Abstract The line-haul feeder vehicle routing problem (LFVRP) is a rather new and therefore hardly investigated problem and can be seen as vehicle routing problem with synchronisation constraints. Synchronisation takes place if two or more vehicles (small and large vehicles) meet at the same place and at the same time and perform a transshipment of goods. Small vehicles are used to serve customers which are difficult to access (e.g. due to traffic jams, narrow streets or limited parking space). The downside is their limited capacity. To avoid the journey back to the depot, the small vehicle can meet with a large vehicle at a customer with enough space for reloading. Thus, the small vehicle uses the large vehicle as virtual depot and is able to save time and reduce costs. In Brandstätter and Reimann (Eur J Oper Res 270:157–170, 2018), we already introduced two promising solution approaches to master the LFVRP—the Linkage- and Split-Approach. Both approaches were shown to find high-quality solutions in short time. Moreover, we demonstrated the advantage of the LFVRP strategy when compared with the heterogeneous fleet vehicle routing problem. With this paper, we propose and justify several improvements to our original algorithms. These include the application of Ant Colony Optimization, different local search operators, as well as the exact solution of a sub-problem. To highlight the performance contribution of these modifications, we perform a thorough and extensive computational experiment. We evaluate each algorithmic component individually as well as their combination and statistically validate the benefits. Overall, we find that the final algorithm improves our previous approaches by almost 9% at a computational cost of a few seconds.


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    Titel :

    Performance analysis of a metaheuristic algorithm for the line-haul feeder vehicle routing problem


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    02.08.2018


    Format / Umfang :

    18 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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