A method and system for optimizing a picking operation of a dual-elevator shuttle vehicle warehouse system

Abstract

The application discloses a kind of double elevator shuttle car warehousing system's goods taking operation optimization method and system, method includes: obtaining the parameter of double elevator shuttle car warehousing system, parameter includes the parameter information of system, shuttle car information, elevator information and operation information;According to parameter information, construct goods taking operation optimization model for double elevator shuttle car warehousing system;Using goods taking operation optimization model, according to operation information, obtain the operation scheduling strategy of double elevator shuttle car warehousing system.The goods taking operation optimization method provided by the application reasonably arranges shuttle car and elevator to complete goods taking operation, optimizes operation sequence, considers the interaction between elevator and shuttle car, between elevator and elevator, compared with prior art, saves completion time, realizes high throughput capacity;The goods taking operation optimization system provided by the application can improve the response speed of supply chain, improve the picking operation efficiency of double elevator shuttle car warehousing system.

Description

Technical Field

[0001] This invention relates to the field of warehouse system operation planning and control, and in particular to a method and system for optimizing the picking operation of a dual-elevator shuttle warehouse system. Background Technology

[0002] With the rapid development of e-commerce, warehousing companies need to efficiently respond to customers' demands for multi-category, small-batch products. To meet these needs, an increasing number of warehousing companies are adopting shuttle warehousing systems. This system mainly consists of three parts: shuttles, elevators, and racking for storing goods. The shuttles handle horizontal transport of goods, while the elevators handle vertical transport. In such systems, elevator operation is often the bottleneck. In recent years, warehousing companies have developed dual-elevator shuttle warehousing systems. This new type of shuttle warehousing system significantly improves system throughput and is widely used in actual warehousing enterprises.

[0003] Traditional dual-elevator order picking scheduling has the following problems: (1) Traditional scheduling strategies are relatively simple and do not optimize the order of operations; (2) Traditional scheduling strategies do not consider the interaction between elevators and shuttles. Since shuttles and elevators move in parallel during the actual order picking process in the warehousing system, it is necessary to reduce the order of operations and shorten the waiting time of elevators for shuttles to improve system efficiency; (3) Traditional scheduling strategies do not consider the interaction between elevators. Since there are two elevators, avoiding congestion between them can improve system efficiency. Summary of the Invention

[0004] This invention aims to overcome the shortcomings of traditional work scheduling strategies, which are relatively simple in design, lack optimization of work sequence, and fail to consider the interaction between elevators and shuttle cars, and between elevators themselves. It provides a method and system for optimizing the picking operations of a dual-elevator shuttle car storage system.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for optimizing the picking operation of a dual-elevator shuttle warehouse system includes the following steps: S1: Obtaining parameters of the dual-elevator shuttle warehouse system, including system structure information, shuttle information, elevator information, and operation information related to picking operation scheduling; S2: Constructing a picking operation optimization model for the dual-elevator shuttle warehouse system based on the parameters; S3: Using the picking operation optimization model, obtaining the picking operation scheduling strategy of the shuttle warehouse system based on the operation information. The picking operation optimization method for a dual-elevator shuttle warehouse system provided by this invention rationally arranges shuttles and elevators to complete picking operations, optimizes the operation sequence, and considers the interactive influence between elevators and shuttles, and between elevators. Compared with existing technologies, it saves completion time and achieves high throughput capacity.

[0007] As a preferred embodiment of the present invention, the system structure information in S1 includes information on the number of shelf layers, information on the number of storage locations per layer, information on the spacing between adjacent layers, and information on the length and width of storage locations; the shuttle information includes shuttle speed information and information on the time it takes for the shuttle to pick up or release a piece of goods; the elevator information includes elevator speed information and information on the initial stopping floor position of the elevator; and the operation information includes information on the number of picking operations, information on the coordinates of picking operations, information on the time required for the shuttle to process the operation, and information on the time required for the elevator to reach the operation floor.

