We just received the nice news that our paper “The Share-a-Ride Problem: People and Parcels Sharing Taxis” is accepted for publication in European Journal of Operational Research. This joint work with Boaxiang Li, Dmitry Krushinsky and Hajo Reijers looks into the challenging issue to combine freight and people into the same (people-oriented) transportation mode. Similar to the recent blog by Transportationist (see here), the key idea is to make different systems “bigger, inter-connecting and inter-operating, and even merging them”.
In many real-life situations, especially in urban areas, people and freight transportation operations are handled separately. New city logistics approaches are needed to ensure efficient urban mobility for both people and goods. Little research is available on the efficiency gains that can be obtained by combining individual freight and passenger transportation streams. A lack of real-time information and the increased planning complexity due to such a combination are among the main reasons. Usually, these are handled independently in dedicated networks. Our research fills in this gap and explores People and Freight Integrated Transportation problems (PFIT problems) with a particular focus on taxis.
This figure reflects the trails of 528 taxis in San Francisco, based on one month data.
This paper considers conceptual and mathematical models in which people and parcels are handled in an integrated way by the same taxi network. From a city perspective, this system has a potential to alleviate urban congestion and environmental pollution. From the perspective of a taxi company, new benefits from the parcel delivery service can be obtained. We propose two multi-commodity sharing models. The Share-a-Ride Problem (SARP) is discussed and defined in detail. A reduced problem based on the SARP is proposed: the Freight Insertion Problem (FIP) starts from a given route for handling people requests and inserts parcel requests into this route. We present MILP formulations and perform a numerical study of both static and dynamic scenarios. The obtained numerical results provide valuable insights into successfully implementing a taxi sharing service.
The numerical results show that there exists a trade-off between the profit of a taxi company and the acceptance rate of parcels. In addition, the results suggest that it is desirable to analyze the spatial characteristics of requests before implementing a taxi sharing service, because the spatial distribution of requests can dramatically affect the performance of the taxi sharing system. Finally, we have shown that the performance of the system is the highest in case the spatial distribution of requests resembles a pattern inherent to cities. This makes taxi-sharing quite promising for urban areas. In general, our numerical study confirms appropriateness of the taxi-sharing systems but suggests that a traditional freight service must also be available to ensure that all requests are served.
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