobility. Typically, several users with different pickup and dropoff locations are transported on a vehicle simultaneously. The focus in dial-a-ride problems (DARPs) is mainly on minimizing routing cost. Service quality has been taken into account in the models by imposing time windows and limiting the maximum ride time of each user. We extend the classical DARP by an additional feature of service quality referred to as driver consistency. Customers of dial-a-ride services are often sensitive to changes in their daily routine. This aspect includes the person who is providing the transportation service, i.e., the driver of the vehicle. Our problem, called the driver consistent dial-a-ride problem (DC-DARP), considers driver consistency by bounding the maximum number of different drivers that transport a user over a multi-period planning horizon. We propose different formulations of the problem and examine their efficiency when applied in a Branch-and-Cut fashion. Additionally, we develop a large neighborhood search algorithm that generates near-optimal solutions in a short amount of time. Over 1000 instances are generated with close reference to real world scenarios. Extensive computational experiments are conducted in order to assess the quality of the solution approaches and to provide insights into the new problem. Results reveal that the cost of offering driver consistency varies greatly in magnitude. Depending on the instance, the cost of assigning one driver to each user can be up to 27.98% higher compared to a low-cost solution. However, routing cost increases by not more than 5.80% if users are transported by at least two drivers.
ISSN:0191-2615
1879-2367
DOI:10.1016/j.trb.2016.09.010