[0008] As a preferred embodiment of the present invention, the formula for calculating the time required for the shuttle car to handle operation i is as follows:

[0009]

[0010] The formula for calculating the time required for elevator 1 to reach the floor where task i is located is as follows:

[0011]

[0012] The formula for calculating the time required for elevator 2 to reach the floor where task i is located is as follows:

[0013]

[0014] Among them, X i D is the coordinate of the storage location where operation i is located. c It is the unit length of the storage space, v shuttle It's the shuttle speed, Z. i D is the coordinate of the layer where task i is located. h It is the unit floor height, v lift It refers to the elevator's operating speed.

[0015] As a preferred embodiment of the present invention, the picking operation optimization model is as follows:

[0016]

[0017] in, It is the time it takes for elevator 1 to unload the work and reach the exit in the k-th cycle. It is the time it takes for elevator 2 to unload its work and reach the exit in the kth cycle.

[0018] As a preferred embodiment of the present invention, the time for elevator 1 to unload work and reach the exit in the kth cycle. as follows:

[0019]

[0020] The time it takes for elevator 2 to unload work and reach the exit in the kth cycle as follows:

[0021]

[0022] Among them, u i It is the time when task i is released onto the elevator, u j It is the time when assignment j is released onto the elevator, d i This is the time required for elevator 1 to travel from the exit to the floor where work i is located. It is the time required for elevator 2 to travel from floor -1 to the floor where operation i is located.

[0023] As a preferred embodiment of the present invention, the constraints of the picking operation optimization model are as follows:

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030]

[0031]

[0032] Where, x ik It is a binary decision variable; it equals 1 when elevator 1 completes operation i in the k-th cycle, and equals 0 otherwise. ijk It is a binary decision variable; the value is 1 when elevator 2 completes task i first and then task j in the k-th cycle, otherwise it is 0. jlkThese are binary decision variables. The value is 1 when elevator 2 completes task j first, followed immediately by task l in the k-th cycle; otherwise, it is 0. R is the set of tasks, K is the set of cycles, and u... i It is the time when task i is released onto the elevator, u j It is the time when assignment j is released onto the elevator, d i This is the time required for elevator 1 to travel from the exit to the floor where work i is located. p is the time required for elevator 2 to travel from floor -1 to the floor where operation i is located. i M is the time required for the shuttle to process job i, and M is a very large number.

[0033] As a preferred embodiment of the present invention, the method further includes optimizing the order of goods retrieval by using a dynamic programming model, wherein the dynamic programming model is as follows:

[0034]

[0035]

[0036]

[0037]

[0038] Where F(s,e) represents the shortest completion time for completing e tasks in the first s stages, F(s-1,e′) represents the shortest completion time for completing e′ tasks in the first s-1 stages, and c(s,e′,e) represents the shortest completion time for completing ee tasks in the s-th stage. ′ +1 The time required to complete task e; This represents the travel time of elevator 1 in stage s. c (s,e′,e) represents the travel time of elevator 2 in stage s, and d e This is the time required for elevator 1 to travel from the exit to the floor where work e is located. e This indicates the time when task e is released onto the elevator. This is the time required for elevator 2 to travel from floor -1 to the floor where work e-1 is located. e-1 This indicates the time when task e-1 was released onto the elevator.

[0039] As a preferred embodiment of the present invention, it further includes using relative task completion time as a measurement index, wherein the relative task completion time is calculated as follows:

[0040]

[0041] Where M(P) represents the total completion time of the operation obtained from empirical decision-making, and M(C) is the total completion time of the operation obtained from the picking operation optimization model.

[0042] A picking operation optimization system for a dual-elevator shuttle warehouse system includes: a first acquisition module for parameters of the dual-elevator shuttle warehouse system, wherein the parameters include system structure information, shuttle information, elevator information, and operation information related to picking operation scheduling; a construction module for constructing a picking operation optimization model for the dual-elevator shuttle warehouse system based on the parameters; and a second acquisition module for using the dual-elevator shuttle warehouse system to construct the picking operation optimization model and, based on the operation information, acquiring the picking operation scheduling strategy of the dual-elevator shuttle warehouse system. The picking operation optimization system for a dual-elevator shuttle warehouse system provided by this invention can improve the response speed of the supply chain and increase the picking efficiency of the dual-elevator shuttle warehouse system.

