CN118220712A - Stacker scheduling method, device, equipment and storage medium - Google Patents

Abstract

The embodiment of the application discloses a stacker scheduling method, a stacker scheduling device, stacker scheduling equipment and a storage medium, wherein the method comprises the following steps: based on N first stock units SKU required by cargo delivery task demands, the number N of the first SKUs, the positions of the N first SKUs in a goods shelf, the capacity P of a conveyor belt and the positions of P second SKUs currently parked on the conveyor belt in the goods shelf, P grabbing paths with capacity constraint are obtained, grabbing sequences of all the N first SKUs are obtained based on the P grabbing paths with capacity constraint, and a scheduling stacker sequentially places the N first SKUs in the P position of the conveyor belt from the goods shelf according to the grabbing sequences of all the first SKUs. Wherein N and P are integers greater than 1. By adopting the embodiment of the application, the empty load moving time of the stacker can be reduced, thereby improving the working efficiency of the stacker.

Description

Stacker scheduling method, device, equipment and storage medium

Technical Field

The application relates to the technical field of automatic logistics, in particular to a stacker scheduling method, device and equipment and a storage medium.

Background

Along with the rapid development of the logistics industry, the demand for automated logistics is higher and higher at the present stage, and the stacker is widely applied to the logistics business process of factories due to the characteristic of high automation degree. In the logistics business process, the warehousing system performs path planning according to the positions of goods in the delivery tasks, determines the grabbing order, and dispatches the stacker to grab the goods according to the grabbing order and places the goods on the delivery conveyor belt.

However, the same job of leaving warehouse has different work efficiency of the stacker due to different management methods, decision means and methods of scheduling operations. Therefore, how to improve the working efficiency of the stacker without changing the warehouse hardware facilities is a problem to be solved.

Disclosure of Invention

The embodiment of the application provides a method, a device, equipment and a storage medium for scheduling a stacker, which can reduce the empty load moving time of the stacker, thereby improving the working efficiency of the stacker.

In a first aspect, an embodiment of the present application provides a stacker scheduling method, including:

According to the cargo delivery task demand, N first stock units (stock keeping un it, SKUs) and the positions of the N first SKUs in a goods shelf required by the cargo delivery task demand are determined, the capacity P of a conveyor belt and the positions of P second SKUs currently parked on the conveyor belt in the goods shelf are obtained, then based on the N first SKUs, the number N of the first SKUs, the positions of the N first SKUs in the goods shelf, the capacity P of the conveyor belt and the positions of the P second SKUs in the goods shelf, P capacity-constrained grabbing paths are obtained, the grabbing sequence of each first SKU in the N first SKUs is obtained based on the P capacity-constrained grabbing paths, and the stacker is scheduled to sequentially place the N first SKUs in the P position in the conveyor belt from the goods shelf according to the grabbing sequence of each first SKU. The movement distance corresponding to the grabbing path with capacity constraint is calculated based on the Chebyshev distance. N and P are integers greater than 1.

According to the embodiment of the application, the vehicle path planning problem is applied to a stacker scheduling scene, P grabbing paths with capacity constraint can be obtained, the grabbing sequence of each first SKU in N first SKUs can be calculated once according to the P grabbing paths with capacity constraint, calculation of each time of warehouse-out and warehouse-in is omitted, the calculation delay problem under multitasking (warehouse-in and warehouse-out tasks) is reduced, and meanwhile, the empty load moving distance of the stacker can be minimized, so that the empty load moving time of the stacker is shortened, and the working efficiency of the stacker is improved.

With reference to the first aspect, in a possible implementation manner, obtaining P gripping paths with capacity constraint on a shelf based on the N first SKUs, the number N of first SKUs, positions of the N first SKUs in the shelf, the capacity P of the conveyor belt, and the P second SKUs includes:

The capacity K of each of the P second SKUs and the capacity M of each of the N first SKUs are determined based on the number N of the first SKUs and the capacity P of the conveyor belt, and the path capacity Q is determined based on the number N of the first SKUs and the capacity P of the conveyor belt. Taking the number N of the first SKUs, the positions of the N first SKUs in the shelf, the capacity P of the conveyor belt, the positions of the P second SKUs in the shelf, the capacity K of each second SKU in the P second SKUs, the capacity M of each first SKU in the N first SKUs and the path capacity Q as input parameters of a path algorithm for calculating a grabbing path with capacity constraint, and obtaining P grabbing paths with capacity constraint based on the path algorithm and the input parameters. Wherein K and M are positive integers and Q is an integer less than N and greater than 1. In the application, P grabbing paths with capacity constraint are obtained based on a path algorithm with capacity constraint, and the grabbing paths are shortest paths in all paths generated by N first SKUs after the stacker grabs, so that the empty load moving distance of the stacker is minimized.

With reference to the first aspect, in a possible implementation manner, the determining, based on the number N of the first SKUs and the capacity P of the conveyor belt, the capacity K of each of the P second SKUs and the capacity M of each of the N first SKUs includes:

the capacity of the second SKU with the position index greater than or equal to L is set to 2, the capacity of the second SKU with the position index smaller than L is set to 1, and then the capacity of each of the N first SKUs is set to 1. Wherein L is obtained from N and P. Illustratively, L can be calculated by (1+ (N-1)% P). In the application, the capacity of each second SKU and the capacity of each first SKU are determined, so that the path corresponding to the second SKU with the front position index is larger than or equal to the path corresponding to the second SKU with the rear position index, and the P paths obtained by the warehousing system based on the path algorithm can be applied to stacker scheduling.

With reference to the first aspect, in a possible implementation manner, the determining the path capacity Q based on the number N of the first SKUs and the capacity P of the conveyor belt includes:

And determining an integer obtained by upwardly rounding the ratio of N to P and adding 1 as the value of the path capacity Q, wherein the sum of the capacities of the SKUs of each grabbing path in the P grabbing paths with capacity constraint is smaller than or equal to Q. In the application, the warehousing system determines the path capacity, and the length difference between each path is not more than 1, so that the P paths obtained by the warehousing system based on the path algorithm can be applied to stacker scheduling.

With reference to the first aspect, in a possible implementation manner, the obtaining, based on the P capacity-constrained grabbing paths, a grabbing order of each first SKU of the N first SKUs includes:

And determining the j-th first SKU in the grabbing path i as the (i+ (j-1) P) -th first SKU in the grabbing sequence of the N first SKUs to obtain the grabbing sequence of each first SKU in the N first SKUs, wherein the grabbing path i is a grabbing path with capacity constraint corresponding to the i-th second SKU in the conveyor belt. Wherein i has a value of 1,2, … P, if the i second SKU has a capacity of 1, j has a value of 1,2, … (Q-1), and if the i second SKU has a capacity of 2, j has a value of 1,2, … (Q-2). A capacity constrained grabbing path comprises a second SKU and at most (Q-1) grabbing orders of the first SKUs, wherein the grabbing orders of the second SKU are before the grabbing orders of the first SKU in the at most (Q-1), and a second SKU corresponds to the capacity constrained grabbing path. In the application, the warehousing system obtains the grabbing sequence of each first SKU in the N first SKUs based on the P grabbing paths with capacity constraint, and the P paths obtained based on the path algorithm can be applied to stacker scheduling.

