Commercial vehicle offline storage warehouse area automatic distribution method and device with commercial vehicle offline storage warehouse area automatic distribution method

Abstract

The invention discloses a commercial vehicle offline storage warehouse area automatic distribution method and a device with the same. The method comprises the steps that attribute information of a target vehicle to be offline is acquired, and the attribute information at least comprises vehicle type information of the target vehicle and the offline number of the target vehicle in a preset period; state information of each warehouse is obtained, and the state information at least comprises distance information between each warehouse and a main engine plant and warehousing quantity constraint information of each warehouse; based on the state information and the attribute information, a vehicle offline strategy set is generated, and the vehicle offline strategy set is at least used for distributing the target vehicle to the corresponding target warehouse for unloading. The technical problem of low logistics efficiency caused by a traditional manual warehouse area distribution mode is solved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle logistics management, and in particular to a method for automatically allocating offline storage areas for commodity vehicles and a device having the same. Background Art

[0002] The production plan is made based on the automobile production of the main engine of the automobile factory, the market demand and the orders of the dealers. After the main engine factory completes the production, the commercial vehicles need to be temporarily stored before being shipped to the destination. Different storage cycles are set according to the different shipping modes and distribution requirements of each main engine factory. Taking a main engine factory we serve as an example, the operation and control personnel will allocate the next day's reverse transportation tasks based on the production plan for the next day and the storage situation of the whole vehicle logistics warehouse, guide the vehicles to enter the designated storage area for temporary storage, and then carry out the shipment operation according to the sales plan.

[0003] Existing technologies mainly rely on manual operations to carry out storage area allocation operations. The main challenges and problems faced are as follows:

[0004] ① The change of warehouse capacity, the number of models flowing into the warehouse every day plus the current inventory, and the number of each model flowing into the warehouse cannot exceed the set maximum number of warehouses, all have an impact on the allocation of warehouse areas. Manual work needs to be done every day to identify the warehouse capacity in order to determine the relevant allocation premise.

[0005] ②Restrictions on warehouse area attributes. The nature of warehouse areas includes self-owned warehouse areas, externally rented warehouse areas, temporary warehouse areas, etc. It is necessary to manually analyze the allocation of each warehouse area. At the same time, the allocation of self-owned warehouse areas and externally rented warehouse areas needs to consider multiple rules and constraints.

[0006] ③ Vehicle type restrictions: Each warehouse area needs to achieve a balance between hot-selling and common models as much as possible. At the same time, the cumulative distribution ratio needs to be considered and analyzed and calculated every day.

[0007] ④ Strong subjectivity: All factors are derived from human "experience" and "feelings", and are allocated based on subjective judgment. And they require manual analysis, and tasks are issued by dedicated personnel to ensure operations.

[0008] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0009] The embodiment of the present invention provides a method for automatically allocating storage areas for offline commodity vehicles and a device having the same, so as to at least solve the technical problem of low logistics efficiency caused by the traditional manual storage area allocation method.

[0010] According to one aspect of an embodiment of the present invention, in order to achieve the above-mentioned purpose, a method for automatically allocating storage areas for commodity vehicle offline storage is provided, comprising: obtaining attribute information of a target vehicle to be offline, wherein the attribute information at least includes target vehicle model information, and the number of target vehicles offline within a preset period; obtaining status information of each warehouse, wherein the status information at least includes distance information between each warehouse and the main engine factory, and storage quantity constraint information of each warehouse; based on the status information and attribute information, generating a vehicle offline strategy set, wherein the vehicle offline strategy set is at least used to allocate the target vehicle to the corresponding target warehouse for transfer.

[0011] Furthermore, based on the status information and attribute information, a vehicle offline strategy set is generated, including: obtaining the vehicle identification, brand code, vehicle model code and offline factory information in the attribute information, wherein the vehicle model information includes the vehicle model code, and the offline factory information includes at least one of the following: factory code, factory name, and factory location information; based on the vehicle identification, brand code, vehicle model code and offline factory information, combined with the offline quantity and status information, a vehicle offline strategy set is generated.