[0043] An electronic device includes: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to perform a method for optimizing the picking operation of a dual-elevator shuttle storage system according to the present invention.

[0044] Therefore, the present invention has the following beneficial effects: The picking operation optimization method of the dual-elevator shuttle warehouse system provided by the present invention rationally arranges the shuttle and elevator to complete the picking operation, optimizes the operation sequence, and considers the interaction between elevators and shuttles, and between elevators. Compared with the prior art, it saves completion time and achieves high throughput capacity; The picking operation optimization system of the dual-elevator shuttle warehouse system provided by the present invention can improve the response speed of the supply chain and improve the picking operation efficiency of the dual-elevator shuttle warehouse system. Attached Figure Description

[0045] Figure 1 This is a flowchart of the method of the present invention;

[0046] Figure 2 This is a schematic diagram of the system structure of the present invention;

[0047] Figure 3 This is a block diagram of the electronic device structure according to an embodiment of the present invention.

[0048] In the diagram: 300, Picking operation optimization system; 310, First acquisition module; 320, Construction module; 330, Second acquisition module; 401, Processor; 402, Read-only memory; 403, Random access memory; 404, Bus; 405, I / O interface; 406, Input section; 407, Output section; 408, Storage section; 409, Communication section; 410, Driver; 411, Removable media. Detailed Implementation

[0049] The present invention will now be further described with reference to the accompanying drawings and specific embodiments.

[0050] In a dual-elevator shuttle system, the shuttle moves horizontally within the current floor to retrieve goods, while the elevator travels vertically to complete the retrieval. Although a dual-elevator system is more efficient than a single-elevator system, scheduling retrieval operations in a dual-elevator system is complex and challenging because both elevators share the same mast. To improve system efficiency, the order in which retrieval operations are completed needs to be optimized, determining which elevator and in what order completes the tasks, as well as the order in which the shuttle completes the tasks. By optimizing the scheduling strategy, the system's operation completion time can be reduced, system efficiency can be improved, and consequently, the efficiency of the entire supply chain can be enhanced.

[0051] Figure 1 A flowchart illustrating an operation optimization method for a dual-elevator shuttle storage system according to an embodiment of the present invention is shown.

[0052] like Figure 1 As shown, the job optimization method in this embodiment includes operations S1 to S3.

[0053] In operation S1, parameters of the dual-elevator shuttle storage system are obtained, including system structure information, shuttle information, elevator information, and operation information related to the picking operation scheduling.

[0054] In operation S2, an operation optimization model is built for the dual-elevator shuttle storage system based on the parameters.

[0055] By deciding the order of pickups and how to assign tasks to shuttles, the time to complete all operations can be determined.

[0056] In operation S3, the picking operation optimization model is used to obtain the picking operation scheduling strategy of the dual-elevator shuttle warehouse system based on the operation information.

[0057] The operation information includes the quantity of pickup operations and the coordinates of the pickup operations.

[0058] By utilizing the above-mentioned operation optimization methods, the overall operational efficiency of the dual-elevator shuttle storage system can be improved, and the time required for the dual-elevator shuttle storage system to complete all operations can be reduced, thereby effectively reducing costs.

[0059] According to an embodiment of the present invention, the above-mentioned system structure information includes information on the number of shelf layers, information on the number of storage locations per layer, information on the spacing between adjacent layers, and information on the length and width of storage locations; shuttle information includes shuttle speed information and information on the time it takes for the shuttle to pick up or release a piece of goods; elevator information includes elevator speed information and information on the initial stopping floor position of the elevator; and operation information includes information on the number of picking operations, information on the coordinates of picking operations, information on the time required for the shuttle to process the operation, and information on the time required for the elevator to reach the operation floor.

