Planning method and system for plane warehouse goods placement based on model calculation

Abstract

The invention relates to a plane warehouse goods placement planning method and system based on model calculation, and belongs to the technical field of warehouse management, and the method comprises the steps: obtaining plane warehouse parameters of a target plane warehouse and goods parameters corresponding to target goods needing to be stored in the target plane warehouse, the plane warehouse parameters at least comprise space parameters of the plane warehouse and distance parameters corresponding to the space parameters, and the cargo parameters at least comprise cargo specification parameters and cargo utilization rates; determining a first placement area of the target goods according to the distance parameter and the goods utilization rate; determining a second placement area of the target goods according to the space parameters and the goods specification parameters of the planar warehouse; and in combination with a pre-constructed placement area evaluation model, the first placement area and the second placement area, determining a target placement area where the target goods are placed. According to the invention, the labor cost and the time cost can be reduced, and the efficiency and the accuracy of plane warehouse cargo placement planning are improved.

Description

Technical Field

[0001] The present application relates to the technical field of warehouse management, and in particular to a method and system for cargo placement planning in a flat warehouse based on model calculation. Background Art

[0002] The existing technology usually relies on manual recording and calculation to plan the placement of goods in a flat warehouse, which has the following disadvantages:

[0003] (1) Relying on personal experience and subjective judgment, lacking standardization and objectivity;

[0004] (2) Manual recording and calculation are prone to errors, especially when the amount of data is large or the environment is complex;

[0005] (3) Every time the environment or operating model changes, additional time and resources may be required to adapt to the new conditions, resulting in high adaptability costs;

[0006] (4) Data processing is complex and manual calculations take a long time, which is time-consuming.

[0007] Therefore, there is an urgent need to propose a method and system for cargo placement planning in a planar warehouse based on model calculation that can improve efficiency and accuracy. Summary of the invention

[0008] Based on this, it is necessary to provide a method and system for cargo placement planning in a planar warehouse based on model calculation that can improve efficiency and accuracy in response to the above technical problems.

[0009] In a first aspect, a method for cargo placement planning in a planar warehouse based on model calculation is provided, the method comprising:

[0010] Acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate;

[0011] Determining a first placement area for the target goods according to the distance parameter and the goods utilization rate;

[0012] Determining a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods;

[0013] A target placement area is determined by combining the pre-constructed placement area evaluation model, the first placement area, and the second placement area, and the target goods are placed in the target placement area.

[0014] Optionally, after obtaining the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, the method further includes:

[0015] Based on the target parameter preprocessing mechanism, the plane warehouse parameters and the cargo parameters are preprocessed respectively;

[0016] The preprocessed planar warehouse parameters and the cargo parameters are classified and stored.

[0017] Optionally, expressions corresponding to the target parameter preprocessing mechanism include:

[0018]

[0019] Among them, Q i represents the normalized coefficient of the i-th parameter attribute, D j represents the custom coefficient of the jth parameter, P ij represents the i-th parameter attribute of the j-th parameter, P i represents the weight of the i-th parameter attribute, k represents the number of parameter attributes, Represents the normalized value of the i-th parameter attribute of the j-th parameter, i = 1, 2, ..., m, and m represents the number of parameters.

[0020] Optionally, determining the first placement area of ​​the target cargo according to the distance parameter and the cargo utilization rate includes:

[0021] Acquiring the distance parameter and the cargo utilization rate;

[0022] Based on a first objective function, a first target score corresponding to the distance parameter and the cargo utilization rate is determined, wherein the first objective function includes:

[0023] L1=q1A+q2B

[0024] Among them, L1 represents the first target score, q1 and q2 represent weight coefficients, A represents the distance parameter, and B represents the cargo utilization rate;

[0025] In response to detecting that the first target score is greater than a first preset threshold, the planar warehouse placement area corresponding to the first target score is determined as a first placement area for the target goods.

[0026] Optionally, determining the second placement area of ​​the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods includes:

[0027] Acquire the space parameters of the planar warehouse and the specification parameters of the goods;

[0028] Based on a second objective function, a second objective score corresponding to the space parameter of the planar warehouse and the cargo specification parameter is determined, wherein the second objective function includes:

[0029] L2=q3C+q4E+q5(F1-F2)

[0030] Among them, L2 represents the second target score, q3, q4, and q5 all represent weight coefficients, C represents the number of goods placed in the target placement area, E represents the gap between goods stacked, F1 represents the remaining space in the target placement area, and F2 represents the volume of the target goods;

[0031] In response to detecting that the second target score is greater than a second preset threshold, the planar warehouse placement area corresponding to the second target score is determined as a second placement area for the target goods.

