Solving the order batching and sequencing problem with multiple pickers: A grouped genetic algorithm

This paper introduces a grouped genetic algorithm (GGA) to solve the order batching and sequencing problem with multiple pickers (OBSPMP) objective of minimizing total completion time. To best our knowledge, for first time, an OBSPMP is solved by means GGA considering picking devices heterogeneous load capacity. For this, encoding scheme proposed represent in chromosome orders assigned batches, batches devices. Likewise, operators are adapted specific requirements OBSPMP. Computational experiments show that performs much better than six heuristics, leading function savings 18.3% on average. As conclusion, provides feasible solutions operations planning warehouses distribution centers, improving margins reducing operating time pickers, customer service times.