[0060] In this embodiment, the formula for calculating the time required for the shuttle to handle task i is as follows:

[0061]

[0062] The formula for calculating the time required for elevator 1 to reach the floor where task i is located is as follows:

[0063]

[0064] The formula for calculating the time required for elevator 2 to reach the floor where task i is located is as follows:

[0065]

[0066] Among them, X i D is the coordinate of the storage location where operation i is located. c It is the unit length of the storage space, v shuttle It's the shuttle speed, Z. i D is the coordinate of the layer where task i is located. h It is the unit floor height, v lift It refers to the elevator's operating speed.

[0067] In this embodiment, the pickup operation optimization model is as follows:

[0068]

[0069] in, It is the time it takes for elevator 1 to unload the work and reach the exit in the k-th cycle. It is the time it takes for elevator 2 to unload its work and reach the exit in the kth cycle.

[0070] In this embodiment, the time it takes for elevator 1 to unload the work and reach the exit in the k-th cycle is... as follows:

[0071]

[0072] The time it takes for elevator 2 to unload the work and reach the exit in the kth cycle as follows:

[0073]

[0074] Among them, u i It is the time when task i is released onto the elevator, u j It is the time when assignment j is released onto the elevator, d i This is the time required for elevator 1 to travel from the exit to the floor where work i is located. It is the time required for elevator 2 to travel from floor -1 to the floor where operation i is located.

[0075] In this embodiment, the constraints of the picking operation optimization model are as follows:

[0076]

[0077] This constraint ensures that elevator 1 completes only one task in each cycle.

[0078]

[0079] This constraint ensures that each job is completed.

[0080]

[0081] This constraint is a network traffic constraint.

[0082]

[0083] This constraint determines whether task i is executed after task j, and vice versa.

[0084]

[0085] This constraint stipulates that the working floor operated by elevator 2 cannot exceed the working floor operated by elevator 1.

[0086]

[0087] This constraint is used to calculate the time required for the elevator to acquire the task.

[0088]

[0089] This constraint gives the binary decision variable x ik The range of values ​​for .

[0090]

[0091] This constraint gives the binary decision variable y ijk The range of values ​​for .

[0092] Where, x ik It is a binary decision variable; it equals 1 when elevator 1 completes operation i in the k-th cycle, and equals 0 otherwise. ijkThese are binary decision variables. The value is 1 when elevator 2 completes task i first, followed immediately by task j in the k-th cycle; otherwise, it is 0. R is the set of tasks, K is the set of cycles, and u... i It is the time when task i is released onto the elevator, u j It is the time when assignment j is released onto the elevator, d i This is the time required for elevator 1 to travel from the exit to the floor where work i is located. The time p is the time required for elevator 2 to travel from floor -1 to the floor where operation i is located. i This is the time required for the shuttle to process task i.

[0093] In this embodiment, a dynamic programming model is used to optimize the order of goods retrieval for the two elevators. The dynamic programming model is as follows:

[0094]

[0095]

[0096]

[0097]

[0098] Where F(s,e) represents the shortest completion time for completing e tasks in the first s stages, F(s-1,e′) represents the shortest completion time for completing e′ tasks in the first s-1 stages, and c(s,e′,e) represents the shortest completion time for completing ee tasks in the s-th stage. ′ +1 The time required to complete task e; This represents the travel time of elevator 1 in stage s. c (s,e′,e) represents the travel time of elevator 2 in stage s, and d e This is the time required for elevator 1 to travel from the exit to the floor where work e is located. e This indicates the time when task e is released onto the elevator. This is the time required for elevator 2 to travel from floor -1 to the floor where work e-1 is located. e-1 This indicates the time when task e-1 was released onto the elevator.

