Computing Optimized Stock (Re-)Placements in Last-In, First-Out Warehouses

摘要: Within this work, we focus on the optimization of storage location assignments arising in warehouses with locations applying a last-in, first-out throughput policy. The sequence goods to be stored is, however, not entirely known such that for each item currently best has identified almost immediately. Caused by imperfect data and stock removals concurrently performed it is necessary apply relocation operations from time time, which might range few relocations lasting working day depending workload warehousemen. For purpose propose an ad hoc stocking strategy as well based variable neighborhood descent. Supported experimental tests compare variants our approaches other formerly used strategies showing number conflicts could significantly reduced proposed approach. Furthermore, application can improve warehouse states obtained due strategies, insufficient information production sequences.