With reference to the first aspect, in a possible implementation manner, the scheduling stacker sequentially places the N first SKUs from the shelf to a P-th position in the conveyor belt in a grabbing order of the respective first SKUs, including:

And (3) scheduling the stacker to replace the first SKU in the conveyor belt from the conveyor belt to the goods shelf, and placing the ith first SKU from the goods shelf to the P position in the conveyor belt according to the grabbing sequence of the first SKUs, wherein the value of i is 1,2 and … N. In the application, when the warehouse system dispatches the stacker to put the SKU back to the warehouse from the conveyor belt, the stacker will put the SKU back to the original position, thereby avoiding the change of the SKU position and avoiding the frequent update of the warehouse system to the SKU position information and the quantity information.

With reference to the first aspect, in a possible implementation manner, the movement distance corresponding to the grabbing path with capacity constraint is further obtained based on a manhattan distance. For example, when the stacker can move forward and backward, up and down at the same time, the moving distance may be calculated based on chebyshev distance, and when the stacker cannot move forward and backward, up and down at the same time (cannot move up and down when moving forward and backward, or cannot move left and right when moving up and down), the moving distance may be calculated based on manhattan distance.

In a second aspect, an embodiment of the present application provides a stacker scheduling apparatus, including:

the input module is used for receiving the cargo delivery task demand;

The determining module is used for determining N first stock quantity units (SKUs) and positions of the N first SKUs in the goods shelf, wherein the N first stock quantity units (SKUs) are required by the goods delivery task demands and received by the input module, and N is an integer greater than 1;

The acquisition module is used for acquiring the capacity P of the conveyor belt and the positions of P second SKUs currently parked on the conveyor belt in a goods shelf, wherein P is an integer greater than 1;

the acquisition module is further used for acquiring P grabbing paths with capacity constraint based on the N first SKUs, the number N of the first SKUs, the positions of the N first SKUs in the goods shelf, the capacity P of the conveyor belt and the positions of the P second SKUs in the goods shelf, and the moving distance corresponding to the grabbing paths with capacity constraint is calculated based on Chebyshev distance;

the acquisition module is further used for acquiring the grabbing sequence of each first SKU in the N first SKUs based on the P grabbing paths with capacity constraint;

and the scheduling module is used for scheduling the stacker to sequentially put the N first SKUs into the P position in the conveyor belt from the goods shelf according to the grabbing sequence of each first SKU.

With reference to the second aspect, in a possible implementation manner, the determining module is further configured to determine, based on the number N of the first SKUs and the capacity P of the conveyor belt, a capacity K of each of the P second SKUs and a capacity M of each of the N first SKUs, where K and M are positive integers; the determining module is further configured to determine a path capacity Q based on the number N of the first SKUs and the capacity P of the conveyor belt, where Q is an integer less than N and greater than 1; the acquiring module is further configured to take the number N of the first SKUs, the positions of the N first SKUs in the shelf, the capacity P of the conveyor belt, the positions of the P second SKUs in the shelf, the capacity K of each second SKU in the P second SKUs, the capacity M of each first SKU in the N first SKUs, and the path capacity Q as input parameters of a path algorithm with capacity constraint, and acquire P grabbing paths with capacity constraint based on the path algorithm.

With reference to the second aspect, in a possible implementation manner, the determining module is further configured to: setting the capacity of a second SKU with a position index greater than or equal to L to 2, and setting the capacity of a second SKU with the position index less than L to 1, wherein L is obtained from N and P; the capacity of each of the N first SKUs is set to 1.

With reference to the second aspect, in a possible implementation manner, the determining module is further configured to: and determining an integer obtained by upwardly rounding the ratio of N to P and adding 1 as the value of the path capacity Q, wherein the sum of the capacities of the SKUs of each grabbing path in the P grabbing paths with capacity constraint is smaller than or equal to Q.

With reference to the second aspect, in a possible implementation manner, the determining module is further configured to: and determining the j-th first SKU in the grabbing path i as the (i+ (j-1) P) -th first SKU in the grabbing sequence of the N first SKUs to obtain the grabbing sequence of each first SKU in the N first SKUs, wherein the grabbing path i is a grabbing path with capacity constraint corresponding to the i-th second SKU in the conveyor belt. Wherein i has a value of 1,2, … P, if the i second SKU has a capacity of 1, j has a value of 1,2, … (Q-1), if the i second SKU has a capacity of 2, j has a value of 1,2, … (Q-2), a capacity-constrained grabbing path includes a second SKU and at most (Q-1) first SKUs in a grabbing order, and the grabbing order of the second SKU is before the first SKU in the at most (Q-1), a second SKU corresponds to a capacity-constrained grabbing path.

With reference to the second aspect, in a possible implementation manner, the scheduling module is further configured to: and (3) scheduling the stacker to replace the first SKU in the conveyor belt from the conveyor belt to the goods shelf, and placing the ith first SKU from the goods shelf to the P-th position in the conveyor belt according to the grabbing sequence of the first SKUs, wherein the value of i is 1,2 and … N.

In a third aspect, the present application provides a computer device comprising a processor and a memory; the processor is connected to the memory, where the memory is configured to store a computer program, and the processor is configured to invoke the computer program to cause the computer device to execute the stacker scheduling method provided by the foregoing first aspect or any one of the possible implementation manners of the first aspect, and also achieve the beneficial effects provided by the stacker scheduling method provided by the foregoing first aspect.

In a fourth aspect, the present application provides a computer readable storage medium, where the computer readable storage medium is configured to store a computer program, where the computer program when executed on a computer causes the computer to execute the stacker scheduling method provided in the first aspect or any one of the possible implementation manners of the first aspect, and also implements the beneficial effects provided by the stacker scheduling method provided in the first aspect.

By adopting the embodiment of the application, the empty load moving time of the stacker can be reduced, thereby improving the working efficiency of the stacker.

Drawings

In order to more clearly describe the embodiments of the present application or the technical solutions in the background art, the following description will describe the drawings that are required to be used in the embodiments of the present application or the background art.

FIG. 1 is a workflow diagram of a logistics business provided by an embodiment of the present application;

fig. 2 is a schematic flow chart of a stacker scheduling method according to an embodiment of the present application;

FIG. 3 is a schematic diagram of two different stacker scheduling schemes according to an embodiment of the present application;

Fig. 4 is an equivalent schematic diagram of a movement track and a path of a stacker provided in an embodiment of the present application;

fig. 5 is a schematic diagram of a stacker scheduling scheme according to an embodiment of the present application;

Fig. 6 is a schematic diagram of a stacker scheduling scheme based on the HSG-CVPR algorithm according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a stacker scheduling apparatus according to an embodiment of the present application;

fig. 8 is a schematic structural diagram of a computer device according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application.

In the description of the present application, the words "first", "second", etc. are used only to distinguish different objects, and are not limited to numbers and execution orders, and the words "first", "second", etc. are not necessarily different. Furthermore, the terms "comprising," "including," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion. Such as a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to the list of steps or elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

In the present application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary," "by way of example," or "such as" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "by way of example," or "such as" is intended to present related concepts in a concrete fashion.