[0012] Furthermore, based on the vehicle identification, brand code, model code and offline factory information, combined with the offline quantity and status information, a vehicle offline strategy set is generated, including: based on the vehicle identification and brand code, determining the popularity of the target vehicle, wherein the popularity includes the average vehicle popularity; based on the vehicle identification, brand code, offline quantity and offline factory information, determining the average inventory period of the target vehicle; based on the popularity, average inventory period and status information, generating a vehicle offline strategy set.

[0013] Furthermore, based on the popularity, average inventory cycle and status information, a vehicle offline strategy set is generated, including: obtaining the warehouse area identification information, warehouse area, standard storage capacity, available storage capacity on the day, warehouse location, warehouse-bound brand and vehicle model information and warehouse area properties in the status information of each warehouse, wherein the warehouse area properties include independent inventory, leased inventory and temporary inventory; based on the popularity, average inventory cycle and warehouse area identification information, warehouse area, standard storage capacity, available storage capacity on the day, warehouse location, warehouse-bound brand and vehicle model information and warehouse area properties, a vehicle offline strategy set is generated.

[0014] Furthermore, based on the popularity, average inventory cycle and status information, a vehicle offline strategy set is generated, including: obtaining the utilization rate of the autonomous inventory within a preset time period, and when it is determined that the utilization rate of the autonomous inventory is lower than a first preset threshold, generating a first strategy in the vehicle offline strategy set, the first strategy being used to preferentially allocate target vehicles to be offline to the autonomous inventory for transfer.

[0015] Furthermore, based on the popularity, average inventory cycle and status information, a vehicle offline strategy set is generated, including: obtaining the popularity level information of the target vehicle to be offline, and obtaining the limit storage location occupancy ratio information of the autonomous inventory in the status information; when it is determined that the limit storage location occupancy ratio information meets the second preset threshold, generating a second strategy of the vehicle offline strategy set based on the level information and the average inventory cycle, wherein the second strategy is used to allocate the target vehicle to the autonomous inventory for transfer; when it is determined that the limit storage location occupancy ratio information does not meet the second preset threshold, generating a third strategy of the vehicle offline strategy set based on the level information and the average inventory cycle, wherein the third strategy is used to allocate the target vehicle with high level information to the autonomous inventory for transfer, and allocate the target vehicle with non-high level information to the rental inventory or temporary inventory.

[0016] Furthermore, based on the status information and attribute information, a vehicle offline strategy set is generated, including: an acquisition module, used to obtain attribute information of the target vehicle to be offline, wherein the attribute information at least includes the target vehicle model information and the number of target vehicles offline within a preset period; a determination module, used to obtain the status information of each warehouse, wherein the status information at least includes the distance information between each warehouse and the main factory, and the storage quantity constraint information of each warehouse; a strategy generation module, based on the status information and attribute information, generates a vehicle offline strategy set, wherein the vehicle offline strategy set is at least used to allocate the target vehicle to the corresponding target warehouse for transfer.

[0017] According to another aspect of an embodiment of the present invention, there is also provided an automatic allocation device for commodity vehicle offline storage area, including an automatic allocation method for commodity vehicle offline storage area, including: obtaining attribute information of a target vehicle to be offline, wherein the attribute information at least includes target vehicle model information, and the number of target vehicles offline within a preset period; obtaining status information of each warehouse, wherein the status information at least includes distance information between each warehouse and the main engine factory, and storage quantity constraint information of each warehouse; based on the status information and attribute information, generating a vehicle offline strategy set, wherein the vehicle offline strategy set is at least used to allocate the target vehicle to a corresponding target warehouse for transfer.

[0018] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0019] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0020] In the embodiment of the present invention, an intelligent algorithm is adopted to achieve the purpose of automatically optimizing the allocation of storage areas after the vehicle is offline by comprehensively analyzing the attribute information of the target vehicle and the status information of each warehouse, thereby achieving the technical effects of improving logistics efficiency, reducing inventory management costs, ensuring the rational use of warehouse resources, and enhancing the flexibility of shipping plans, thereby solving the technical problem of low logistics efficiency caused by traditional manual warehouse allocation methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0022] Figure 1 It is a hardware structure block diagram of a computer terminal of a method for automatically allocating a commodity vehicle offline storage area according to one optional embodiment of the present invention;

[0023] Figure 2 is a flow chart of a method for automatically allocating offline storage areas for commodity vehicles according to one optional embodiment of the present invention;

