Ship freight control method and device and server

Abstract

The invention provides a ship freight control method and device and a server, and relates to the technical field of logistics management, and the method comprises the steps: obtaining order information in an order pool, the order information comprises map position information, a shipping time window and cargo attributes, and the cargo attributes comprise cargo density and cargo barycentric coordinates; performing integration processing on the map position information, the shipment time window and the cargo attributes by using a space-time clustering model in a preset cabinet splicing engine so as to dynamically adjust a cabinet splicing strategy and determine a target cabinet splicing combination; and through a preset cost analysis model, based on the target cabinet combination and the shipping information, determining a target accounting cost of logistics corresponding to the target cabinet combination, and feeding back the target cabinet combination and the target accounting cost to the user side. According to the invention, the freight cabinet splicing efficiency can be obviously improved, and the freight cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics management, and in particular, to a control method, device and server for ship freight transportation. Background Art

[0002] During the process of ship freight transportation, it is necessary to adjust the container loading strategy according to factors such as the size and weight of the goods. In addition, during the container loading process, it is also necessary to consider the shipping time and shipping location of the goods, so as to avoid placing the goods that arrive first deep in the cargo hold, which brings additional handling costs. Therefore, how to load and transport the goods to obtain the best consolidation efficiency and the optimal freight cost is an extremely complex problem. At present, related technologies propose that traditional international logistics systems mainly rely on manual experience to match orders and enter customs declaration information. Such an operation that completely relies on experience is difficult to achieve a unified loading standard, and it is also impossible to comprehensively compare and optimize various consolidation plans, resulting in low consolidation efficiency and high transportation costs. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a control method, device and server for ship freight transportation, which can significantly improve the consolidation efficiency of freight transportation and reduce the freight cost.

[0004] In a first aspect, an embodiment of the present invention provides a control method for ship freight transportation, the method includes: obtaining order information in an order pool, where the order information includes: map location information, shipping time window and cargo attributes, and the cargo attributes include: cargo density and cargo center of gravity coordinates; using a spatio-temporal clustering model in a preset consolidation engine to integrally process the map location information, shipping time window and cargo attributes, so as to dynamically adjust the consolidation strategy and determine a target consolidation combination; through a preset cost analysis model, based on the target consolidation combination and shipping information, determine the target accounting cost of the logistics corresponding to the target consolidation combination, and feedback the target consolidation combination and the target accounting cost to the client.

[0005] In an implementation manner, before the step of using a spatio-temporal clustering model in a preset consolidation engine to integrally process the map location information, shipping time window and cargo attributes, so as to dynamically adjust the consolidation strategy and determine a target consolidation combination, it includes: performing a normalization process on the map location information and the shipping time window, so as to convert the map location information into geographic coordinate information, and convert the shipping time window into a time series.

[0006] In one implementation, the steps of using the spatio-temporal clustering model in the preset container consolidation engine to integrate the map location information, shipping time window, and cargo attributes to dynamically adjust the container consolidation strategy and determine the target container consolidation combination include: performing spatial clustering processing on the geographic coordinate information to determine the target geographic area division, and performing time series clustering processing on the time series to determine the target time series range; performing multi-objective optimization processing on the original container consolidation strategy based on the target geographic area division, target time series range, and cargo attributes through the preset non-dominated sorting genetic algorithm to determine the target container consolidation combination.

[0007] In one implementation, the order information further includes: order density and order transportation demand. The steps of performing spatial clustering processing on the geographic coordinate information to determine the target geographic area division include: dividing the orders into multiple geographic areas based on the geographic coordinate information through the preset spatial clustering algorithm; dynamically adjusting the division of the geographic areas according to the order density and order transportation demand to determine the target geographic area division.

[0008] In one implementation, the order information further includes: order historical shipping time. The steps of performing time series clustering processing on the time series to determine the target time series range include: dividing the orders into multiple time series clusters based on the time series through the preset time clustering algorithm; dynamically adjusting the time series clusters according to the order historical shipping time to determine the target time series range.