[0032] Optionally, combining a pre-built placement area evaluation model, the first placement area, and the second placement area to determine a target placement area, and placing the target goods in the target placement area includes:

[0033] Determining the constraint conditions of the placement area evaluation model includes:

[0034] H∈[h1∩h2]

[0035] e1≤E≤e2

[0036] F>r1F=h3-h4

[0037] L>r2L=|L1-L2|

[0038] Among them, H represents the target placement area, h1 represents the first placement area, h2 represents the second placement area, e1 represents the minimum cargo stacking gap, e2 represents the maximum cargo stacking gap, h3 represents the cargo space occupied by the placement area corresponding to the currently placed most cargo, h4 represents the cargo space occupied by the placement area corresponding to the currently placed least cargo, r represents the preset cargo space occupied standard value, and r2 represents the preset score standard value;

[0039] Determine the objective function of the placement area evaluation model, the expression of the objective function of the placement area evaluation model includes:

[0040]

[0041] Among them, B v represents the target value, V represents the correction function, n represents the number of target placement areas, Z1 represents the weight matrix of the target placement area, ρ w represents the spatial parameter correction coefficient corresponding to the w-th target placement area, N w represents the cargo utilization rate, Mw represents the constant coefficient, α represents the distance parameter correction coefficient, U w Represents the distance parameter, Y τ Represents the fusion classification coefficient.

[0042] Optionally, the method further includes:

[0043] Based on the constraint conditions, the objective function of the placement area evaluation model is solved, and when the target value meets the preset standard, the target placement area is obtained, and the target goods are placed in the target placement area.

[0044] In a second aspect, a system for planning cargo placement in a planar warehouse based on model calculation is provided, the system comprising:

[0045] A parameter acquisition module, used to acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate;

[0046] A first determination module, used to determine a first placement area for the target goods according to the distance parameter and the goods utilization rate;

[0047] A second determination module is used to determine a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods;

[0048] The cargo placement module is used to determine a target placement area by combining a pre-built placement area evaluation model, the first placement area, and the second placement area, and to place the target cargo in the target placement area.

[0049] Optionally, determining the first placement area of ​​the target cargo according to the distance parameter and the cargo utilization rate includes:

[0050] Acquiring the distance parameter and the cargo utilization rate;

[0051] Based on a first objective function, a first target score corresponding to the distance parameter and the cargo utilization rate is determined, wherein the first objective function includes:

[0052] L1=q1A+q2B

[0053] Among them, L1 represents the first target score, q1 and q2 represent weight coefficients, A represents the distance parameter, and B represents the cargo utilization rate;

[0054] In response to detecting that the first target score is greater than a first preset threshold, the planar warehouse placement area corresponding to the first target score is determined as a first placement area for the target goods.

[0055] Optionally, determining the second placement area of ​​the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods includes:

[0056] Acquire the space parameters of the planar warehouse and the specification parameters of the goods;

[0057] Based on a second objective function, a second objective score corresponding to the space parameter of the planar warehouse and the cargo specification parameter is determined, wherein the second objective function includes:

[0058] L2=q3C+q4E+q5(F1-F2)

[0059] Among them, L2 represents the second target score, q3, q4, and q5 all represent weight coefficients, C represents the number of goods placed in the target placement area, E represents the gap between goods stacked, F1 represents the remaining space in the target placement area, and F2 represents the volume of the target goods;

[0060] In response to detecting that the second target score is greater than a second preset threshold, the planar warehouse placement area corresponding to the second target score is determined as a second placement area for the target goods.

[0061] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:

[0062] Acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate;

[0063] Determining a first placement area for the target goods according to the distance parameter and the goods utilization rate;

[0064] Determining a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods;

[0065] A target placement area is determined by combining the pre-constructed placement area evaluation model, the first placement area, and the second placement area, and the target goods are placed in the target placement area.

[0066] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0067] Acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate;

[0068] Determining a first placement area for the target goods according to the distance parameter and the goods utilization rate;

[0069] Determining a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods;

[0070] A target placement area is determined by combining the pre-constructed placement area evaluation model, the first placement area, and the second placement area, and the target goods are placed in the target placement area.

[0071] In a fifth aspect, a computer program product is provided, the computer program product comprising a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0072] Acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate;

[0073] Determining a first placement area for the target goods according to the distance parameter and the goods utilization rate;

[0074] Determining a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods;

[0075] A target placement area is determined by combining the pre-constructed placement area evaluation model, the first placement area, and the second placement area, and the target goods are placed in the target placement area.

[0076] The above-mentioned method and system for cargo placement planning in a planar warehouse based on model calculation, the method includes: obtaining the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include cargo specification parameters and cargo utilization rate; determining the first placement area of ​​the target cargo according to the distance parameters and the cargo utilization rate; determining the second placement area of ​​the target cargo according to the space parameters of the planar warehouse and the cargo specification parameters; determining the target placement area in combination with a pre-constructed placement area evaluation model, the first placement area and the second placement area, and placing the target cargo in the target placement area. The present application can reduce the errors caused by manual calculations by intelligently processing the collected parameters, reduce labor costs and time costs, and thus improve the efficiency and accuracy of cargo placement planning in planar warehouses. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 This is an application environment diagram of a method for planning the placement of goods in a planar warehouse based on model calculation in one embodiment;

[0078] Figure 2 It is a flowchart of a method for calculating the planar warehouse cargo placement planning based on a model in one embodiment;

[0079] Figure 3 It is a structural block diagram of a system for planning the placement of goods in a planar warehouse based on model calculation in one embodiment;

[0080] Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0081] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0082] It should be understood that in the description of the present application, unless the context clearly requires otherwise, words such as "include", "comprises", and the like throughout the specification should be interpreted as including rather than being exclusive or exhaustive; that is, as including but not limited to.