It should be understood that, in the present application, "when …", "if" and "if" all refer to the fact that the device will perform the corresponding process under some objective condition, and are not limited in time, nor do they require that the device be implemented with a judging action, nor are they meant to imply other limitations.

Elements referred to in the singular are intended to be used in the present disclosure as "one or more" rather than "one and only one" unless specifically stated otherwise.

It should be understood that in embodiments of the present application, "B corresponding to A" may mean that B is associated with A, from which B may be determined. It should also be understood that determining/generating B from a does not mean determining/generating B from a alone, but may also determine/generate B from a and/or other information.

The stacker scheduling method provided by the embodiment of the application can be applied to logistics business. Referring to fig. 1, fig. 1 is a workflow diagram of a logistics service provided by an embodiment of the present application, where the logistics service may be implemented together by the following systems: an enterprise resource planning (ENTERPRISE RESOURCE PLANNING, ERP) system, a manufacturing execution system (manufacturing execution system, MES), a warehouse management system (warehouse MANAGEMENT SYSTEM, WMS), a warehouse control system (warehouse control system, WCS) and a library erecting system. The ERP system is a management platform which is based on information technology and provides decision operation means for an enterprise decision-making layer and staff by using a systematic management idea. The MES system is a production informatization management system facing the workshop execution layer of a manufacturing enterprise. WMS is a real-time computer software system that is capable of managing information, resources, activities, inventory and distribution operations according to operational business rules and algorithms. The WCS system is used to guide real-time activities within warehouses and distribution centers. The vertical warehouse system is an automatic warehouse logistics system for multi-layer three-dimensional storage of goods, and consists of a plurality of rows of high-rise shelves, roadways, a plurality of roadway stacker, a top rail, a ground rail, a warehouse in-out conveying device, an automatic control and management system and the like, and is used for dispatching the stacker to grab or put back the goods. As shown in fig. 1, in the logistics business, the ERP system generates a production task and sends the production task to the MES system (i.e., sends the production task to the MES system). The MES system (for the production task) performs production scheduling (to obtain the outbound task requirements of the production task) and sends the outbound task requirements to the WMS system. The WMS system performs inventory inquiry on goods required by the delivery task requirement, and delivers the inventory units (stock keeping unit, SKU) of the goods in the delivery task requirement and the quantity to the WCS system. After receiving the SKU library bits and the number required by the WMS system, the WCS system performs path planning on the SKU library bits, determines a grabbing sequence and sends the grabbing sequence to the library erecting system. The vertical warehouse system includes one or more stackers that run in a single aisle with SKU shelves on both sides. And the vertical warehouse system receives the SKU warehouse positions, the number and the grabbing sequence sent by the WCS system, schedules the stacker to grab the SKUs to be placed on the warehouse-out conveyor belt, and schedules the stacker to put the SKUs needing to be warehoused on the conveyor belt back to a specific position (namely, a certain position in a goods shelf) to finish one warehouse-out operation. The staff stands between the picking station and the conveyor belt and takes out a corresponding number of goods from SKUs on the conveyor belt as required. It will be appreciated that each SKU required for an out-of-stock task needs to be grabbed (out-of-stock) and put back (in-stock) once. it can be understood that the above systems may be deployed in the same device or in different devices, and the embodiments of the present application are not limited to the deployment manner of the above systems.

In summary, in the logistics business at present, for the same cargo delivery task requirement, the grabbing task sets formed by the WCS system based on the cargo delivery task requirement are different, and paths formed by SKUs required by scheduling the stacker to grab the cargo delivery task requirement are different, so that the working efficiency of the stacker is different. How to improve the working efficiency of the stacker without changing the warehouse hardware facilities is a problem to be solved.

In view of the above, embodiments of the present application provide a method, an apparatus, and a readable storage medium for scheduling a stacker, which can reduce the empty load moving time of the stacker from the perspective of minimizing the empty load moving distance of the stacker, thereby improving the working efficiency of the stacker. The warehousing system in the embodiment of the present application may be a system integrating functions of one or more of the WMS system, the WCS system, and the vertical warehouse system, or may be any one of the WMS system, the WCS system, and the vertical warehouse system, and for convenience of description, the warehousing system will be described below as an example of an execution body of stacker scheduling, and will not be described in detail.

Referring to fig. 2, fig. 2 is a flow chart of a stacker scheduling method according to an embodiment of the present application, where the method includes, but is not limited to, the following steps:

step S101: according to the cargo delivery task demand, N first stock quantity units SKUs required by the cargo delivery task demand and positions of the N first SKUs in a goods shelf are determined, wherein N is an integer greater than 1.

In some possible implementations, the warehousing system may receive a cargo shipment task requirement, which may include, for example, SKU numbers of M cargo that need to be shipped. The warehousing system can determine N first SKUs to which the M goods belong according to SKU numbers of the M goods. Wherein, a SKU may contain one or more items, and SKUs of the one or more items contained in the same SKU are numbered identically. The warehousing system may further obtain the positions of the N first SKUs in the shelf according to the SKU numbers of the N first SKUs. Wherein a first SKU corresponds to a SKU number, a SKU number corresponds to a position in the shelf, N is an integer greater than 1, and M is an integer greater than or equal to N. In the logistics business scene, the WMS system can receive the cargo delivery task requirement sent by the MES system, determine N first SKUs required by the cargo delivery task requirement and positions of the N first SKUs in the goods shelf, and send the number N of the first SKUs and the positions of the N first SKUs in the goods shelf to the WCS system.

Step S102: the capacity P of the conveyor and the position in the shelf of the P second SKUs currently parked on the conveyor are obtained, P being an integer greater than 1.

In some possible implementations, the warehousing system may acquire a capacity P of the conveyor belt, which represents that the conveyor belt can accommodate up to P SKUs. It will be appreciated that because the warehousing and ex-warehouse operations performed by the stacker are in pairs, the stacker will place the SKU at the 1 st position of the conveyor (i.e., the end of the conveyor) back on the shelf, and will remove the SKU that needs to be ex-warehouse from the shelf to place it at the P-th position of the conveyor (i.e., the beginning of the conveyor), the last P SKUs in the last ex-warehouse task will remain on the conveyor when this ex-warehouse task is performed. For example, the order of the 4 first SKUs captured by the last shipment task is { a, B, C, D }, the capacity of the conveyor is 2, then the first second SKU on the conveyor is C and the second SKU is D. The warehousing system can acquire the SKU numbers of the P second SKUs currently parked on the conveyor belt, and the positions of the P second SKUs in the goods shelf are acquired according to the numbers of the P second SKUs. Wherein P is an integer greater than 1. In the logistics business scenario, the WMS system may obtain the capacity P of the conveyor belt and the positions of the P second SKUs currently parked on the conveyor belt in the shelf, and send the capacity P of the conveyor belt and the positions of the P second SKUs in the shelf to the WCS system.

Step S103: and obtaining P grabbing paths with capacity constraint based on the N first SKUs, the number N of the first SKUs, the positions of the N first SKUs in the goods shelf, the capacity P of the conveyor belt and the positions of the P second SKUs in the goods shelf, wherein the corresponding moving distance of the grabbing paths with capacity constraint is calculated based on the Chebyshev distance.