[0024] Figure 3 It is a structural block diagram of a control device for a method for automatically allocating commodity vehicle offline storage areas according to one embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] According to an embodiment of the present invention, a method embodiment of a method for automatically allocating offline storage areas for commodity vehicles is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0028] The method embodiment can be executed in an electronic device including a memory and a processor in a computer or a similar computing device. For example, the electronic device running on the computer, such as Figure 1 As shown, the electronic device of the computer may include one or more processors 102 (the processor may include but is not limited to a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microprocessor (MCU), a field programmable logic device (FPGA), a neural network processor (NPU), a tensor processing unit (TPU), an artificial intelligence (AI) type processor, etc.) and a memory 104 for storing data. Optionally, the electronic device of the above-mentioned computer may also include a transmission device 106 for communication functions, an input and output device 108, and a display device 110. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the electronic device of the computer. For example, the electronic device of the computer may include more or fewer components than the above structure description, or have a configuration different from the above structure description.

[0029] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the generation method of the large-scale fault auxiliary decision of the distribution network in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the generation method of the large-scale fault auxiliary decision of the distribution network is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0030] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0031] The display device 110 may be, for example, a touch screen type liquid crystal display (LCD) and a touch display (also referred to as a "touch screen" or a "touch display screen"). The liquid crystal display may enable a user to interact with a user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), and a user may interact with the GUI by finger contact and / or gestures on a touch-sensitive surface, wherein the human-computer interaction functions here may optionally include the following interactions: creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital videos, playing digital music and / or web browsing, etc. The executable instructions for executing the above human-computer interaction functions are configured / stored in a computer program product or a readable storage medium executable by one or more processors.

[0032] Figure 2 1 is a flow chart of an embodiment of a method for automatically allocating storage areas for commodity vehicles offline according to the present invention, as shown in FIG. Figure 1 As shown, the method comprises the following steps:

[0033] Step S102, obtaining attribute information of the target vehicle to be taken offline, wherein the attribute information at least includes the model information of the target vehicle and the number of target vehicles taken offline within a preset period;

[0034] Step S104, obtaining status information of each warehouse, wherein the status information at least includes distance information between each warehouse and the OEM, and storage quantity constraint information of each warehouse;

[0035] Step S106, generating a vehicle offline strategy set based on the state information and the attribute information, wherein the vehicle offline strategy set is at least used to allocate the target vehicle to a corresponding target warehouse for transfer.

[0036] Through the above steps S102 to S106, in the embodiment of the present invention, an intelligent algorithm is used to comprehensively analyze the attribute information of the target vehicle and the status information of each warehouse, so as to achieve the purpose of automatically optimizing the allocation of storage areas after the vehicle is offline, thereby achieving the technical effects of improving logistics efficiency, reducing inventory management costs, ensuring the rational use of warehouse resources, and enhancing the flexibility of shipping plans, thereby solving the technical problem of low logistics efficiency caused by traditional manual warehouse allocation methods.

[0037] Optionally, based on the status information and attribute information, a vehicle offline strategy set is generated, including: obtaining the vehicle identification, brand code, vehicle model code and offline factory information in the attribute information, wherein the vehicle model information includes the vehicle model code, and the offline factory information includes at least one of the following: factory code, factory name, factory location information; based on the vehicle identification, brand code, vehicle model code and offline factory information, combined with the offline quantity and status information, a vehicle offline strategy set is generated.

[0038] Specifically, by implementing this optimization strategy, the vehicle allocation logic can be further refined to ensure that vehicles of different brands and models can be optimally allocated based on their characteristics and the geographical location of the warehouse, which will help improve the level of refinement in inventory management and reduce the complexity of logistics caused by mixed vehicle models.