[0083] It should also be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, "plurality" means two or more.

[0084] It should be noted that the terms "S1", "S2", etc. are only used for the purpose of describing the steps, and do not specifically refer to the order or sequence, nor are they used to limit the present application. They are only for the convenience of describing the method of the present application, and cannot be understood as indicating the order of the steps. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0085] The method for planning the placement of goods in a flat warehouse based on model calculation provided in this application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the data processing platform set on the server 104 through the network, wherein the terminal 102 can be but not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices, and the server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0086] In one embodiment, Figure 2 As shown in the figure, a method for cargo placement planning in a flat warehouse based on model calculation is provided. Figure 1 The terminal in is used as an example to illustrate, including the following steps:

[0087] S1: Obtain the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include cargo specification parameters and cargo utilization rate.

[0088] It should be noted that the spatial parameters of a flat warehouse generally include the number of placement areas of the warehouse, the size of each placement area, and the spacing between goods. The distance parameters corresponding to the spatial parameters generally include the distance between each placement area and the entrance and exit. The cargo specification parameters generally include parameter information such as cargo volume, size, and weight. The cargo utilization rate is determined by the frequency with which the goods are moved out of or into the flat warehouse.

[0089] In some specific implementations, after obtaining the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, the method further includes:

[0090] Based on the target parameter preprocessing mechanism, the plane warehouse parameters and the cargo parameters are preprocessed respectively, wherein the expressions corresponding to the target parameter preprocessing mechanism include:

[0091]

[0092] Among them, Q i represents the normalized coefficient of the i-th parameter attribute, D j represents the custom coefficient of the jth parameter, P ij represents the i-th parameter attribute of the j-th parameter, P i represents the weight of the i-th parameter attribute, k represents the number of parameter attributes, represents the normalized value of the i-th parameter attribute of the j-th parameter, i = 1, 2, ..., m, m represents the number of parameters;

[0093] The preprocessed plane warehouse parameters and the cargo parameters are classified and stored, that is, the parameters of different categories are stored in their corresponding databases, such as the plane warehouse parameters, which are stored in the database corresponding to the plane warehouse, and so on, which will not be repeated here.

[0094] S2: Determine a first placement area for the target cargo according to the distance parameter and the cargo utilization rate.

[0095] It should be noted that the first placement area is a placement area that can be efficiently transported by combining distance parameters and cargo utilization. For example, cargo with high cargo utilization can be placed at a location closer to the entrance, and cargo with low cargo utilization can be placed at a location farther from the entrance.

[0096] In some specific implementations, determining the first placement area of ​​the target cargo according to the distance parameter and the cargo utilization rate includes:

[0097] Acquiring the distance parameter and the cargo utilization rate;

[0098] Based on a first objective function, a first target score corresponding to the distance parameter and the cargo utilization rate is determined, wherein the first objective function includes:

[0099] L1=q1A+q2B

[0100] Among them, L1 represents the first target score, q1 and q2 represent weight coefficients, A represents the distance parameter, and B represents the cargo utilization rate;

[0101] In response to detecting that the first target score is greater than a first preset threshold, the flat warehouse placement area corresponding to the first target score is determined as the first placement area for the target goods, wherein the first preset threshold can be set according to actual needs, and the first placement area can include multiple placement areas that meet the above standards.

[0102] S3: Determine a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods.

[0103] It should be noted that the second placement area is determined by combining the space parameters of the flat warehouse and the cargo specification parameters to ensure that the cargo space occupancy in each placement area is relatively evenly distributed. If the cargo in a certain placement area occupies a smaller space, this placement area will be given priority to place the cargo that needs to be stored.

[0104] In some specific implementations, determining the second placement area of ​​the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods includes:

[0105] Acquire the space parameters of the planar warehouse and the specification parameters of the goods;

[0106] Based on a second objective function, a second objective score corresponding to the space parameter of the planar warehouse and the cargo specification parameter is determined, wherein the second objective function includes:

[0107] L2=q3C+q4E+q5(F1-F2)

[0108] Among them, L2 represents the second target score, q3, q4, and q5 all represent weight coefficients, C represents the number of goods placed in the target placement area, E represents the gap between goods stacked, F1 represents the remaining space in the target placement area, and F2 represents the volume of the target goods;

[0109] In response to detecting that the second target score is greater than a second preset threshold, the flat warehouse placement area corresponding to the second target score is determined as the second placement area for the target goods, wherein the second preset threshold can be set according to actual needs, and the second placement area can include multiple placement areas that meet the above standards.

[0110] S4: Determine a target placement area by combining the pre-built placement area evaluation model, the first placement area, and the second placement area, and place the target goods in the target placement area.

[0111] It should be noted that the placement area evaluation model includes constraints and objective functions, and the target placement area is the area where the goods are finally placed.

