Joint order assignment and picking station scheduling in KIVA warehouses with multiple stations
This addresses efficiency improvements for robot-assisted warehouse operations, though it is incremental as it builds on existing methods.
The paper tackles the problem of jointly assigning orders and scheduling picking stations in KIVA warehouses to minimize rack visits, resulting in savings of over one-third and one-fifth compared to baseline methods.
We consider the problem of allocating orders to multiple stations and sequencing the interlinked order and rack processing flows in each station in the robot-assisted KIVA warehouse. The various decisions involved in the problem, which are closely associated and must be solved in real time, are often tackled separately for ease of treatment. However, exploiting the synergy between order assignment and picking station scheduling benefits picking efficiency. We develop a comprehensive mathematical model that takes the synergy into consideration to minimize the total number of rack visits. To solve this intractable problem, we develop an efficient algorithm based on simulated annealing and beam search. Computational studies show that our proposed approach outperforms the rule-based greedy policy and the independent picking station scheduling method in terms of solution quality, saving over one-third and one-fifth of rack visits compared with the former and latter, respectively.