[0039] In a specific embodiment, suppose that on a certain day, a certain automobile company needs to allocate appropriate storage areas for storage of various commercial vehicles off the production line. First, obtain attribute information: target vehicles: Q5, A4, C-BEV, CC, Magotan hybrid, Magotan, A6 and other commercial vehicles. Vehicle identification, brand code, model code and off-line factory information: for example, the Q5 model identification is "Q5", the brand code is "F1", the model code is "Q5123", and the off-line factory information includes the factory code "F1001", the factory name "FAW First Factory", and the factory location information "No. 6820, Dongfeng Street, Qikai District, Changchun City, Jilin Province". Obtain the status information of each warehouse: warehouse code: 365, 364, 36C, 368, 36R, 36E, 36T, 36P, 36L, 363, etc. Distance information between the warehouse and the OEM: for example, the distance between warehouse 365 and FAW First Factory is 5 kilometers, and the distance between warehouse 368 and FAW First Factory is 150 kilometers. Inbound quantity constraint information: For example, the available storage capacity of warehouse 365 on that day is 200 vehicles, the self-owned warehouse nature of warehouse 36R and the available storage capacity on that day is 150 vehicles, and the consecutive days of inbound storage cannot exceed 3 days. The vehicle offline strategy set is generated through the various information obtained above: For the Q5 model, the system obtains its offline quantity of 500 vehicles, and combined with the distance information and available storage capacity constraints, it generates a strategy to allocate 300 Q5 models to warehouse 365.

[0040] Through the above embodiment, the system automatically generates a detailed vehicle offline strategy set by collecting and analyzing the vehicle's attribute information and the warehouse's status information. This strategy set not only takes into account the number of vehicles offline and brand characteristics, but also fully considers the available storage capacity and distance of the warehouse. It can significantly improve the intelligence level and efficiency of warehouse area allocation, reduce manual intervention, and ensure that the logistics management of vehicles before temporary storage and shipment is more orderly and efficient.

[0041] Optionally, based on the vehicle identification, brand code, model code and offline factory information, combined with the offline quantity and status information, a vehicle offline strategy set is generated, including: based on the vehicle identification and brand code, determining the popularity of the target vehicle, wherein the popularity includes the average vehicle popularity; based on the vehicle identification, brand code, offline quantity and offline factory information, determining the average inventory period of the target vehicle; based on the popularity, average inventory period and status information, generating a vehicle offline strategy set.

[0042] The instability and demand fluctuations of popular models in the market are large, which can easily lead to inventory backlogs or out-of-stock risks. Hot-selling models usually require faster turnover and shorter inventory time to meet market demand and improve customer satisfaction. By determining the popularity of vehicles through vehicle identification and brand coding, the warehouse allocation strategy can be dynamically adjusted to ensure that the inventory level of hot-selling models remains at the optimal state, avoiding supply chain disruptions or cost increases caused by improper inventory control.

[0043] In a rapidly changing market environment, accurate analysis of vehicle sales and inventory cycles can help automakers and dealers make faster and more accurate inventory adjustment decisions. For example, when a certain model suddenly becomes popular, the system can automatically adjust the offline strategy, increase the number of models offline, and give priority to warehouses with high inventory turnover rates to meet market demand. At the same time, for models that are not highly popular or are about to be retired, the system can reasonably plan their storage to avoid occupying high-value warehouse locations, optimize inventory structure, and improve overall capital utilization efficiency.

[0044] Optionally, based on the popularity, average inventory cycle and status information, a vehicle offline strategy set is generated, including: obtaining the warehouse identification information, warehouse area, standard storage capacity, available storage capacity on the day, warehouse location, warehouse-bound brand model information and warehouse area nature in the status information of each warehouse, where the warehouse area nature includes independent inventory, rental inventory and temporary inventory; based on the popularity, average inventory cycle and warehouse identification information, warehouse area, standard storage capacity, available storage capacity on the day, warehouse location, warehouse-bound brand model information and warehouse area nature, a vehicle offline strategy set is generated. By carefully analyzing the nature and status of the warehouse area, vehicles and warehouse areas can be matched more accurately, avoiding logistics bottlenecks and cost waste caused by improper allocation of warehouse area resources. For example, when the storage capacity is tight, the system can automatically identify and allocate vehicles to rental inventory or temporary inventory to ensure efficient use of independent inventory while avoiding additional rental costs.

