Optimizing storage assignment, order picking, and their interaction in mezzanine warehouses

Abstract In warehouses, order picking is known to be the most labor-intensive and costly task in which employees account for a large part of warehouse performance. Hence, many approaches exist, that optimize process based on diverse economic criteria. However, these focus single objective at once disregard ergonomic criteria their optimization. Further, influence placement items picked underestimated accordingly, too little attention paid interdependence two problems. this work, we aim optimizing storage assignment problem within mezzanine with regards reciprocal influence. We propose customized version Non-dominated Sorting Genetic Algorithm II (NSGA-II) as well an Ant Colony Optimization (ACO) algorithm problem. Both algorithms incorporate multiple constraints simultaneously. Furthermore, knowledge about between both problems, aiming improve overall Our evaluation results show our proposed return better assignments pick routes compared commonly used techniques following quality indicators comparing Pareto fronts: Coverage, Generational Distance, Euclidian Front Size, Inverted Distance. Additionally, regarding interaction shows performance when combining algorithms.