Abstract
The picking efficiency of warehouses assisted by KIVA robots benefit from exploiting synergy effect between order assignment and picking station scheduling. We treat an integrated optimization which contains both allocating orders and racks to multiple stations and concurrently sequencing their interlinked processing flows at each individual one. The various decisions included in our problem, which are closely associated and must be solved in real time, are often tackled separately for ease of treatment in past. We, however, develop a comprehensive mathematical model under the consideration of the minimum total rack visits. The problem can be proven NP-hard. Consequently, an efficient algorithm based on simulated annealing and dynamic programming is developed. The experimental results show that the proposed approach has more advantage in the light of solution quality as compared with actual rule-based policies. Moreover, the results reveal that ignoring order assignment policy leads to considerable optimality gaps under realistically sized settings.
Abstract (translated)
URL
https://arxiv.org/abs/2108.09056