In some possible implementations, the warehousing system may calculate the distance between each SKU based on the positions of the N first SKUs in the shelf and the positions of the P second SKUs in the shelf, and perform path planning on the N first SKUs. The movement distance may be calculated based on chebyshev distance or manhattan distance, for example. When the stacker can move back and forth and up and down simultaneously, the moving distance can be calculated based on the chebyshev distance. When the stacker cannot move back and forth, up and down at the same time (cannot move up and down when moving back and forth, or cannot move left and right when moving up and down), the moving distance can be calculated based on the manhattan distance. The embodiment of the present application will be described by taking chebyshev distance calculation (calculation of the maximum value of the forward-backward movement distance and the upward-downward movement distance) as an example. It will be appreciated that the empty path of travel of the stacker in the rack to perform a job for delivery may be equivalent to P paths beginning with P second SKUs on the conveyor. The empty load movement is the movement of the stacker when the SKU is not loaded, i.e., the movement of the stacker arm after the warehouse-in operation and before the warehouse-out operation. The warehouse system may obtain a maximum length P of the path based on the number N of the first SKUs and the capacity of the conveyor belt, and the maximum length of the path may be, for example, a ratio of N to P rounded up and then added by 1. The warehouse system can plan the paths of the N first SKUs based on the N first SKUs, the number N of the first SKUs, the distance among the SKUs, the capacity P of the conveyor belt, the maximum length of the paths and the like, and all path groups corresponding to the empty load moving tracks of the stacker executing the warehouse-out task in the goods shelf are obtained. Wherein one path group includes P paths with capacity constraints. It can be understood that different path groups correspond to different scheduling schemes (grabbing sequences), and the empty load moving distances of the stackers corresponding to the different scheduling schemes are also different. For example, referring to fig. 3, fig. 3 is a schematic diagram comparing two different scheduling schemes of a stacker according to the embodiment of the present application, as shown in fig. 3, the warehousing sequence of scheme 1 is { C, F, D, E, L, G, a }, and the total distance of empty load movements of the corresponding stacker is 6 (2+2+1+1). The warehouse-in sequence of the scheme 2 is { C, F, D, L, G, E, A }, and the total distance of empty load movement of the corresponding stacker is 9 (2+1+3+3). It can be seen from the schemes 1 and 2 that the gripping order is different and the empty moving distance of the stacker is different for the same SKU set. Therefore, the warehousing system can obtain the empty moving distances corresponding to all the path groups, and screen out the path group with the smallest empty moving distance, so that the empty moving distance of the stacker is the smallest in all the scheduling schemes when the warehousing system schedules the stacker to execute the warehouse-out task based on the grabbing path of the path group. In the logistics business scene, the WCS system can receive the number N of the first SKUs sent by the WMS system, the positions of the N first SKUs in the goods shelf, the capacity P of the conveyor belt and the positions of the P second SKUs in the goods shelf, and then perform path planning on the N first SKUs to obtain P grabbing paths with capacity constraint.

To further illustrate that the empty path of travel of the stacker in the rack for performing a job for delivery may be equivalent to P paths beginning with P second SKUs on the conveyor, the following description will be given by way of example in FIG. 4. For example, referring to fig. 4, fig. 4 is an equivalent schematic diagram of a movement track and a path of a stacker according to an embodiment of the present application. As shown in FIG. 4, 401 is in an initial state, 3 SKUs on the conveyor belt are { C, F, D }. Beginning at 402, the stacker grabs the 7 SKUs in the order { B, I, G, a, J, K, E }. The stacker first returns the 1 st SKU (i.e., C in the figure) from the conveyor to the pallet and then moves the B on the gripping pallet, at which time the conveyor has moved F to the 1 st position and D to the 2 nd position, so the stacker can place B in the 3 rd position of the conveyor. And (3) warehousing the C by the stacker, and discharging the B from the warehouse, so that one-time warehouse discharging operation is completed, and the empty load moving track of the stacker is C to B. The first position in the conveyor is F, the stacker first returns F from the conveyor to the pallet and then moves I on the gripping pallet, at which point the conveyor has moved D to position 1 and B to position 2, so the stacker places I in position 3 of the conveyor. And (3) warehousing the F by the stacker, and warehousing the I, wherein the operation of warehousing the I once is completed, and the empty load moving track of the stacker is F to I. Similarly, the empty moving track of the stacker in 404 is D to G, the empty moving track of the stacker in 405 is B to a, the empty moving track of the stacker in 406 is I to J, the empty moving track of the stacker in 407 is G to K, and the empty moving track of the stacker in 408 is a to E. By combining the 7 empty movement tracks of { C.fwdarw.B, F.fwdarw.I, D.fwdarw.G, B.fwdarw.A, I.fwdarw.J, G.fwdarw.K, A.fwdarw.E }, three paths shown in FIG. 4 can be obtained. Path 1 is a path { C→B→A→E } starting with the 1 st SKU on the conveyor belt in the initial state, path 2 is a path { F→I→J } starting with the 2 nd SKU on the conveyor belt in the initial state, and path 3 is a path { D→G→K } starting with the 3 rd SKU on the conveyor belt in the initial state.

In some possible implementations, the warehousing system may correspond the stacker scheduling scenario to the vehicle path planning problem (CAPACITATED VEH IC LE rout ing prob lem, CVPR) scenario, calculate values of parameters of the path algorithm in the stacker scheduling scenario, and obtain P paths with capacity constraints based on the path algorithm. By way of example, the path algorithm may be an algorithm (HSG-CVPR) that uses a hybrid genetic search (hybr ID GENET IC SEARCH, HGS) to address capacity-limited CVPR. The embodiment of the application is described by taking an HSG-CVPR algorithm as an example. In CVRP, the task of transporting goods from a warehouse to other pre-designated customer points is required to be undertaken by a fleet, so the decision object of the HSG-CVPR algorithm is the path of travel of the vehicles, each with different costs of travel on different paths, with the final objective of minimizing the overall cost of the fleet to accomplish this task. The empty load movement of the stacker among the shelves can be regarded as a running path of the vehicle by analogy with the scheduling scene of the stacker, and the final aim is to minimize the empty load movement distance of the stacker which completes the delivery task, but the empty load movement of the stacker among the shelves is not continuous like the running path of a vehicle, and consists of P paths together, wherein P is the capacity of a conveying belt. Therefore, as long as the corresponding relation between the definition in CVRP scenes and the definition in the stacker scheduling scenes is found, the values of the input parameters of the HSG-CVPR algorithm in the stacker scheduling scenes are calculated, and the values are input into the HSG-CVPR algorithm, P grabbing paths with capacity constraint can be obtained, and the empty moving distance of the stacker corresponding to the grabbing paths with capacity constraint is the smallest in all scheduling schemes.