[0099] In this embodiment, relative task completion time is used as the metric, and the relative task completion time is calculated as follows:

[0100]

[0101] Where M(P) represents the total completion time of the operation obtained by empirical decision-making, and M(C) is the total completion time of the operation obtained by solving the picking operation optimization model.

[0102] To more intuitively demonstrate the reduction of operation time in a dual-elevator shuttle warehouse system, this embodiment uses a dual-elevator shuttle warehouse system from a certain location as an example. The current empirical decision-making method used in this dual-elevator shuttle warehouse system is as follows: picking operations are performed in a first-come, first-served order. This embodiment of the invention selects the percentage difference between the empirical decision-making method and the method proposed in this invention as a measurement indicator, as shown below:

[0103]

[0104] Where M(P) and M(C) represent the total task completion time obtained by empirical decision-making and the method proposed in this invention, respectively. Table 1 shows the relative task completion times.

[0105] Table 1 Relative Task Completion Time

[0106]

[0107]

[0108] Note: |O| represents the number of assignments.

[0109] As shown in Table 1, the method proposed in this invention performs better than empirical decision-making in real-world applications, greatly reducing service time and improving system operating efficiency.

[0110] Figure 2 The diagram illustrates the structure of an operation optimization system for a dual-elevator shuttle storage system according to an embodiment of the present invention.

[0111] like Figure 2 As shown, the pickup operation optimization system 300 of this embodiment includes a first acquisition module 310, a construction module 320, and a second acquisition module 330.

[0112] The first acquisition module 310 is used to acquire parameters of the dual-elevator shuttle storage system, including system structure information, shuttle information, elevator information and operation information related to the picking operation scheduling.

[0113] Module 320 is used to build an optimized model for picking operations for a dual-elevator shuttle warehouse system based on parameters.

[0114] The second acquisition module 330 is used to acquire the picking operation scheduling strategy of the dual elevator shuttle warehouse system based on the operation information using the dual elevator shuttle warehouse system picking operation optimization model.

[0115] By utilizing the aforementioned operation optimization system, the dual-elevator shuttle storage system can achieve the optimal operation sequence, thereby significantly reducing operation completion time, improving operation efficiency, and ultimately reducing the overall operating cost of the dual-elevator shuttle storage system.

[0116] Figure 3 A block diagram of an electronic device suitable for implementing an operation optimization method for a dual-elevator shuttle storage system, according to an embodiment of the present invention, is shown schematically.

[0117] like Figure 3 As shown, an electronic device according to an embodiment of the present invention includes a processor 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage portion 408 into a random access memory (RAM) 403. The processor 401 may include a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 401 may also include onboard memory for caching purposes. The processor 401 may include a single processing unit or multiple processing units for performing different actions of the method flow according to embodiments of the present disclosure.

[0118] Random access memory 403 stores various programs and data required for the operation of the electronic device. Processor 401, read-only memory 402, and random access memory 403 are interconnected via bus 404. Processor 401 executes various operations of the method flow according to embodiments of the present invention by executing programs stored in read-only memory 402 and / or random access memory 403. It should be noted that programs may also be stored in one or more memories other than read-only memory 402 and random access memory 403. Processor 401 may also execute various operations of the method flow according to embodiments of the present invention by executing programs stored in one or more memories.

[0119] According to embodiments of the present invention, the electronic device may further include an input / output (I / O) interface 405, which is also connected to a bus 404. The electronic device may also include one or more of the following components connected to the I / O interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN card, modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A driver 410 is connected to the I / O interface 405 as needed. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the driver 410 as needed so that computer programs read from it can be installed into the storage section 408 as needed.