[0112] In some specific implementations, combining the pre-built placement area evaluation model, the first placement area, and the second placement area, determining a target placement area, and placing the target goods in the target placement area includes:

[0113] Determining the constraint conditions of the placement area evaluation model includes:

[0114] H∈[h1∩h2]

[0115] e1≤E≤e2

[0116] F>r1F=h3-h4

[0117] L>r2L=|L1-L2|

[0118] Among them, H represents the target placement area, h1 represents the first placement area, h2 represents the second placement area, e1 represents the minimum cargo stacking gap, e2 represents the maximum cargo stacking gap, h3 represents the cargo space occupied by the placement area corresponding to the currently placed most cargo, h4 represents the cargo space occupied by the placement area corresponding to the currently placed least cargo, r represents the preset cargo space occupied standard value, and r2 represents the preset score standard value;

[0119] Determine the objective function of the placement area evaluation model, the expression of the objective function of the placement area evaluation model includes:

[0120]

[0121] Among them, B v represents the target value, V represents the correction function, n represents the number of target placement areas, Z1 represents the weight matrix of the target placement area, ρ w represents the spatial parameter correction coefficient corresponding to the w-th target placement area, N w represents the cargo utilization rate, M w represents the constant coefficient, α represents the distance parameter correction coefficient, U w Represents the distance parameter, Y τ Represents the fusion classification coefficient.

[0122] Among them, all parameter information used for calculation in this application are parameters processed by the preprocessing mechanism in step S1, and the preprocessing mechanism is used to eliminate the dimensions between parameters to facilitate calculation.

[0123] In some embodiments, the method further comprises:

[0124] Based on the constraints, the objective function of the placement area evaluation model is solved. When the target value meets the preset standard, the target placement area is obtained, and the target goods are placed in the target placement area, wherein the preset standard is that the target value reaches the minimum, and the target placement area refers to the placement area corresponding to when the target value reaches the minimum. The solution method of the evaluation model is a commonly used method, such as taking specific points of the objective function to solve one by one, solving the derivative of the objective function, etc. The corresponding solution method can be selected according to actual needs, and the solution process will not be repeated here. After the target placement area is determined, its location information can be sent to the terminal to facilitate the staff or cargo transport machine to place the target goods in the target placement area.

[0125] In the above-mentioned model-based calculation method for flat warehouse cargo placement planning, the method includes: obtaining the flat warehouse parameters of the target flat warehouse and the cargo parameters corresponding to the target cargo to be stored in the target flat warehouse, the flat warehouse parameters at least include the space parameters of the flat warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include cargo specification parameters and cargo utilization; determining the first placement area of ​​the target cargo according to the distance parameters and the cargo utilization; determining the second placement area of ​​the target cargo according to the space parameters of the flat warehouse and the cargo specification parameters; determining the target placement area in combination with the pre-constructed placement area evaluation model, the first placement area and the second placement area, and placing the target cargo in the target placement area. The present application can reduce the errors caused by manual calculations by intelligently processing the collected parameters, reduce labor costs and time costs, and thereby improve the efficiency and accuracy of flat warehouse cargo placement planning.

[0126] It should be understood that although Figure 2 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0127] In one embodiment, Figure 3 As shown, a system for cargo placement planning in a planar warehouse based on model calculation is provided, comprising: a parameter acquisition module, a first determination module, a second determination module and a cargo placement module, wherein:

[0128] A parameter acquisition module, used to acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate;

[0129] A first determination module, used to determine a first placement area for the target goods according to the distance parameter and the goods utilization rate;

[0130] A second determination module is used to determine a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods;

[0131] The cargo placement module is used to determine a target placement area by combining a pre-built placement area evaluation model, the first placement area, and the second placement area, and to place the target cargo in the target placement area.

[0132] As a preferred implementation, in the embodiment of the present invention, the system further includes a parameter preprocessing module, and the parameter preprocessing module is specifically used for:

[0133] Based on the target parameter preprocessing mechanism, the plane warehouse parameters and the cargo parameters are preprocessed respectively;

[0134] The preprocessed plane warehouse parameters and the cargo parameters are classified and stored; wherein the expression corresponding to the target parameter preprocessing mechanism includes:

[0135]

[0136] Among them, Q i represents the normalized coefficient of the i-th parameter attribute, D j represents the custom coefficient of the jth parameter, P ij represents the i-th parameter attribute of the j-th parameter, P i represents the weight of the i-th parameter attribute, k represents the number of parameter attributes, Represents the normalized value of the i-th parameter attribute of the j-th parameter, i = 1, 2, ..., m, and m represents the number of parameters.

[0137] As a preferred implementation manner, in the embodiment of the present invention, the first determination module is specifically used for:

[0138] Acquiring the distance parameter and the cargo utilization rate;

[0139] Based on a first objective function, a first target score corresponding to the distance parameter and the cargo utilization rate is determined, wherein the first objective function includes:

[0140] L1=q1A+q2B

[0141] Among them, L1 represents the first target score, q1 and q2 represent weight coefficients, A represents the distance parameter, and B represents the cargo utilization rate;

[0142] In response to detecting that the first target score is greater than a first preset threshold, the planar warehouse placement area corresponding to the first target score is determined as a first placement area for the target goods.