[0009] In one implementation, after the steps of determining the target container consolidation combination, it includes: automatically detecting the compliance of the container loading of the target container consolidation combination based on the cargo density and cargo center of gravity coordinates through the preset three-dimensional loading simulation engine, and calculating the physical cost of the target container consolidation combination when the detection is qualified.

[0010] In one implementation, before the steps of determining the target accounting cost of the logistics corresponding to the target container consolidation combination based on the target container consolidation combination and shipping information through the preset cost analysis model and feeding back the target container consolidation combination and the target accounting cost to the user side, it includes: extracting the customs clearance information corresponding to each order through the intelligent mapping library in the preset declaration robot model, and determining the shipping information according to the customs clearance information.

[0011] Second aspect, an embodiment of the present invention further provides a control device for ship freight. The device includes: an information acquisition module that acquires order information in an order pool. The order information includes: map location information, shipping time window, and cargo attributes. The cargo attributes include: cargo density and cargo centroid coordinates; a container consolidation combination module that uses a spatio-temporal clustering model in a preset container consolidation engine to integrally process the map location information, shipping time window, and cargo attributes to dynamically adjust the container consolidation strategy and determine a target container consolidation combination; a cost analysis module that, through a preset cost analysis model, based on the target container consolidation combination and shipping information, determines the target accounting cost of the logistics corresponding to the target container consolidation combination and feeds back the target container consolidation combination and the target accounting cost to the user terminal.

[0012] Third aspect, an embodiment of the present invention further provides a server, including a processor and a memory. The memory stores computer-executable instructions that can be executed by the processor. The processor executes the computer-executable instructions to implement the method according to any one of the first aspect.

[0013] Fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by the processor, the computer-executable instructions cause the processor to implement the method according to any one of the first aspect.

[0014] The embodiments of the present invention bring the following beneficial effects:

[0015] A control method, device, and server for ship freight provided by an embodiment of the present invention, after acquiring order information in an order pool, use a spatio-temporal clustering model in a preset container consolidation engine to integrally process the map location information, shipping time window, and cargo attributes to dynamically adjust the container consolidation strategy and determine a target container consolidation combination. Finally, through a preset cost analysis model, based on the target container consolidation combination and shipping information, determine the target accounting cost of the logistics corresponding to the target container consolidation combination and feed back the target container consolidation combination and the target accounting cost to the user terminal. The embodiments of the present invention can dynamically adjust the container consolidation strategy by comprehensively considering time and space factors, thereby improving the container consolidation efficiency, and conduct cost analysis in combination with shipping information to intuitively provide accurate freight costs to the user terminal, so as to eliminate freight plans with higher costs and effectively reduce freight costs.

[0016] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification, claims, and drawings.

[0017] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following provides preferred embodiments in conjunction with the accompanying drawings and detailed descriptions are as follows. Description of the Drawings

[0018] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0019] Figure 1 Schematic flowchart of a control method for ship freight provided by an embodiment of the present invention;

[0020] Figure 2 Specific flowchart of a control method for ship freight provided by an embodiment of the present invention;

[0021] Figure 3 Schematic structural diagram of a control device for ship freight provided by an embodiment of the present invention;

[0022] Figure 4 Schematic structural diagram of a server provided by an embodiment of the present invention. Detailed Embodiments

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0024] At present, during the process of ship freight transportation, it is necessary to adjust the cargo packing strategy according to factors such as the size and weight of the cargo. In addition, during the packing process, it is also necessary to consider the shipping time and shipping location of the cargo, so as to avoid placing the goods that arrive first deep in the cargo hold, bringing additional handling costs. Therefore, how to load and transport to obtain the best consolidation efficiency and the optimal freight cost is an extremely complex problem. Related technologies propose that the traditional international logistics system mainly relies on manual experience to match orders and enter customs declaration information. This operation that completely relies on experience is difficult to achieve a unified loading standard, and it is also impossible to comprehensively compare and optimize various consolidation plans, resulting in low consolidation efficiency and high transportation costs. Based on this, the control method, device and server for ship freight provided by the implementation of the present invention can dynamically adjust the consolidation strategy by comprehensively considering time and space factors, thereby improving the consolidation efficiency, and conduct cost analysis in combination with shipping information to intuitively provide accurate freight costs to the user side, so as to eliminate freight plans with higher costs and effectively reduce freight costs.