[0120] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions conceived without creative effort should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing the picking operation of a dual-elevator shuttle warehouse system, characterized in that, Includes the following steps: S1: Obtain the parameters of the dual-elevator shuttle warehouse system, including system structure information, shuttle information, elevator information and operation information related to the picking operation scheduling; The system structure information includes information on the number of shelf layers, the number of storage locations per layer, the spacing between adjacent layers, and the length and width of the storage locations. The shuttle information includes shuttle speed information and the time information when the shuttle picks up or releases a cargo; The elevator information includes elevator speed information and elevator initial stopping floor location information; The operation information includes the quantity of goods to be picked up, the coordinates of the goods to be picked up, the time required for the shuttle car to process the operation, and the time required for the elevator to reach the operation floor. The shuttle handling operation described above The formula for calculating the required time is as follows: Elevator 1 arrival operation The formula for calculating the time required for the current layer is as follows: Elevator 2 arrival operation The formula for calculating the time required for the current layer is as follows: in, It's homework. Coordinates of the location of the cargo. It is the unit length of the storage space. It's the speed of the shuttle. It's homework. The coordinates of the layer, It is the unit floor height. It refers to the elevator's operating speed; S2: Based on the parameters, construct an optimization model for picking operations for the dual-elevator shuttle warehouse system; The optimized model for the pickup operation is as follows: in, Is elevator 1 in the... The time from unloading the work to exiting the station in each cycle. Elevator 2 is in The time from unloading the work to exiting the station in each cycle; The elevator 1 in the The time for unloading work to the exit in each cycle as follows: The elevator 2 in the The time for unloading work to the exit in each cycle as follows: in, It's homework. The time it took to be released onto the elevator, It's homework. The time it took to be released onto the elevator, Elevator 1 is from the exit to the work area. The time required for the current layer Elevator 2 goes from -1 floor to the work area. The required time for the current layer; The constraints of the picking operation optimization model are as follows: in, It is a binary decision variable, when elevator 1 is in the... Complete the task in one cycle. If the value is 1, then it equals 0; otherwise, it equals 0. It is a binary decision variable, when elevator 2 is in the... The task is completed in one cycle. Then complete the assignment. If the value is 1, then it equals 0; otherwise, it equals 0. K is the set of assignments, and K is the set of cycles. It's homework. The time it took to be released onto the elevator, It's homework. The time it took to be released onto the elevator, Elevator 1 is from the exit to the work area. The time required for the current layer Elevator 2 goes from -1 floor to the work area. The time required for the current layer It is a shuttle car handling operation Time required; S3: Using the picking operation optimization model, obtain the picking operation scheduling strategy of the shuttle warehouse system based on the operation information; It also includes using a dynamic programming model to optimize the order of goods pickup operations for the two elevators, the dynamic programming model being as follows: in, Indicates preceding Phase completed The shortest time to complete each task Indicates preceding Phase completed The shortest time to complete each task Indicates the first Phase completion assignment The time required to complete task e; Indicates that elevator 1 is in the... The duration of each stage of the journey. This indicates that elevator 2 is in the... The duration of each stage of the journey. Elevator 1 is from the exit to the work area. The time required for the current layer Indicate homework The time it took to be released onto the elevator; Elevator 2 goes from -1 floor to the work area. The time required for the current layer Indicate homework The time it took to be released onto the elevator.

2. The method for optimizing the picking operation of a dual-elevator shuttle warehouse system according to claim 1, characterized in that, It also includes using relative task completion time as a metric, and the relative task completion time is calculated as follows: in, This represents the total completion time of the task obtained from empirical decision-making. The total completion time of the operation is obtained by solving the pickup operation optimization model.

3. A retrieval operation optimization system for a dual-elevator shuttle warehouse system, applicable to the retrieval operation optimization method for a dual-elevator shuttle warehouse system as described in claim 1, characterized in that... include: The first acquisition module is used to obtain parameters of the dual-elevator shuttle storage system, wherein the parameters include system structure information, shuttle information, elevator information and operation information related to the picking operation scheduling; A construction module is used to build an optimized model for picking operations for the dual-elevator shuttle warehouse system based on the parameters. The second acquisition module is used to construct a picking operation optimization model using the dual-elevator shuttle warehouse system, and to acquire the picking operation scheduling strategy of the dual-elevator shuttle warehouse system based on the operation information.

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