[0143] As a preferred implementation manner, in the embodiment of the present invention, the second determination module is specifically used for:

[0144] Acquire the space parameters of the planar warehouse and the specification parameters of the goods;

[0145] Based on a second objective function, a second objective score corresponding to the space parameter of the planar warehouse and the cargo specification parameter is determined, wherein the second objective function includes:

[0146] L2=q3C+q4E+q5(F1-F2)

[0147] Among them, L2 represents the second target score, q3, q4, and q5 all represent weight coefficients, C represents the number of goods placed in the target placement area, E represents the gap between goods stacked, F1 represents the remaining space in the target placement area, and F2 represents the volume of the target goods;

[0148] In response to detecting that the second target score is greater than a second preset threshold, the planar warehouse placement area corresponding to the second target score is determined as a second placement area for the target goods.

[0149] As a preferred implementation, in the embodiment of the present invention, the cargo placement module is specifically used for:

[0150] Determining the constraint conditions of the placement area evaluation model includes:

[0151] H∈[h1∩h2]

[0152] e1≤E≤e2

[0153] F>r1F=h3-h4

[0154] L>r2L=|L1-L2|

[0155] Among them, H represents the target placement area, h1 represents the first placement area, h2 represents the second placement area, e1 represents the minimum cargo stacking gap, e2 represents the maximum cargo stacking gap, h3 represents the cargo space occupied by the placement area corresponding to the currently placed most cargo, h4 represents the cargo space occupied by the placement area corresponding to the currently placed least cargo, r represents the preset cargo space occupied standard value, and r2 represents the preset score standard value;

[0156] Determine the objective function of the placement area evaluation model, the expression of the objective function of the placement area evaluation model includes:

[0157]

[0158] Among them, B v represents the target value, V represents the correction function, n represents the number of target placement areas, Z1 represents the weight matrix of the target placement area, ρ w represents the spatial parameter correction coefficient corresponding to the w-th target placement area, N w represents the cargo utilization rate, M w represents the constant coefficient, α represents the distance parameter correction coefficient, U w Represents the distance parameter, Y τ Represents the fusion classification coefficient.

[0159] As a preferred implementation, in the embodiment of the present invention, the cargo placement module is further used for:

[0160] Based on the constraint conditions, the objective function of the placement area evaluation model is solved, and when the target value meets the preset standard, the target placement area is obtained, and the target goods are placed in the target placement area.

[0161] For the specific limitations of the model-based calculation planar warehouse cargo placement planning system, please refer to the limitations of the model-based calculation planar warehouse cargo placement planning method above, which will not be repeated here. Each module in the above-mentioned model-based calculation planar warehouse cargo placement planning system can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0162] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for calculating the placement planning of flat warehouse goods based on model calculation is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0163] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0164] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0165] S1: Acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate;

[0166] S2: determining a first placement area for the target goods according to the distance parameter and the goods utilization rate;

[0167] S3: determining a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods;

[0168] S4: Determine a target placement area by combining the pre-built placement area evaluation model, the first placement area, and the second placement area, and place the target goods in the target placement area.

[0169] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0170] Based on the target parameter preprocessing mechanism, the plane warehouse parameters and the cargo parameters are preprocessed respectively;

[0171] The preprocessed plane warehouse parameters and the cargo parameters are classified and stored; wherein the expression corresponding to the target parameter preprocessing mechanism includes:

[0172]

[0173] Among them, Q i represents the normalized coefficient of the i-th parameter attribute, D j represents the custom coefficient of the jth parameter, P ij represents the i-th parameter attribute of the j-th parameter, P i represents the weight of the i-th parameter attribute, k represents the number of parameter attributes, Represents the normalized value of the i-th parameter attribute of the j-th parameter, i = 1, 2, ..., m, and m represents the number of parameters.

[0174] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0175] Acquiring the distance parameter and the cargo utilization rate;

[0176] Based on a first objective function, a first target score corresponding to the distance parameter and the cargo utilization rate is determined, wherein the first objective function includes:

[0177] L1=q1A+q2B

[0178] Among them, L1 represents the first target score, q1 and q2 represent weight coefficients, A represents the distance parameter, and B represents the cargo utilization rate;

[0179] In response to detecting that the first target score is greater than a first preset threshold, the planar warehouse placement area corresponding to the first target score is determined as a first placement area for the target goods.

[0180] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0181] Acquire the space parameters of the planar warehouse and the specification parameters of the goods;

[0182] Based on a second objective function, a second objective score corresponding to the space parameter of the planar warehouse and the cargo specification parameter is determined, wherein the second objective function includes:

[0183] L2=q3C+q4E+q5(F1-F2)

[0184] Among them, L2 represents the second target score, q3, q4, and q5 all represent weight coefficients, C represents the number of goods placed in the target placement area, E represents the gap between goods stacked, F1 represents the remaining space in the target placement area, and F2 represents the volume of the target goods;

[0185] In response to detecting that the second target score is greater than a second preset threshold, the planar warehouse placement area corresponding to the second target score is determined as a second placement area for the target goods.