The input parameters of the HSG-CVPR algorithm include: the number of customer points, the set of customer points, the number of vehicles, the distance between each customer point defined, the capacity demand of each customer point, the maximum payload of vehicles. The number of client points may correspond to the number of SKUs to be delivered in the stacker scheduling scenario, that is, N, the set of client points may correspond to the N first SKUs, and the number of vehicles may correspond to the capacity P of the conveyor belt. For the distance between each customer point, the distance between the N SKUs may correspond to the distance between the N SKUs, and because the embodiment of the present application does not consider the distance of movement of the stacker from the conveyor belt to the shelf, the warehouse system sets the distance between the N first SKUs to the conveyor belt to 0 and the distance between the P second SKUs in the conveyor belt to the shelf to 0. The capacity demand for each customer point may correspond to the capacity of SKUs in the stacker scheduling scenario, and the maximum load capacity of vehicles may correspond to the path capacity in the stacker scheduling scenario. It will be appreciated that SKU capacity and path capacity are not practical in a stacker scheduling scenario, but only to ensure that P paths output by the HSG-CVPR algorithm can be used in a stacker scheduling scenario. For example, 3 SKUs on the conveyor belt are { C, F, D }, and SKUs to be delivered are { a, B, E, G, I } if the lengths of the 3 paths outputted by the HSG-CVPR algorithm are 4, 2, respectively, { c→b→a→e }, { f→i }, { d→g }, stacker warehouse-in C, warehouse-out B, warehouse-in F, warehouse-out I, warehouse-in D, warehouse-out G, warehouse-in B, warehouse-out a, and 3 SKUs on the conveyor belt are { I, G, a }, and the next warehouse-in I has no path to indicate which SKU is delivered next. Thus, paths that can be applied in a stacker scheduling scenario need to satisfy the following conditions: the difference in length between each path is not more than 1, and the path corresponding to the second SKU with the preceding position index is greater than or equal to the path corresponding to the second SKU with the following position index. The warehousing system may determine the capacity K of each of the P second SKUs and the capacities M, K, and M of each of the N first SKUs based on the number N of first SKUs and the capacity P of the conveyor belt. Illustratively, the warehousing system may set the capacity of each of the N first SKUs to 1, set the capacity of the second SKU having a position index greater than or equal to (1+ (N-1)% P) to 2, and set the capacity of the second SKU having a position index less than (1+ (N-1)% P) to 1. The warehousing system can determine an integer obtained by upwardly rounding the ratio of N to P and adding 1 as a value of the capacity Q of the changed path, wherein the sum of the capacities of SKUs of all grabbing paths in the P grabbing paths with capacity constraint is smaller than or equal to Q. The warehousing system inputs the obtained number of the client points, the client point set, the number of vehicles, the distance between each client point, the capacity demand of each client point and the numerical value corresponding to the maximum loading capacity of the vehicles in a stacker scheduling scene into an HSG-CVPR algorithm, obtains P grabbing paths with capacity constraint based on the HSG-CVPR algorithm, and when the warehousing system schedules the stacker to execute a warehouse-out task based on the P grabbing paths with capacity constraint, the empty load moving distance of the stacker is minimum in all scheduling schemes.

In order to further illustrate the correspondence between the stacker scheduling scenario and CVRP scenario in the embodiment of the present application, the following description will take fig. 4 as an example. As shown in FIG. 4, the stacker would need to grasp from the shelves a set of SKUs (the first SKU described above) of { A, B, E, G, I, J, K }, the conveyor would buffer 3 SKUs (i.e., the capacity of the conveyor is 3), and a set of SKUs on the conveyor (the second SKU described above) of { C, F, D }. As shown in table 1 below, table 1 shows the correspondence of definitions in CVRP scenarios with definitions in stacker scheduling scenarios, and the values of the input parameters of the HSG-CVPR algorithm in stacker scheduling scenarios. The number of client points in CVRP scenes can be corresponding to the number of SKUs needing to be delivered in a stacker scheduling scene, the number N is 7, the set of client points can be corresponding to the set of SKUs needing to be delivered, namely { a, B, E, G, I, J, K }, and the number of vehicles can be corresponding to the number of SKUs that can be buffered by a conveyor belt, namely the capacity P of the conveyor belt is 3. The number of paths is the same as the number of vehicles. The vehicle travel path in the CVRP scenario may correspond to the path that the stacker takes to place a SKU in the conveyor back into the shelf and grasp the next SKU. The maximum load of the vehicles in CVRP scenes corresponds to the path capacity Q in the stacker scheduling scenes, and the calculation formula is adoptedThe path capacity Q can be calculated to be 4. The customer point capacity requirement in CVRP scenario corresponds to the SKU capacity in the stacker scheduling scenario, a value of (1+ (N-1)% P) is calculated to be 1, the position index of c is 0,F, the position index of D is 2, so the capacities of F and D are 2, and the capacity of c is 1. The warehouse system takes the values as input parameters of the HSG-CVPR algorithm, and 3 paths can be obtained based on the HSG-CVPR algorithm, wherein the paths correspond to path 1, path 2 and path 3 in FIG. 4, namely, C, B, A, E, F, I, J, D, G and K.

TABLE 1

Step S104: and based on the P grabbing paths with capacity constraint, acquiring the grabbing sequence of each first SKU in the N first SKUs, and sequentially placing the N first SKUs from the goods shelf to the P position in the conveyor belt by a scheduling stacker according to the grabbing sequence of each first SKU.

In some possible implementations, the warehousing system may determine the order of grabbing the first SKUs, where the (i+ (j-1) x P) th first SKU is the j-th first SKU in the capacity-constrained grabbing path corresponding to the i-th second SKU in the conveyor belt. Wherein, the value of i is 1,2, … P, if the capacity of the i second SKU is 1, i.e. the path length corresponding to the second SKU is Q, the value of n is 1,2, … (Q-1), if the capacity of the i second SKU is 2, i.e. the path length corresponding to the second SKU is (Q-1), the value of j is 1,2, … (Q-2). It will be appreciated that the capacity constrained fetch path includes a second SKU and at most (Q-1) of the first SKU's fetch order, with the second SKU's fetch order preceding the first SKU of the at most (Q-1) SKUs. That is, each of the grasping paths starts with a second SKU, and the capacity of each grasping path does not exceed the path capacity Q. Thus, a second SKU corresponds to a capacity-constrained grasping path. It will also be appreciated that since the SKU in the stacker is always the 1 st SKU in the conveyor belt, and the 1 st SKU in the conveyor belt can be determined based on SKUs from the previous P shipments, the shipments can be completed as long as the order of grabbing each of the N first SKUs that need to be shipments is obtained. For example, as shown in fig. 4, the 4 capacity-constrained grasping paths obtained by the warehouse system are c→b→a→e, f→i→j, d→g→k. So the warehousing system determines that in the grabbing sequence of each first SKU, the 1 st first SKU is the 1 st first SKU (B) in the grabbing paths (c→b→a→e) corresponding to the 1 st second SKU (C), the 2 nd first SKU is the 1 st first SKU (I) in the grabbing paths (f→i→j) corresponding to the 2 nd second SKU (F), the 3 rd first SKU is the 1 st first SKU (G) in the grabbing paths (d→g→k) corresponding to the 3 rd second SKU (D), the 4 th first SKU is the 2 nd first SKU (a) in the grabbing paths (c→b→a→e) corresponding to the 1 st second SKU (C), The 5 th first SKU is the 2 nd first SKU (J) in the grabbing path (f→i→j) corresponding to the 2 nd second SKU (F), the 6 th first SKU is the 2 nd first SKU (K) in the grabbing path (d→g→k) corresponding to the 3 rd second SKU (D), and the 7 th first SKU is the 3 rd first SKU (E) in the grabbing path (c→b→a→e) corresponding to the 1 st second SKU (C). Therefore, the order of grabbing each first SKU obtained by the warehousing system is { B, I, G, a, J, K, E }. It can be appreciated that the warehousing system may also obtain the warehousing sequences of the P second SKUs and the N first SKUs according to the grasping sequence of the respective first SKUs. For example, as shown in FIG. 4 above, the order in which the SKUs obtained by the warehouse system are placed back onto the shelves (warehouse entry) from the conveyor is { C, F, D, B, I, G, A, J, K, E }. After the warehousing system obtains the grabbing sequence of each first SKU in the N first SKUs, the stacker can be scheduled to put the first SKU in the conveyor belt back to the goods shelf from the conveyor belt, the ith first SKU is put into the P position in the conveyor belt from the goods shelf according to the grabbing sequence of each first SKU, the operation is repeated for N times until all the N first SKUs are taken out of the warehouse, and the task of taking out the warehouse is completed, wherein the value of i is 1,2 and … N. For example, as shown in fig. 4, according to the grabbing sequence of each first SKU, the warehouse system schedules the stacker to sequentially warehouse in C, warehouse out B, warehouse in F, warehouse out I, warehouse in D, warehouse out G, warehouse in B, warehouse out a, warehouse in I, warehouse out J, warehouse in G, warehouse out K, warehouse in a, warehouse out E, and completes the warehouse-out task, and finally the 3 SKUs J, K, E remain on the conveyor belt.

