Scheduling the truckload operations in automated warehouses with alternative aisles for pallets

Abstract

Graphical abstractDisplay Omitted HighlightsScheduling of truck load operations problem in automated warehouses is investigated.The problem includes both the sequencing of pallets and selection of aisles.A real life problem is modelled as a flexible job shop scheduling problem.A hybrid genetic algorithm is applied to raise the warehouse management system.Flexibility of aisle selection improves the total loading time and throughput. In this study, the scheduling of truck load operations in automated storage and retrieval systems is investigated. The problem is an extension of previous ones such that a pallet can be retrieved from a set of alternative aisles. It is modelled as a flexible job shop scheduling problem where the loads are considered as jobs, the pallets of a load are regarded as the operations, and the forklifts used to remove the retrieving items to the trucks are seen as machines. Minimization of maximum loading time is used as the objective to minimize the throughput time of orders and maximize the efficiency of the warehouse. A priority based genetic algorithm is presented to sequence the retrieving pallets. Permutation coding is used for encoding and a constructive algorithm generating active schedules for flexible job shop scheduling problem is applied for decoding. The proposed methodology is applied to a real problem arising in a warehouse installed by a leading supplier of automated materials handling and storage systems.