Flow Balancing with Uncertain Demand for Automated Package Sorting Centers
研究了自动化包裹分拣中心中，在包裹量每日波动的情况下，如何将包裹目的地分配给二级分拣机以平衡工作负荷并遵守装载容量限制，提出了三种混合整数非线性规划模型并比较了效果。
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. The online appendix is available at https://doi.org/10.1287/trsc.2015.0662 .