[0186] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0187] Determining the constraint conditions of the placement area evaluation model includes:

[0188] H∈[h1∩h2]

[0189] e1≤E≤e2

[0190] F>r1F=h3-h4

[0191] L>r2L=|L1-L2|

[0192] Among them, H represents the target placement area, h1 represents the first placement area, h2 represents the second placement area, e1 represents the minimum cargo stacking gap, e2 represents the maximum cargo stacking gap, h3 represents the cargo space occupied by the placement area corresponding to the currently placed most cargo, h4 represents the cargo space occupied by the placement area corresponding to the currently placed least cargo, r represents the preset cargo space occupied standard value, and r2 represents the preset score standard value;

[0193] Determine the objective function of the placement area evaluation model, the expression of the objective function of the placement area evaluation model includes:

[0194]

[0195] Among them, B v represents the target value, V represents the correction function, n represents the number of target placement areas, Z1 represents the weight matrix of the target placement area, ρ w represents the spatial parameter correction coefficient corresponding to the w-th target placement area, N w represents the cargo utilization rate, M w represents the constant coefficient, α represents the distance parameter correction coefficient, U w Represents the distance parameter, Y τ Represents the fusion classification coefficient.

[0196] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0197] Based on the constraint conditions, the objective function of the placement area evaluation model is solved, and when the target value meets the preset standard, the target placement area is obtained, and the target goods are placed in the target placement area.

[0198] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0199] S1: Acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate;

[0200] S2: determining a first placement area for the target goods according to the distance parameter and the goods utilization rate;

[0201] S3: determining a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods;

[0202] S4: Determine a target placement area by combining the pre-built placement area evaluation model, the first placement area, and the second placement area, and place the target goods in the target placement area.

[0203] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0204] Based on the target parameter preprocessing mechanism, the plane warehouse parameters and the cargo parameters are preprocessed respectively;

[0205] The preprocessed plane warehouse parameters and the cargo parameters are classified and stored; wherein the expression corresponding to the target parameter preprocessing mechanism includes:

[0206]

[0207] Among them, Q i represents the normalized coefficient of the i-th parameter attribute, D j represents the custom coefficient of the jth parameter, P ij represents the i-th parameter attribute of the j-th parameter, P i represents the weight of the i-th parameter attribute, k represents the number of parameter attributes, Represents the normalized value of the i-th parameter attribute of the j-th parameter, i = 1, 2, ..., m, and m represents the number of parameters.

[0208] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0209] Acquiring the distance parameter and the cargo utilization rate;

[0210] Based on a first objective function, a first target score corresponding to the distance parameter and the cargo utilization rate is determined, wherein the first objective function includes:

[0211] L1=q1A+q2B

[0212] Among them, L1 represents the first target score, q1 and q2 represent weight coefficients, A represents the distance parameter, and B represents the cargo utilization rate;

[0213] In response to detecting that the first target score is greater than a first preset threshold, the planar warehouse placement area corresponding to the first target score is determined as a first placement area for the target goods.

[0214] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0215] Acquire the space parameters of the planar warehouse and the specification parameters of the goods;

[0216] Based on a second objective function, a second objective score corresponding to the space parameter of the planar warehouse and the cargo specification parameter is determined, wherein the second objective function includes:

[0217] L2=q3C+q4E+q5(F1-F2)

[0218] Among them, L2 represents the second target score, q3, q4, and q5 all represent weight coefficients, C represents the number of goods placed in the target placement area, E represents the gap between goods stacked, F1 represents the remaining space in the target placement area, and F2 represents the volume of the target goods;

[0219] In response to detecting that the second target score is greater than a second preset threshold, the planar warehouse placement area corresponding to the second target score is determined as a second placement area for the target goods.

[0220] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0221] Determining the constraint conditions of the placement area evaluation model includes:

[0222] H∈[h1∩h2]

[0223] e1≤E≤e2

[0224] F>r1F=h3-h4

[0225] L>r2L=|L1-L2|

[0226] Among them, H represents the target placement area, h1 represents the first placement area, h2 represents the second placement area, e1 represents the minimum cargo stacking gap, e2 represents the maximum cargo stacking gap, h3 represents the cargo space occupied by the placement area corresponding to the currently placed most cargo, h4 represents the cargo space occupied by the placement area corresponding to the currently placed least cargo, r represents the preset cargo space occupied standard value, and r2 represents the preset score standard value;

[0227] Determine the objective function of the placement area evaluation model, the expression of the objective function of the placement area evaluation model includes:

[0228]

[0229] Among them, B v represents the target value, V represents the correction function, n represents the number of target placement areas, Z1 represents the weight matrix of the target placement area, ρ w represents the spatial parameter correction coefficient corresponding to the w-th target placement area, N w represents the cargo utilization rate, M w represents the constant coefficient, α represents the distance parameter correction coefficient, U w Represents the distance parameter, Y τ Represents the fusion classification coefficient.

[0230] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0231] Based on the constraint conditions, the objective function of the placement area evaluation model is solved, and when the target value meets the preset standard, the target placement area is obtained, and the target goods are placed in the target placement area.

