Joint order assignment and picking station scheduling in KIVA warehouses with multiple stations
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| RMFS Order Allocation and Robot Scheduling | Synth Small (test) | Objective Value1.02e+3 | 14 | |
| RMFS Order Allocation and Robot Scheduling | Synth-Large synthetic (test) | Objective Value2.61e+3 | 14 | |
| RMFS Order Allocation and Robot Scheduling | Synth-Medium (test) | Objective Value1.93e+3 | 14 | |
| RMFS Order Allocation and Robot Scheduling | Real-world Large (test) | Objective Value978.1 | 14 | |
| RMFS Order Allocation and Robot Scheduling | Real-World Medium (test) | Objective Value792.4 | 14 | |
| RMFS Order Allocation and Robot Scheduling | Real-world Small (test) | Objective Value465.1 | 14 |