Package carriers use sophisticated automated sorting facilities to efficiently process inbound packages and sort them to their down line destinations. During each of several daily processing windows, primary sorters perform high level sortation of the packages and direct them to one of several secondary sorters that are then used to segregate the packages by their outbound loading destinations. We examine the problem of assigning package destinations to the secondary sorters in a way that balances the workload in the facility, while incorporating the day-to-day fluctuation in package volumes and adhering to the outbound loading capacities of the various workcenters in the facility. We present a general stochastic modeling framework using chance constraints to balance the flows, and robust constraints to model the capacity limits. We propose and evaluate the performance of three alternative mixed integer nonlinear formulations for the problem and determine which is most effective. Significant improvement in package flow balance and loading capacity robustness is shown for the test sorting facilities by comparing the solutions from the proposed new model to those obtained when ignoring, partially or completely, the stochasticity in the package volumes.


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    Title :

    Flow Balancing with Uncertain Demand for Automated Package Sorting Centers




    Publication date :

    2016




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    Local classification TIB:    770/1935/7000
    BKL:    55.80 / 55.80 Verkehrswesen, Transportwesen: Allgemeines



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