In the logistics business scenario, the function of the warehouse system in step S104 may be jointly implemented by the WCS system and the library erecting system. After the WCS system obtains P grabbing paths with capacity constraint, the grabbing sequences of the N first SKUs may be obtained according to the P grabbing paths with capacity constraint, and the positions and grabbing sequences of the N first SKUs may be sent to the vertical warehouse system. After the vertical warehouse system receives the positions and the grabbing sequences of the N first SKUs sent by the WCS system, the stacker is scheduled to grab the first SKUs according to the grabbing sequences and place the first SKUs at the P-th position of the conveyor belt, and the 1 st SKU on the conveyor belt is placed back to the goods shelf.

According to the embodiment of the application, CVPR is applied to a stacker scheduling scene, the value of the input parameter of the HSG-CVPR algorithm in the stacker scheduling scene is calculated by a storage system, and P grabbing paths with capacity constraint are obtained, wherein the grabbing paths are shortest paths in all paths generated by the fact that the stacker grabs N first SKUs. The warehousing system obtains the grabbing sequence of each first SKU according to the P grabbing paths with capacity constraint, so that the scheduling scheme of the stacker can be calculated once without calculation for each warehouse-out and warehouse-in, and the calculation delay problem under multitasking (warehouse-in and warehouse-out tasks) is reduced. The warehouse system dispatches the stacker to finish the warehouse-out task according to the grabbing sequence of each first SKU, so that the idle running movement distance of the stacker is minimized, and the working efficiency of the stacker is improved. And when the warehouse system dispatches the stacker to put the SKU back to the warehouse from the conveyor belt, the stacker will put the SKU back to the original position, so that the change of the SKU position is avoided, and the frequent update of the warehouse system to the SKU position information and the quantity information is avoided.

In order to better illustrate that the stacker scheduling method provided by the embodiment of the present application can minimize the idle movement distance of the stacker, a brief description will be given below by way of an example.

For example, assuming a capacity of 4 for a conveyor, a number of SKUs to be taken out of the conveyor is 9, a set of SKUs to be taken out of the conveyor is { D, T, H, J, M, L, S, I, N }, and a set of SKUs on the conveyor is { C, K, F, O }. If the warehouse system directly dispatches the stacker to grasp SKUs according to SKU sequences required by warehouse-out task demands, the empty load moving distance of the stacker is usually quite large. Referring to fig. 5, fig. 5 is a schematic diagram of a stacker scheduling scheme according to an embodiment of the present application. As shown in FIG. 5, the warehousing system sequentially warehouses the SKUs in the order { D, T, H, J, M, L, S, I, N }. It can be seen that, calculated according to chebyshev distance, the empty moving distance of the path 1 stacker is 5, the empty moving distance of the path 2 stacker is 7, the empty moving distance of the path 3 stacker is 6, the empty moving distance of the path 4 stacker is 2, and the total empty moving distance of the stacker is 20 (5+7+6+2=20).

Referring to fig. 6, fig. 6 is a schematic diagram of a stacker scheduling scheme based on the HSG-CVPR algorithm according to an embodiment of the present application. The warehousing system firstly calculates the value of the input parameter of the HSG-CVPR algorithm in the scheduling scene of the stacker. From the capacity 4 of the conveyor belt, the number of vehicles in the input parameters of the HSG-CVPR algorithm can be obtained as 4, and the number of paths as 4. According to the required number of SKUs 9 and the capacity 4 of the conveyor belt, the maximum load of the vehicle in the input parameters of the HSG-CVPR algorithm can be calculated and obtained as followsAccording to the number of SKUs 9 required to be delivered and the capacity 4 of the conveyor belt, K, F, O of which the position index is greater than or equal to 1 (1+ (9-1)% 4=1) can be calculated, and the capacities of the remaining SKUs are 1. The warehouse system takes the values as input parameters of the HSG-CVPR algorithm, and 4 paths can be obtained based on the HSG-CVPR algorithm: c, H, N, M, K, J, I, F, L, D, O, T and S. Based on these 4 paths, the order of grabbing SKUs to be delivered is { H, J, L, T, N, I, D, S, M }, and the order of retrieving SKUs to be delivered from the conveyor is { C, K, F, O, H, J, L, T, N, I, D, S, M }. As shown in fig. 6, the distance of travel of the path 1 stacker is 3, the distance of travel of the path 2 stacker is 2, the distance of travel of the path 3 stacker is 3, the distance of travel of the path 4 stacker is 2, and the total distance of travel of the stacker is 10 (3+2+3+2=10) calculated by chebyshev distance. It can be seen that the stacker scheduling scheme shown in fig. 6 produces a smaller null shift distance (10) than the stacker scheduling scheme shown in fig. 4 produces (20), and that the stacker scheduling scheme shown in fig. 6 produces the null shift distance that is the smallest of all scheduling schemes.

The foregoing details of the method according to the embodiments of the present application and the apparatus according to the embodiments of the present application are provided below.

