On-line order batching and sequencing problem with multiple pickers: A hybrid rule-based algorithm

Abstract Existing on-line order batching rules, namely fixed time window batching (FTWB) and variable time window batching (VTWB), try to choose the fixed time window in the case of FTWB or the fixed number of orders in the case of VTWB. However, these solutions are not appropriate for the fluctuating order environment. The reasonable assignment of batches to order pickers is also an important issue in order picking systems. Motivated by these issues, we study the problem of integrating on-line order batching and the assignment of the batches, which is called the on-line order batching and sequencing problem with multiple pickers (OOBSPMP). The objective is to minimize the turnover time. To solve the problem, a hybrid rule-based algorithm, referred to FTWB, is proposed in order to form batches and assign them to appropriate pickers under a fluctuating order environment. Three batching situations (off-peak, normal and peak arrival time) and two assigning situations (assigning to one busy picker and assigning to one idle picker) are distinguished. Through a series of experiments, we discover several enlightening findings: (i) the rule-based algorithm demonstrates high effectiveness and efficiency in turnover time with multiple pickers; (ii) the rule-based algorithm leads to an impressive improvement in both saving time and wage costs under different arrival rates, picking devices and time intervals compared with VTWB; (iii) to obtain both good warehouse performance and a reasonable workload distribution, the factors, such as the fixed time window, the average workload per picker and the average idle time per picker are also important issues in analysing the efficiency of order picking systems.

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