[0045] Specifically, the warehouse identification information is the unique identification code or name of each warehouse or warehouse, which is used to distinguish different warehouses in the system; the warehouse area refers to the actual floor space of the warehouse, in square meters; the standard storage capacity refers to the maximum number of commodity vehicles that the warehouse can store according to its design and physical conditions; the available storage capacity on the day refers to the actual number of commodity vehicles that the warehouse can accept on the same day. It is calculated by subtracting the current inventory quantity and the reserved storage quantity from the standard storage capacity; the warehouse location refers to the geographical location information of the warehouse, including longitude and latitude, specific address, etc.; the warehouse binding brand model information: refers to the information that the warehouse is specifically used to store commodity vehicles of a specific brand or model; the nature of the warehouse area defines the ownership and operation mode of the warehouse area, which is usually divided into autonomous inventory (self-owned warehouse area), leased inventory and temporary inventory. Autonomous inventory is built by the company or controlled for a long time, leased inventory is the use of a third party's warehouse space through a lease agreement, and temporary inventory is a storage point temporarily enabled under specific circumstances. The nature of the warehouse area affects the use cost, management method and allocation rules of the warehouse area. For example: Warehouse 365, the nature of the warehouse area is a self-owned warehouse, with an area of ​​10,000 square meters, a standard storage capacity of 800 vehicles, and a daily available storage capacity of 600 vehicles. The warehouse is located in FAW Logistics Park, Changchun City, Jilin Province, and the bound brand model is the Volkswagen series; Warehouse 36R, the nature of the warehouse area is a self-owned warehouse, with an area of ​​5,000 square meters, a standard storage capacity of 400 vehicles, and a daily available storage capacity of 200 vehicles. The warehouse is located in FAW Logistics Park, and the bound brand model is the Audi series.

[0046] In a specific embodiment, the Q5 model (Audi brand) is obtained, which is hot-selling (average heat value 90) and has an average storage cycle of 2.5 days. For the Q5 model, the number of offline vehicles is 300. Based on the hot-selling degree, average storage cycle and storage area identification information, storage area area, standard storage capacity, available storage capacity on the day, warehouse location, warehouse binding brand model information and storage area nature, the offline vehicles are first allocated to the self-owned storage area 36R. Considering its high heat value and short average storage cycle, it is preferentially allocated to the self-owned storage area, and the current available storage capacity of 36R is 200 vehicles. It is decided to use all the available storage capacity of 36R for the storage of Q5 models, and the remaining 100 vehicles will be allocated according to the availability of storage area 365. If the available storage capacity of 365 is not enough to meet the demand, the remaining storage areas will be automatically selected for allocation. Through this embodiment, a vehicle offline strategy set is automatically generated based on the vehicle's popularity, average inventory cycle, and real-time warehouse status information, which not only improves the efficiency and accuracy of warehouse area allocation, but also ensures the rational use of warehouse area resources and cost control, ultimately achieving the optimization and upgrading of logistics management.

[0047] Optionally, based on the popularity, average inventory cycle and status information, a vehicle offline strategy set is generated, including: obtaining the utilization rate of the autonomous inventory within a preset time period, and generating a first strategy in the vehicle offline strategy set when it is determined that the utilization rate of the autonomous inventory is lower than a first preset threshold, the first strategy is used to preferentially allocate the target vehicle to be offline to the autonomous inventory for transfer. By giving priority to the use of autonomous inventory, this solution can effectively reduce the cost of leasing and temporary inventory, while ensuring the rapid turnover of vehicles and improving the economic benefits of inventory management.

[0048] In a specific embodiment, the utilization rate of the self-owned inventory (365) within a preset time period (one week) is obtained, and the average utilization rate of the self-owned warehouse area (365) within one week is 60%. Assuming that the first preset threshold is set to 70%, the average utilization rate (60%) of the self-owned warehouse area (365) is lower than the first preset threshold (70%), which means that the warehouse 365 has enough space to accept more vehicles, and the current storage capacity utilization rate still has room for improvement. For example, 200 Q5 models are currently offline. Considering the low utilization rate of the self-owned warehouse area 365, it is decided based on the first strategy to give priority to all Q5 models offline vehicles to the 365 warehouse area. By implementing this strategy, the hot-selling models are quickly and efficiently allocated to the self-owned warehouse area, making full use of the warehouse area resources and avoiding the idleness of the self-owned warehouse area.

