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.

翻译：我们研究了机器人辅助KIVA仓库中多站订单分配以及各站内订单流与料架流相互关联的排序问题。该问题涉及多种紧密关联且需实时求解的决策，为简化处理通常分别求解。然而，利用订单分配与拣选站调度之间的协同效应可提升拣选效率。我们构建了考虑协同效应的综合数学模型，以最小化总料架访问次数。为求解这一复杂问题，我们基于模拟退火与波束搜索开发了高效算法。计算研究表明，所提方法在解质量上优于基于规则的贪心策略及独立拣选站调度方法，相较于两者分别减少了超过三分之一和五分之一的料架访问次数。