Referring to fig. 7, fig. 7 is a schematic structural diagram of a stacker scheduling apparatus according to an embodiment of the present application, where the stacker scheduling apparatus includes:

an input module 701, configured to receive a cargo shipment task requirement;

A determining module 702, configured to determine N first stock units SKUs and positions of the N first SKUs in a shelf required for the cargo delivery task demand received by the input module 701, where N is an integer greater than 1;

An acquisition module 703 for acquiring the capacity P of the conveyor belt and the positions in the shelf of the P second SKUs currently parked on the conveyor belt, P being an integer greater than 1;

The obtaining module 703 is further configured to obtain P capacity-constrained grabbing paths based on the N first SKUs, the number N of the first SKUs, positions of the N first SKUs in the shelf, the capacity P of the conveyor belt, and positions of the P second SKUs in the shelf, where a movement distance corresponding to the capacity-constrained grabbing paths is calculated based on chebyshev distances;

the acquiring module 703 is further configured to acquire a grabbing order of each of the N first SKUs based on the P grabbing paths with capacity constraint;

and a scheduling module 704, configured to schedule the stacker to sequentially place the N first SKUs from the shelf to the P-th position in the conveyor belt according to the grabbing order of the first SKUs.

In a possible implementation manner, the determining module 702 is further configured to determine, based on the number N of the first SKUs and the capacity P of the conveyor belt, a capacity K of each of the P second SKUs and a capacity M of each of the N first SKUs, where K and M are positive integers; the determining module 702 is further configured to determine a path capacity Q based on the number N of the first SKUs and the capacity P of the conveyor belt, where Q is an integer less than N and greater than 1; the obtaining module 703 is further configured to obtain P grabbing paths with capacity constraint based on the path algorithm by using the number N of the first SKUs, the positions of the N first SKUs in the shelf, the capacity P of the conveyor belt, the positions of the P second SKUs in the shelf, the capacity K of each second SKU in the P second SKUs, the capacity M of each first SKU in the N first SKUs, and the path capacity Q as input parameters of the path algorithm with capacity constraint.

In a possible implementation manner, the determining module 702 is further configured to: setting the capacity of a second SKU with a position index greater than or equal to L to 2, and setting the capacity of a second SKU with the position index less than L to 1, wherein L is obtained from N and P; the capacity of each of the N first SKUs is set to 1.

In a possible implementation manner, the determining module 702 is further configured to: and determining an integer obtained by upwardly rounding the ratio of N to P and adding 1 as the value of the path capacity Q, wherein the sum of the capacities of the SKUs of each grabbing path in the P grabbing paths with capacity constraint is smaller than or equal to Q.

In a possible implementation manner, the determining module 702 is further configured to: determining the j-th first SKU in the grabbing path i as the (i+ (j-1) P) -th first SKU in the grabbing sequence of the N first SKUs to obtain the grabbing sequence of each first SKU in the N first SKUs, where the grabbing path i is a grabbing path with capacity constraint corresponding to the i-th second SKU in the conveyor belt; wherein i has a value of 1,2, … P, if the i second SKU has a capacity of 1, j has a value of 1,2, … (Q-1), and if the i second SKU has a capacity of 2, j has a value of 1,2, … (Q-2). A capacity constrained grabbing path comprises a second SKU and at most (Q-1) grabbing orders of the first SKUs, wherein the grabbing orders of the second SKU are before the grabbing orders of the first SKU in the at most (Q-1), and a second SKU corresponds to the capacity constrained grabbing path.

In a possible implementation manner, the scheduling module 704 is further configured to: and (3) scheduling the stacker to replace the first SKU in the conveyor belt from the conveyor belt to the goods shelf, and placing the ith first SKU from the goods shelf to the P-th position in the conveyor belt according to the grabbing sequence of the first SKUs, wherein the value of i is 1,2 and … N.

In a specific implementation, the stacker scheduling apparatus shown in fig. 7 may execute, through each module built in the stacker scheduling apparatus, an implementation manner executed by the warehouse system in the embodiment shown in fig. 2, and specifically may refer to an implementation manner provided in each step of the embodiment. The advantages (or benefits) provided by the implementation manner provided in each step of each embodiment described above can also be achieved, and will not be described in detail herein.

Referring to fig. 8, fig. 8 is a schematic structural diagram of a computer device according to an embodiment of the application. The computer device may be a server in which the warehousing system in the above embodiment is deployed, and may be configured to implement the steps of the stacker scheduling method performed by the warehousing system described in the above embodiment. The computer device may include: a processor 801, memory 802, a network interface 803, and a bus system 804.

Memory 802 includes, but is not limited to, RAM, ROM, EPROM or CD-ROM, which memory 802 is used to store related instructions and data. Memory 802 stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof:

Operation instructions: including various operational instructions for carrying out various operations.

Operating system: including various system programs for implementing various basic services and handling hardware-based tasks.

Only one memory is shown in fig. 8, but a plurality of memories may be provided as needed.

The processor 801 may be a controller, CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules and circuits described in connection with the disclosure of embodiments of the application. The process of analyzing the first command data as referred to in the embodiment. The processor 801 may also be a combination of computing functions, e.g., including one or more microprocessor combinations, a combination of a DSP and a microprocessor, and the like.

The network interface 803 may provide network communication functionality and may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). In an embodiment of the present application, the network interface 803 is used to perform the process of receiving the cargo shipment task requirements involved in the embodiment shown in fig. 2.

In a particular application, components of the computer device are coupled together by a bus system 804, where the bus system 804 may include a power bus, a control bus, a status signal bus, and the like, in addition to a data bus. But for clarity of illustration the various buses are labeled as bus system 804 in fig. 8. For ease of illustration, fig. 8 is only schematically drawn.

It should be noted that, in practical applications, the processor in the embodiment of the present application may be an integrated circuit chip, which has signal processing capability. In implementation, the steps of the above method embodiments may be implemented by integrated logic circuits of hardware in a processor or instructions in software form. The Processor may be a general purpose Processor, a digital signal Processor (DIGITAL SIGNAL Processor, DSP), an Application SPECIFIC INTEGRATED Circuit (ASIC), an off-the-shelf programmable gate array (field programmable GATE ARRAY, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed.

It will be appreciated that the memory in embodiments of the application may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an erasable programmable ROM (erasable PROM), an electrically erasable programmable EPROM (EEPROM), or a flash memory. The volatile memory may be random access memory (random access memory, RAM) which acts as external cache memory. By way of example, and not limitation, many forms of RAM are available, such as static random access memory (STATIC RAM, SRAM), dynamic random access memory (DYNAMIC RAM, DRAM), synchronous Dynamic Random Access Memory (SDRAM), double data rate synchronous dynamic random access memory (double DATA RATE SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (ENHANCED SDRAM, ESDRAM), synchronous link dynamic random access memory (SYNCHLINK DRAM, SLDRAM), and direct memory bus random access memory (direct rambus RAM, DR RAM). It should be noted that the memory described by embodiments of the present application is intended to comprise, without being limited to, these and any other suitable types of memory.

It can be understood that the computer device described in the embodiment of the present application may perform the description of the method for scheduling a stacker in the embodiment shown in fig. 2, or may perform the description of the device for scheduling a stacker in the embodiment shown in fig. 7, which is not repeated herein. In addition, the description of the beneficial effects of the same method is omitted.

The embodiment of the present application further provides a computer readable storage medium, where the computer readable storage medium is configured to store a computer program, where the computer program when executed on a computer causes the computer to perform the description of the method for scheduling a stacker in the embodiment corresponding to fig. 2, and also perform the description of the apparatus for scheduling a stacker in the embodiment corresponding to fig. 7, which is not described herein again. In addition, the description of the beneficial effects of the same method is omitted.