[0049] Optionally, based on the popularity, average inventory cycle and status information, a vehicle offline strategy set is generated, including: obtaining the popularity level information of the target vehicle to be offline, and obtaining the limit inventory occupancy ratio information of the autonomous inventory in the status information; when it is determined that the limit inventory occupancy ratio information meets the second preset threshold, based on the level information and the average inventory cycle, a second strategy of the vehicle offline strategy set is generated, wherein the second strategy is used to allocate the target vehicle to the autonomous inventory for transfer; when it is determined that the limit inventory occupancy ratio information does not meet the second preset threshold, based on the level information and the average inventory cycle, a third strategy of the vehicle offline strategy set is generated, wherein the third strategy is used to allocate the target vehicle with a high level information to the autonomous inventory for transfer, and allocate the target vehicle with a non-high level information to the rental inventory or temporary inventory. This method can effectively respond to market fluctuations by dynamically adjusting the inventory allocation strategy, ensure the rapid response of high-hot models and the reasonable storage of non-high-hot models, and improve the flexibility and market adaptability of inventory management.

[0050] The maximum storage space occupancy ratio refers to the maximum proportion of commercial vehicles that can be safely and efficiently stored in the storage area within a certain period of time. When the utilization rate of the storage area reaches this ratio, the storage capacity of the storage area is close to saturation.

[0051] Specifically, the popularity level information of the vehicle is determined based on the average value of the vehicle's popularity. If the average value of the vehicle's popularity is greater than 80 points, the popularity level information of the vehicle is high; if the average value of the vehicle's popularity is less than 80 points, it is a non-high-popularity model.

[0052] If the information of the limit storage space occupancy ratio meets the second preset threshold, it means that the storage space utilization and storage capacity of the storage area have reached a relatively ideal balance, the storage area still has enough space to accept new vehicles, and the storage space occupancy will not reach an overcrowded level. If the information of the limit storage space occupancy ratio does not meet the second preset threshold, it means that the storage area is close to full capacity and the storage area space is tight.

[0053] In a specific embodiment, when it is determined that the limit storage location occupancy ratio information meets the second preset threshold, a second strategy of the vehicle offline strategy set is generated based on the level information and the average storage cycle, wherein the second strategy is used to allocate the target vehicle to the autonomous inventory for transfer, that is, when the limit storage location occupancy ratio information (80%) meets the second preset threshold (80%), the target vehicles under all level information (whether high-heat or non-high-heat models) can be allocated to the self-owned storage area for transfer. For example: for the Q5 model (the popularity is high, the average storage cycle is 3 days) and the A4 model (the popularity is non-high-heat, the average storage cycle is 7 days), under the condition that the limit storage location occupancy ratio information meets the second preset threshold, the vehicles of these two models will be directly allocated to the self-owned storage area for storage according to the vehicle offline plan and inventory situation.

[0054] In another specific embodiment, when it is determined that the limit storage space occupancy ratio information (90%) does not meet the second preset threshold (80%), a third strategy of the vehicle offline strategy set is generated based on the level information and the average storage cycle, wherein the third strategy is used to allocate the target vehicle with high level information to the autonomous inventory for transfer, and allocate the target vehicle with non-high level information to the rental inventory or temporary inventory. For example: for the A6 model (the popularity is highly popular, the average storage cycle is 2 days) and the C-BEV model (the popularity is non-high, the average storage cycle is 10 days), the system decides to allocate the A6 model to the self-owned warehouse area first, and use its remaining warehouse space for storage to meet the rapid turnover needs of highly popular models. For the C-BEV model, considering the shortage of warehouse space in the self-owned warehouse area, the system allocates it to the rental warehouse area or temporary warehouse area, which may be far away from the factory, but can provide sufficient storage space to meet the long-term storage needs of non-high-heat models, while avoiding excessive use of the self-owned warehouse area to ensure the stability and flexibility of the logistics network.

[0055] Optionally, based on the status information and attribute information, a vehicle offline strategy set is generated, including: obtaining the warehousing time from the attribute information of the target vehicle to be offline; obtaining the historical allocation deviation information of each warehouse, the limit storage capacity information of each warehouse, and the area ratio information of the independent inventory, leased inventory and temporary inventory in the status information; based on the warehousing time, historical allocation deviation information, limit storage capacity information, and the area ratio information of the independent inventory, leased inventory and temporary inventory, combined with the offline number, a fourth strategy in the vehicle offline strategy set is generated, wherein the fourth strategy is used to transfer the target vehicles to be offline to the target warehouse for allocation.

