Online rescheduling of multiple picking agents for warehouse management

In this paper, we present a solution for a dynamic rescheduling problem involving new orders arriving randomly while static orders have been given in advance in warehouse environments. We propose two variations of an incremental static scheduling scheme: one based on the steepest descent insertion, called OR1, and the other, on multistage rescheduling, called OR2. Both techniques are enhanced by a local search procedure specifically designed for the problem at hand. We also implemented several existing online algorithms to our problem for evaluative purposes. Extensive statistical experiments based on real picking data indicate that the proposed methodologies are competitive with existing online schedulers and show that load-balancing algorithms, such as OR1, yield the best results on the average and that OR2 is effective in reducing the picking time when dynamism is low to moderate.