Embodiments of the present application also provide a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device may execute the description of the stacker scheduling method in the embodiment shown in fig. 2, which is not described herein. In addition, the description of the beneficial effects of the same method is omitted.

The term "comprising" and any variations thereof in the description of embodiments of the application and in the claims and drawings is intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or modules but may, in the alternative, include other steps or modules not listed or inherent to such process, method, apparatus, article, or device.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The method and related apparatus provided in the embodiments of the present application are described with reference to the flowchart and/or schematic structural diagrams of the method provided in the embodiments of the present application, and each flow and/or block of the flowchart and/or schematic structural diagrams of the method may be implemented by computer program instructions, and combinations of flows and/or blocks in the flowchart and/or block diagrams. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or structural diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or structures.

While the application has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims (10)

1. A stacker scheduling method, comprising:

According to the cargo delivery task demand, determining N first stock units SKUs required by the cargo delivery task demand and positions of the N first SKUs in a goods shelf, wherein N is an integer greater than 1;

Acquiring the capacity P of a conveyor belt and the positions of P second SKUs currently parked on the conveyor belt in a goods shelf, wherein P is an integer greater than 1;

Obtaining P grabbing paths with capacity constraint based on the N first SKUs, the number N of the first SKUs, the positions of the N first SKUs in a goods shelf, the capacity P of the conveyor belt and the positions of the P second SKUs in the goods shelf, wherein the moving distance corresponding to the grabbing paths with capacity constraint is calculated based on Chebyshev distance;

And based on the P grabbing paths with capacity constraint, acquiring grabbing orders of all the N first SKUs, and sequentially placing the N first SKUs from the goods shelf to a P position in the conveyor belt by a scheduling stacker according to the grabbing orders of all the first SKUs.

2. The method of claim 1, wherein the obtaining P capacity-constrained grasp paths based on the N first SKUs, the number N of first SKUs, the N first SKUs' positions in the shelf, the conveyor capacity P, and the P second SKUs on the shelf comprises:

Determining a capacity K of each of the P second SKUs and a capacity M, K and M of each of the N first SKUs based on the number N of first SKUs and the capacity P of the conveyor belt, wherein K and M are positive integers;

Determining a path capacity Q based on the number N of first SKUs and the capacity P of the conveyor belt, Q being an integer less than N and greater than 1;

Taking the number N of the first SKUs, the positions of the N first SKUs in the shelf, the capacity P of the conveyor belt, the positions of the P second SKUs in the shelf, the capacity K of each second SKU in the P second SKUs, the capacity M of each first SKU in the N first SKUs and the path capacity Q as input parameters of a path algorithm for calculating a grabbing path with capacity constraint, and obtaining P grabbing paths with capacity constraint based on the path algorithm and the input parameters.

3. The method of claim 2, wherein the determining the capacity K of each of the P second SKUs and the capacity M of each of the N first SKUs based on the number N of first SKUs and the capacity P of the conveyor belt comprises:

setting the capacity of a second SKU with a position index greater than or equal to L to 2, and setting the capacity of a second SKU with a position index less than L to 1, wherein L is obtained from N and P;

the capacity of each of the N first SKUs is set to 1.

4. The method of claim 3, wherein said determining a path capacity Q based on the number N of said first SKUs and the capacity P of said conveyor belt comprises:

And determining an integer obtained by upwardly rounding the ratio of N to P and adding 1 as the value of the path capacity Q, wherein the sum of the capacities of the SKUs of each grabbing path in the P grabbing paths with capacity constraint is smaller than or equal to Q.

5. The method of claim 4, wherein the obtaining the order of grabbing each of the N first SKUs based on the P capacity-constrained grabbing paths comprises:

Determining the j-th first SKU in a grabbing path i as the (i+ (j-1) P) -th first SKU in the grabbing sequence of the N first SKUs to obtain the grabbing sequence of each first SKU in the N first SKUs, wherein the grabbing path i is a grabbing path with capacity constraint corresponding to the i-th second SKU in the conveyor belt;

wherein i has a value of 1,2, … P, 1,2, … (Q-1) if the i second SKU has a capacity of 1, j, and 1,2, … (Q-2) if the i second SKU has a capacity of 2, j;

A capacity constrained grabbing path comprises a second SKU and at most (Q-1) grabbing orders of the first SKUs, wherein the grabbing orders of the second SKU are in front of the at most (Q-1) first SKUs, and a second SKU corresponds to the capacity constrained grabbing path.

6. The method of any of claims 1-5, wherein the scheduling stacker sequentially places the N first SKUs from the shelf into a P-th position in the conveyor belt in the order of grabbing the respective first SKUs, comprising:

And dispatching the stacker to put the first SKU in the conveyor belt back to the goods shelf from the conveyor belt, and putting the ith first SKU in the P position in the conveyor belt from the goods shelf according to the grabbing sequence of each first SKU, wherein the value of i is 1,2 and … N.

7. A stacker scheduling apparatus, the apparatus comprising:

the input module is used for receiving the cargo delivery task demand;

The determining module is used for determining N first stock quantity units (SKUs) and positions of the N first SKUs in the goods shelf, wherein the positions are required by the goods delivery task demands and received by the input module, and N is an integer greater than 1;

The acquisition module is used for acquiring the capacity P of the conveyor belt and the positions of P second SKUs currently parked on the conveyor belt in a goods shelf, wherein P is an integer greater than 1;

The acquisition module is further used for acquiring P grabbing paths with capacity constraint based on the N first SKUs, the number N of the first SKUs, the positions of the N first SKUs in the goods shelf, the capacity P of the conveyor belt and the positions of the P second SKUs in the goods shelf, and the movement distance corresponding to the grabbing paths with capacity constraint is calculated based on Chebyshev distance;

The acquisition module is further used for acquiring the grabbing sequence of each first SKU in the N first SKUs based on the P grabbing paths with capacity constraint;

And the scheduling module is used for scheduling the stacker to sequentially put the N first SKUs from the goods shelf to the P position in the conveyor belt according to the grabbing sequence of each first SKU.

8. The apparatus of claim 7, wherein the determination module is further to:

Determining a capacity K of each of the P second SKUs and a capacity M, K and M of each of the N first SKUs based on the number N of first SKUs and the capacity P of the conveyor belt, wherein K and M are positive integers;

Determining a path capacity Q based on the number N of first SKUs and the capacity P of the conveyor belt, Q being an integer less than N and greater than 1;

The acquisition module is further configured to use the number N of the first SKUs, the positions of the N first SKUs in the shelf, the capacity P of the conveyor belt, the positions of the P second SKUs in the shelf, the capacity K of each second SKU in the P second SKUs determined by the determination module, the capacity M of each first SKU in the N first SKUs determined by the determination module, and the path capacity Q determined by the determination module as input parameters of a path algorithm with capacity constraint, and obtain P grabbing paths with capacity constraint based on the path algorithm.

9. A computer device, comprising: a processor and a memory;

A processor is connected to a memory, wherein the memory is for storing a computer program, the processor being for invoking the computer program to cause a computer device to perform the method of any of claims 1-6.

10. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program, which is loaded and executed by a processor, to cause a computer device having the processor to perform the method according to any of claims 1-6.