[0025] See Figure 1 The flow schematic diagram of a control method for ship freight shown in the figure, this method mainly includes the following steps S102 to step S106:

[0026] Step S102, obtain the order information in the order pool. Among them, the order information includes: map location information, shipping time window and cargo attributes. The cargo attributes include: cargo density and cargo center of gravity coordinates. The order information also includes: order density, order transportation requirements and order historical shipping time. In an implementation manner, after obtaining the order information, it is also necessary to standardize the map location information and the shipping time window to convert the map location information into geographic coordinate information and convert the shipping time window into a time series. Further, after standardizing the map location information and the shipping time window, feature extraction processing can be performed on the geographic coordinate information and the time series to extract key features, specifically including: spatio-temporal features: geographical location, shipping time window; goods features: size, weight, temperature layer requirements, dangerous goods grade; constraint conditions: container capacity limit, dangerous goods mixed loading rules, etc.

[0027] Step S104: Use the spatio-temporal clustering model in the preset container consolidation engine to integrate the map location information, shipping time window, and cargo attributes, so as to dynamically adjust the container consolidation strategy and determine the target container consolidation combination. Among them, the spatio-temporal clustering model (ST-CLUSTER) is a clustering algorithm that combines geospatial information and time information. In this invention, this algorithm is used to solve the problems of dynamic matching and container consolidation optimization of logistics orders. In one implementation, the spatio-temporal features can be matched through the spatio-temporal clustering model, so as to quickly identify the orders that can be consolidated, improve the container consolidation efficiency, and optimize the loading rate during the container consolidation process, thereby reducing the gaps between various goods in the container, improving the loading efficiency of the container. At the same time, by reasonably matching the orders, reducing the transportation distance and time can also reduce the logistics cost.

[0028] Step S106: Through the preset cost analysis model, based on the target container consolidation combination and shipping information, determine the target accounting cost of the logistics corresponding to the target container consolidation combination, and feedback the target container consolidation combination and the target accounting cost to the user terminal. Among them, according to the target container consolidation combination, the value of the goods in this voyage can be determined. According to the shipping information and the dynamic fuel coefficient, the shipping cost can be determined, so as to obtain the target accounting cost. In one implementation, for the shipping information, the customs declaration information corresponding to each order can be extracted through the intelligent mapping library in the preset declaration robot model, and the shipping information can be determined according to the customs declaration information. In addition, by accessing the AIS ship positioning system, a cargo transportation trajectory prediction model can be constructed to more accurately predict the freight trajectory.

[0029] The above control method, device, and server method for ship freight provided by the embodiments of the present invention can dynamically adjust the container consolidation strategy by comprehensively considering time and space factors, thereby improving the container consolidation efficiency, and combining shipping information for cost analysis to intuitively provide accurate freight costs to the user terminal, so as to eliminate freight plans with higher costs and effectively reduce the freight cost.

[0030] See Figure 2 The specific process schematic diagram of a control method for ship freight as shown. The embodiments of the present invention also provide an implementation manner for controlling ship freight, specifically as follows (1) to (3):

[0031] (1) Perform spatial clustering processing on the geographic coordinate information to determine the target geographic area division. Specifically, through the preset spatial clustering algorithm (such as DBSCAN or K-Means), based on the geographic coordinate information, the orders are divided into multiple geographic areas, and the division of the geographic areas is dynamically adjusted according to the order density and order transportation requirements to determine the target geographic area division.

