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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.

Xiying Yang, Guowei Hua, Li Zhang, T.C.E Cheng, Tsan Ming Choi• 2021

Related benchmarks

TaskDatasetResultRank
RMFS Order Allocation and Robot SchedulingSynth Small (test)
Objective Value1.02e+3
14
RMFS Order Allocation and Robot SchedulingSynth-Large synthetic (test)
Objective Value2.61e+3
14
RMFS Order Allocation and Robot SchedulingSynth-Medium (test)
Objective Value1.93e+3
14
RMFS Order Allocation and Robot SchedulingReal-world Large (test)
Objective Value978.1
14
RMFS Order Allocation and Robot SchedulingReal-World Medium (test)
Objective Value792.4
14
RMFS Order Allocation and Robot SchedulingReal-world Small (test)
Objective Value465.1
14
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