[0232] In one embodiment, a computer program product is provided, the computer program product comprising a computer program, the computer program when executed by a processor implements the following steps:

[0233] S1: Acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate;

[0234] S2: determining a first placement area for the target goods according to the distance parameter and the goods utilization rate;

[0235] S3: determining a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods;

[0236] S4: Determine a target placement area by combining the pre-built placement area evaluation model, the first placement area, and the second placement area, and place the target goods in the target placement area.

[0237] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0238] Based on the target parameter preprocessing mechanism, the plane warehouse parameters and the cargo parameters are preprocessed respectively;

[0239] The preprocessed plane warehouse parameters and the cargo parameters are classified and stored; wherein the expression corresponding to the target parameter preprocessing mechanism includes:

[0240]

[0241] Among them, Q i represents the normalized coefficient of the i-th parameter attribute, D j represents the custom coefficient of the jth parameter, P ij represents the i-th parameter attribute of the j-th parameter, P i represents the weight of the i-th parameter attribute, k represents the number of parameter attributes, Represents the normalized value of the i-th parameter attribute of the j-th parameter, i = 1, 2, ..., m, and m represents the number of parameters.

[0242] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0243] Acquiring the distance parameter and the cargo utilization rate;

[0244] Based on a first objective function, a first target score corresponding to the distance parameter and the cargo utilization rate is determined, wherein the first objective function includes:

[0245] L1=q1A+q2B

[0246] Among them, L1 represents the first target score, q1 and q2 represent weight coefficients, A represents the distance parameter, and B represents the cargo utilization rate;

[0247] In response to detecting that the first target score is greater than a first preset threshold, the planar warehouse placement area corresponding to the first target score is determined as a first placement area for the target goods.

[0248] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0249] Acquire the space parameters of the planar warehouse and the specification parameters of the goods;

[0250] Based on a second objective function, a second objective score corresponding to the space parameter of the planar warehouse and the cargo specification parameter is determined, wherein the second objective function includes:

[0251] L2=q3C+q4e+q5(F1-F2)

[0252] Among them, L2 represents the second target score, q3, q4, and q5 all represent weight coefficients, C represents the number of goods placed in the target placement area, E represents the gap between goods stacked, F1 represents the remaining space in the target placement area, and F2 represents the volume of the target goods;

[0253] In response to detecting that the second target score is greater than a second preset threshold, the planar warehouse placement area corresponding to the second target score is determined as a second placement area for the target goods.

[0254] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0255] Determining the constraint conditions of the placement area evaluation model includes:

[0256] H∈[h1∩h2]

[0257] e1≤E≤e2

[0258] F>r1F=h3-h4

[0259] L>r2L=|L1-L2|

[0260] Among them, H represents the target placement area, h1 represents the first placement area, h2 represents the second placement area, e1 represents the minimum cargo stacking gap, e2 represents the maximum cargo stacking gap, h3 represents the cargo space occupied by the placement area corresponding to the currently placed most cargo, h4 represents the cargo space occupied by the placement area corresponding to the currently placed least cargo, r represents the preset cargo space occupied standard value, and r2 represents the preset score standard value;

[0261] Determine the objective function of the placement area evaluation model, the expression of the objective function of the placement area evaluation model includes:

[0262]

[0263] Among them, B v represents the target value, V represents the correction function, n represents the number of target placement areas, Z1 represents the weight matrix of the target placement area, ρ w represents the spatial parameter correction coefficient corresponding to the w-th target placement area, N w represents the cargo utilization rate, M w represents the constant coefficient, α represents the distance parameter correction coefficient, U wRepresents the distance parameter, Y τ Represents the fusion classification coefficient.

[0264] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0265] Based on the constraint conditions, the objective function of the placement area evaluation model is solved, and when the target value meets the preset standard, the target placement area is obtained, and the target goods are placed in the target placement area.

[0266] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0267] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0268] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A method for cargo placement planning in a planar warehouse based on model calculation, characterized in that: The method comprises: Acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate; Determining a first placement area for the target goods according to the distance parameter and the goods utilization rate; Determining a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods; A target placement area is determined by combining the pre-constructed placement area evaluation model, the first placement area, and the second placement area, and the target goods are placed in the target placement area.

2. The method for cargo placement planning in a planar warehouse based on model calculation according to claim 1 is characterized in that: After obtaining the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, the method further includes: Based on the target parameter preprocessing mechanism, the plane warehouse parameters and the cargo parameters are preprocessed respectively; The preprocessed planar warehouse parameters and the cargo parameters are classified and stored.

3. The method for cargo placement planning in a planar warehouse based on model calculation according to claim 2 is characterized in that: The expressions corresponding to the target parameter preprocessing mechanism include: Among them, Q i represents the normalized coefficient of the i-th parameter attribute, D j represents the custom coefficient of the jth parameter, P ij represents the i-th parameter attribute of the j-th parameter, P i represents the weight of the i-th parameter attribute, k represents the number of parameter attributes, Represents the normalized value of the i-th parameter attribute of the j-th parameter, i = 1, 2, ..., m, and m represents the number of parameters.