[0032] (2) Perform time series clustering on the time series to determine the target time series range. Specifically, through a preset time clustering algorithm (such as DTW or K-Medoids), based on the time series, divide the orders into multiple time series clusters, and dynamically adjust the time series clusters according to the historical shipping time of the orders to determine the target time series range.

[0033] (3) Through a preset non-dominated sorting genetic algorithm, perform multi-objective optimization on the original container consolidation strategy based on the target geographical area division, target time series range, and cargo attributes to determine the target container consolidation combination. Among them, the preset non-dominated sorting genetic algorithm (NSGA-III) performs multi-objective optimization on the container consolidation plan. Specifically, the optimization objectives include: maximizing the loading rate, minimizing the transportation cost (i.e., reducing the transportation distance and time), and time window constraint (to ensure that the orders are consolidated within the specified time window). In addition, constraint conditions such as dangerous goods mixing rules and temperature layer matching rules can be added during the optimization process to improve the optimization effect.

[0034] In one implementation, it is also necessary to automatically detect the compliance of the container loading of the target container consolidation combination based on the cargo density and the cargo center of gravity coordinates through a preset 3D loading simulation engine. When the detection is qualified, calculate the physical cost of the target container consolidation combination. Among them, the 3D loading simulation engine (3D-LOAD) is used to combine the cargo density and the center of gravity coordinates, and integrate the AI image recognition algorithm to automatically detect the compliance of the container loading. In addition, the warning ability of dangerous goods mixing can be improved by introducing a dangerous goods knowledge graph.

[0035] In summary, the present invention can dynamically adjust the container consolidation strategy by comprehensively considering time and space factors, thereby improving the container consolidation efficiency, and combining shipping information for cost analysis to intuitively provide accurate freight costs to the user side, so as to eliminate freight plans with higher costs and effectively reduce the freight cost.

[0036] For the ship freight control method provided in the foregoing embodiment, the present invention embodiment provides a ship freight control device. Refer to Figure 3 the structural schematic diagram of a ship freight control device shown, and the device includes the following parts:

[0037] An information acquisition module 302 acquires order information in the order pool. Among them, the order information includes: map location information, shipping time window, and cargo attributes. The cargo attributes include: cargo density and cargo center of gravity coordinates;

[0038] The consolidated container module 304 uses the spatio-temporal clustering model in the preset consolidated container engine to integrate and process the map location information, shipping time window, and cargo attributes, so as to dynamically adjust the consolidated container strategy and determine the target consolidated container combination.

[0039] The cost analysis module 306 uses the preset cost analysis model to determine the target accounting cost of the logistics corresponding to the target consolidated container combination based on the target consolidated container combination and shipping information, and feeds back the target consolidated container combination and the target accounting cost to the user terminal.

[0040] The above-mentioned control device for ship freight provided by the embodiments of the present application can significantly improve the consolidated container efficiency of freight and reduce the freight cost.

[0041] In one implementation, before the step of using the spatio-temporal clustering model in the preset consolidated container engine to integrate and process the map location information, shipping time window, and cargo attributes, so as to dynamically adjust the consolidated container strategy and determine the target consolidated container combination, the above-mentioned consolidated container module 304 is further configured to: standardize the map location information and the shipping time window to convert the map location information into geographic coordinate information and convert the shipping time window into a time series.

[0042] In one implementation, when performing the step of using the spatio-temporal clustering model in the preset consolidated container engine to integrate and process the map location information, shipping time window, and cargo attributes, so as to dynamically adjust the consolidated container strategy and determine the target consolidated container combination, the above-mentioned consolidated container module 304 is further configured to: perform spatial clustering processing on the geographic coordinate information to determine the target geographic area division, and perform time series clustering processing on the time series to determine the target time series range; use the preset non-dominated sorting genetic algorithm to perform multi-objective optimization processing on the original consolidated container strategy based on the target geographic area division, the target time series range, and the cargo attributes to determine the target consolidated container combination.

