Abstract: A material conveying method, device and system and a storage medium. The method specifically includes: first determining a target conveying route from a plurality of candidate conveying routes according to a route planning model; then generating a conveying instruction according to the target conveying route and user order information; and finally sending the conveying instruction to a conveying device to enable the conveying device to convey a material from a source node of supply to a user node via the target conveying route, where the candidate conveying routes refer to routes from a source node of supply to a user node via at least one candidate warehouse. The present method can realize warehouse route planning and material transportation control.

Abstract: In the method according to embodiments, a characteristic vector of a preset dimension is generated based on attribute information of the to-be-shelved product in each attribute of a preset attribute set, and the generated characteristic vector is imported into a pre-trained current-period outbound quantity prediction model to obtain a predicted current-period outbound quantity of the to-be-shelved product; a shelving cost of the shelving task is determined based on a current inventory of the to-be-shelved product in the target warehouse, the to-be-shelved number, a volume of the to-be-shelved product, and the predicted current-period outbound quantity of the to-be-shelved product; a central storage position of the shelving task is determined based on the shelving cost of the shelving task, a predetermined product shelving cost table and a predetermined storage position shelving path length table; and a recommended storage position information set corresponding to the shelving task is generated and outputted.

Abstract: In the method according to embodiments, a characteristic vector of a preset dimension is generated based on attribute information of the to-be-shelved product in each attribute of a preset attribute set, and the generated characteristic vector is imported into a pre-trained current-period outbound quantity prediction model to obtain a predicted current-period outbound quantity of the to-be-shelved product; a shelving cost of the shelving task is determined based on a current inventory of the to-be-shelved product in the target warehouse, the to-be-shelved number, a volume of the to-be-shelved product, and the predicted current-period outbound quantity of the to-be-shelved product; a central storage position of the shelving task is determined based on the shelving cost of the shelving task, a predetermined product shelving cost table and a predetermined storage position shelving path length table; and a recommended storage position information set corresponding to the shelving task is generated and outputted.