4. The method for cargo placement planning in a planar warehouse based on model calculation according to claim 3 is characterized in that: Determining the first placement area of ​​the target cargo according to the distance parameter and the cargo utilization rate includes: Acquiring the distance parameter and the cargo utilization rate; Based on a first objective function, a first target score corresponding to the distance parameter and the cargo utilization rate is determined, wherein the first objective function includes: L1=q1A+q2B Among them, L1 represents the first target score, q1 and q2 represent weight coefficients, A represents the distance parameter, and B represents the cargo utilization rate; In response to detecting that the first target score is greater than a first preset threshold, the planar warehouse placement area corresponding to the first target score is determined as a first placement area for the target goods.

5. The method for cargo placement planning in a planar warehouse based on model calculation according to claim 4 is characterized in that: Determining the second placement area of ​​the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods includes: Acquire the space parameters of the planar warehouse and the specification parameters of the goods; Based on a second objective function, a second objective score corresponding to the space parameter of the planar warehouse and the cargo specification parameter is determined, wherein the second objective function includes: L2=q3C+q4W+q5(F1-F2) Among them, L2 represents the second target score, q3, q4, and q5 all represent weight coefficients, C represents the number of goods placed in the target placement area, E represents the gap between goods stacked, F1 represents the remaining space in the target placement area, and F2 represents the volume of the target goods; In response to detecting that the second target score is greater than a second preset threshold, the planar warehouse placement area corresponding to the second target score is determined as a second placement area for the target goods.

6. The method for cargo placement planning in a planar warehouse based on model calculation according to claim 5 is characterized in that: Combining the pre-built placement area evaluation model, the first placement area, and the second placement area, determining a target placement area, and placing the target goods in the target placement area includes: Determining the constraint conditions of the placement area evaluation model includes: H∈[h1∩h2] e1≤E≤e2 F>r1F=h3-h4 L>r2L=|L1-L2| Among them, H represents the target placement area, h1 represents the first placement area, h2 represents the second placement area, e1 represents the minimum cargo stacking gap, e2 represents the maximum cargo stacking gap, h3 represents the cargo space occupied by the placement area corresponding to the currently placed most cargo, h4 represents the cargo space occupied by the placement area corresponding to the currently placed least cargo, r represents the preset cargo space occupied standard value, and r2 represents the preset score standard value; Determine the objective function of the placement area evaluation model, the expression of the objective function of the placement area evaluation model includes: Among them, B v represents the target value, V represents the correction function, n represents the number of target placement areas, Z1 represents the weight matrix of the target placement area, ρ w represents the spatial parameter correction coefficient corresponding to the w-th target placement area, N w represents the cargo utilization rate, M w represents the constant coefficient, α represents the distance parameter correction coefficient, U w Represents the distance parameter, Y τ Represents the fusion classification coefficient.

7. The method for cargo placement planning in a planar warehouse based on model calculation according to claim 6 is characterized in that: The method further comprises: Based on the constraint conditions, the objective function of the placement area evaluation model is solved, and when the target value meets the preset standard, the target placement area is obtained, and the target goods are placed in the target placement area.

8. A system for planning cargo placement in a flat warehouse based on model calculation, characterized in that: The system comprises: A parameter acquisition module, used to acquire the planar warehouse parameters of the target planar warehouse and the cargo parameters corresponding to the target cargo to be stored in the target planar warehouse, wherein the planar warehouse parameters at least include the space parameters of the planar warehouse and the distance parameters corresponding to the space parameters, and the cargo parameters at least include the cargo specification parameters and the cargo utilization rate; A first determination module, used to determine a first placement area for the target goods according to the distance parameter and the goods utilization rate; A second determination module is used to determine a second placement area for the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods; The cargo placement module is used to determine a target placement area by combining a pre-built placement area evaluation model, the first placement area, and the second placement area, and to place the target cargo in the target placement area.

9. The model-based calculation planar warehouse cargo placement planning system according to claim 8, characterized in that: Determining the first placement area of ​​the target cargo according to the distance parameter and the cargo utilization rate includes: Acquiring the distance parameter and the cargo utilization rate; Based on a first objective function, a first target score corresponding to the distance parameter and the cargo utilization rate is determined, wherein the first objective function includes: L1=q1A+q2B Among them, L1 represents the first target score, q1 and q2 represent weight coefficients, A represents the distance parameter, and B represents the cargo utilization rate; In response to detecting that the first target score is greater than a first preset threshold, the planar warehouse placement area corresponding to the first target score is determined as a first placement area for the target goods.

10. The system for planning cargo placement in a planar warehouse based on model calculation according to claim 9, characterized in that: Determining the second placement area of ​​the target goods according to the space parameters of the planar warehouse and the specification parameters of the goods includes: Acquire the space parameters of the planar warehouse and the specification parameters of the goods; Based on a second objective function, a second objective score corresponding to the space parameter of the planar warehouse and the cargo specification parameter is determined, wherein the second objective function includes: L2=q3C+q4E+q5(F1-F2) Among them, L2 represents the second target score, q3, q4, and q5 all represent weight coefficients, C represents the number of goods placed in the target placement area, E represents the gap between goods stacked, F1 represents the remaining space in the target placement area, and F2 represents the volume of the target goods; In response to detecting that the second target score is greater than a second preset threshold, the planar warehouse placement area corresponding to the second target score is determined as a second placement area for the target goods.

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