[0043] In one implementation, the order information further includes: order density and order transportation demand. When performing the step of performing spatial clustering processing on the geographic coordinate information to determine the target geographic area division, the above-mentioned consolidated container module 304 is further configured to: divide the orders into multiple geographic areas based on the geographic coordinate information through the preset spatial clustering algorithm; dynamically adjust the division of the geographic areas according to the order density and order transportation demand to determine the target geographic area division.

[0044] In one implementation, the order information further includes: the historical shipment time of the order. When performing the step of performing time series clustering processing on the time series to determine the target time series range, the above-mentioned consolidation combination module 304 is further configured to: divide the orders into multiple time series clusters based on the time series through a preset time clustering algorithm; perform dynamic adjustment processing on the time series clusters according to the historical shipment time of the orders to determine the target time series range.

[0045] In one implementation, after performing the step of determining the target consolidation combination, the above-mentioned cost analysis module 306 is further configured to: automatically detect the compliance of the container loading of the target consolidation combination based on the cargo density and the cargo center of gravity coordinates through a preset three-dimensional loading simulation engine, and calculate the physical cost of the target consolidation combination when the detection is qualified.

[0046] In one implementation, before performing the step of determining the target accounting cost of the logistics corresponding to the target consolidation combination based on the target consolidation combination and the shipping information through a preset cost analysis model and feeding back the target consolidation combination and the target accounting cost to the user terminal, the above-mentioned cost analysis module 306 is further configured to: extract the customs declaration information corresponding to each order through the intelligent mapping library in the preset declaration robot model, and determine the shipping information according to the customs declaration information.

[0047] The device provided by the embodiments of the present invention has the same implementation principle and the same technical effects as those of the foregoing method embodiments. For the sake of brief description, for the parts not mentioned in the device embodiments, reference may be made to the corresponding content in the foregoing method embodiments.

[0048] The embodiments of the present invention provide a server. Specifically, the server includes a processor and a storage device; a computer program is stored on the storage device, and the computer program executes the method according to any one of the above-mentioned implementations when being run by the processor.

[0049] Figure 4 FIG. is a schematic structural diagram of a server provided by an embodiment of the present invention. The server 100 includes: a processor 40, a memory 41, a bus 42, and a communication interface 43. The processor 40, the communication interface 43, and the memory 41 are connected through the bus 42; the processor 40 is configured to execute an executable module stored in the memory 41, such as a computer program.

[0050] Among them, the memory 41 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 43 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used.

[0051] The bus 42 can be an ISA bus, a PCI bus, an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 4 only a bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0052] Among them, the memory 41 is used to store a program. After receiving an execution instruction, the processor 40 executes the program. The method executed by the device defined by the flow process disclosed in any one of the foregoing embodiments of the present invention can be applied to the processor 40 or implemented by the processor 40.

[0053] The processor 40 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor 40 or the instructions in the form of software. The above-mentioned processor 40 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory 41, and the processor 40 reads the information in the memory 41 and combines its hardware to complete the steps of the above method.

[0054] The computer program product of the readable storage medium provided by the embodiments of the present invention includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the method described in the foregoing method embodiments. For the specific implementation, reference can be made to the foregoing method embodiments and will not be elaborated herein.

[0055] If the above-mentioned functions are realized in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0056] Finally, it should be noted that the above-mentioned embodiments are only specific implementation manners of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions recorded in the foregoing embodiments or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes, or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention and should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A control method for ship freight, characterized in that, The method includes: Obtain order information in the order pool, where the order information includes: map location information, shipping time window, and cargo attributes, and the cargo attributes include: cargo density and cargo center-of-gravity coordinates; Utilize the spatio-temporal clustering model in the preset container consolidation engine to integrate and process the map location information, the shipping time window, and the cargo attributes, so as to dynamically adjust the container consolidation strategy and determine the target container consolidation combination; Through the preset cost analysis model, based on the target container consolidation combination and shipping information, determine the target accounting cost of the logistics corresponding to the target container consolidation combination, and feedback the target container consolidation combination and the target accounting cost to the user terminal.

