Highlights Our model integrates parking availability in long-haul truck planning. We model parking availability as time-windows in a resource-constrained shortest-path problem. Disregarding parking availability can significantly distort cost estimates. We estimate the cost of not finding parking through simulation. Illegal parking costs may exceed cost increases caused by parking constraints.

    Abstract The US Hours-of-Service (HOS) regulations require truck drivers to take regular breaks. However, drivers often have difficulty finding appropriate rest locations due to truck parking shortages. This may have a significant impact on drivers’ safety and productivity, cost to industry and environment. In this paper, we propose a model that takes into account parking availability when planning long-haul truck shipments in addition to HOS constraints. Given an ordered set of clients, the proposed method plans a minimum cost route and schedule such that the itinerary is regulation-compliant, and the driver is guaranteed to find parking at all scheduled stops. The problem is modeled as a shortest path problem with resource constraints, and a label correcting algorithm is used to generate optimal solutions. Computational experiments are used to compare the cost of solutions that use parking availability information with ones that do not. The cost of disregarding parking information was estimated by simulating drivers’ behavior when parking is unavailable and applying time and cost penalties. The effect of parking availability and alternative routes on trip costs is also studied, aiming to illustrate that disregarding these factors can lead to significant errors in cost estimates. Results show that, although imposing parking constraints can significantly increase costs, preventing accident-related costs can make it advantageous in the long-term.


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    Title :

    Scheduling and shortest path for trucks with working hours and parking availability constraints


    Contributors:


    Publication date :

    2021-04-04


    Size :

    37 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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