  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.