2. The control method for ship freight according to claim 1, wherein, Before the step of utilizing the spatio-temporal clustering model in the preset container consolidation engine to integrate and process the map location information, the shipping time window, and the cargo attributes, so as to dynamically adjust the container consolidation strategy and determine the target container consolidation combination, it includes: By performing normalization processing on the map location information and the shipping time window, convert the map location information into geographic coordinate information, and convert the shipping time window into a time series.

3. The control method for ship freight according to claim 1, characterized in that The step of utilizing the spatio-temporal clustering model in the preset container consolidation engine to integrate and process the map location information, the shipping time window, and the cargo attributes, so as to dynamically adjust the container consolidation strategy and determine the target container consolidation combination, includes: Perform spatial clustering processing on the geographic coordinate information to determine the target geographic area division, and perform time series clustering processing on the time series to determine the target time series range; Through the preset non-dominated sorting genetic algorithm, perform multi-objective optimization processing on the original container consolidation strategy based on the target geographic area division, the target time series range, and the cargo attributes to determine the target container consolidation combination.

4. The control method for ship freight according to claim 3, characterized in that, The order information further includes: order density and order transportation demand, and the step of performing spatial clustering processing on the geographic coordinate information to determine the target geographic area division includes: Based on the geographic coordinate information, divide the orders into multiple geographic areas through a preset spatial clustering algorithm; According to the order density and the order transportation demand, perform dynamic adjustment processing on the division of the geographic areas to determine the target geographic area division.

5. The control method for ship freight according to claim 3, characterized in that The order information further includes: order historical shipping time, and the step of performing time series clustering processing on the time series to determine the target time series range includes: Based on the time series, divide the orders into multiple time series clusters through a preset time clustering algorithm; According to the order historical shipping time, perform dynamic adjustment processing on the time series clusters to determine the target time series range.

6. The control method for ship freight according to claim 1, wherein After the step of determining the target container consolidation combination, it includes: Through the preset three-dimensional loading simulation engine, automatically detect the compliance of the container loading of the target container consolidation combination based on the cargo density and the cargo center-of-gravity coordinates, and when the detection is qualified, calculate the physical cost of the target container consolidation combination.

7. The control method for ship freight according to claim 1, characterized in that, Before the step of determining the target accounting cost of the logistics corresponding to the target consolidated shipment combination based on the target consolidated shipment combination and shipping information through a preset cost analysis model and feeding back the target consolidated shipment combination and the target accounting cost to the client, the following steps are included: Extract the customs declaration information corresponding to each order through the intelligent mapping library in the preset order form robot model, and determine the shipping information according to the customs declaration information.

8. A control device for ship freight, characterized in that, The device includes: An information acquisition module, which acquires order information in an order pool, where the order information includes: map location information, shipping time window, and cargo attributes, and the cargo attributes include: cargo density and cargo center of gravity coordinates; A consolidated shipment combination module, which uses a spatio-temporal clustering model in a preset consolidated shipment engine to integrally process the map location information, the shipping time window, and the cargo attributes, so as to dynamically adjust the consolidated shipment strategy and determine a target consolidated shipment combination; A cost analysis module, which determines the target accounting cost of the logistics corresponding to the target consolidated shipment combination based on the target consolidated shipment combination and shipping information through a preset cost analysis model, and feeds back the target consolidated shipment combination and the target accounting cost to the client.

9. A server, characterized in that, It includes a processor and a memory, and the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer executable instructions, and when the computer executable instructions are called and executed by the processor, the computer executable instructions cause the processor to implement the method according to any one of claims 1 to 7.

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