Fixed versus variable time window warehousing strategies in real time

Warehousing includes many different regular activities such as receiving, batching, picking, packaging, and shipping goods. Several authors indicate that the picking operation might consume up to 55% of the total operational costs. In this paper, we deal with a subtask arising within the picking task in a warehouse, when the picking policy follows the order batching strategy (i.e., orders are grouped into batches before being collected) and orders are received online. Particularly, once the batches have been compiled it is necessary to determine the moment in the time when the picker starts collecting each batch. The waiting time of the picker before starting to collect the next available batch is usually known as time window. In this paper, we compare the performance of two different time window strategies: Fixed Time Window and Variable Time Window. Since those strategies cannot be tested in isolation, we have considered: two different batching algorithms (First Come First Served and a Greedy algorithm based on weight); one routing algorithm (S-Shape); and a greedy selection algorithm for choosing the next batch to collect based on the weight.

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