A Genetic Algorithm for Order Picking in Automated Storage and Retrieval Systems with Multiple Stock Locations

This research deals with an order picking problem in automated storage and retrieval systems (AS/RS). When retrieval requests consist of multiple items and the items are in multiple stock locations, the storage/retrieval (S/R) machine must travel to numerous storage locations to complete each order. The aim of this research is to propose algorithms for the resolution of order picking problems with multiple stock locations to minimize the total time traveled by the S/R machine. We present and compare three alternatives for solving the problem based on enumeration, ordinary heuristic and genetic algorithms. We used a set of 180 different problems that are solved by these three algorithms. The results show that our proposed genetic algorithm is more efficient than the other two.