[0056] The warehousing time refers to the estimated time from when a commodity vehicle rolls off the production line to when it enters the storage area; historical allocation deviation information refers to the difference between the actual number of warehousing and the planned number of warehousing in the past period of time. Analyzing the historical allocation deviation information helps to identify potential problems in warehouse management, optimize allocation strategies, and improve the accuracy of plans and the stability of warehouse operations. The limit storage capacity information refers to the maximum number or proportion of commodity vehicles that can be safely and efficiently stored in the warehouse under certain conditions; the area ratio information reflects the relative scale of warehouses of different natures in the overall warehousing network. By comprehensively analyzing the vehicle's warehousing time and the warehouse's historical allocation deviation, the limit storage capacity information, and the area ratio information of independent inventory, leased inventory, and temporary inventory, this solution can predict and adjust inventory allocation, reduce storage capacity pressure and logistics delays caused by uneven allocation, and improve the foresight and accuracy of inventory management.

[0057] Specifically, taking the A6L model as an example, assuming that 672 A6Ls are planned to roll off the production line. The A6L model takes 3 days to enter the warehouse. The system analyzed the data of the past week and found that the allocation deviation between the owned warehouse area and the leased warehouse area was large. The actual number of warehouses in the owned warehouse area was 10% less than the planned number, while the number of warehouses in the leased warehouse area was 15% more than the plan. At present, the maximum warehouse occupancy ratio of the owned warehouse area is 85%, and the current warehouse occupancy ratio is 80%; the maximum warehouse occupancy ratio of the leased warehouse area is 75%, and the current warehouse occupancy ratio is 70%; the maximum warehouse occupancy ratio of the temporary warehouse area is 90%, and the current warehouse occupancy ratio is 65%. The area ratios of owned inventory, leased inventory and temporary inventory are 0.6:0.3:0.1 respectively. That is, on the premise of ensuring the stability of the warehouse area and avoiding excessive congestion of the warehouse space, vehicles are allocated based on the area ratio of each warehouse area and the current warehouse occupancy ratio. First, according to the area ratio information, most A6L vehicles are allocated to the self-owned warehouse area. At the same time, considering the limit storage capacity and historical allocation deviation, some vehicles will also be allocated to the rental warehouse area with relatively low storage space occupancy and the second largest area ratio. The temporary warehouse area is used as a supplement to receive a small number of vehicles or when other warehouse areas cannot meet the demand. The allocation result is calculated by: the result to be divided = area ratio × vehicle model offline + historical deviation value. The calculation shows that 300 vehicles are allocated to the self-owned warehouse area, 250 vehicles are allocated to the rental warehouse area, and 122 vehicles are allocated to the temporary warehouse area. Through the above steps, a more refined and reasonable allocation of commodity vehicle offline storage areas can be achieved while considering multiple factors, thereby improving the use efficiency of the warehouse area and reducing management deviations.

[0058] It should be further explained that when generating the fourth strategy, the setting that the temporary warehouse cannot be put into storage for more than 3 consecutive days is implemented, and the logic judgment of continuous storage is before the historical allocation deviation information and the limit storage capacity information. Temporary warehouses are often established in specific circumstances to cope with sudden demand or short-term inventory pressure. Their rental costs or use costs are usually higher than those of self-owned warehouses or long-term leased warehouses. Limiting the number of consecutive storage days can avoid the continuous use of high-cost temporary warehouses when it is not necessary, thereby controlling logistics costs.

[0059] Based on the above generated vehicle offline strategy set, the model is established as follows:

[0060] Objective function: Minimize the gap between the warehouse incoming volume and each target incoming volume (including: warehouse incoming volume, long-distance warehouse incoming volume, warehouse hot-selling car dealership incoming volume and the corresponding target incoming volume) and increase the incoming volume of the own warehouse as much as possible:

[0061]

[0062] in:

[0063]

[0064] Storage capacity constraints:

[0065]

[0066] The maximum number of warehouses that can be allocated to each vehicle type is as follows:

[0067]

[0068] Auxiliary variable constraints:

[0069]

[0070] The calculation formula for the total target warehouse inventory is as follows:

[0071]

[0072] Calculation method for target inventory quantity of hot-selling models in warehouse:

[0073]

[0074] In the above formula: W is the set of all warehouses; W N All nearby warehouses are gathered; W F All remote warehouses are collected; W E All external rental warehouses collection; W O All owned warehouses collection; P All car models collection; P h All hot-selling models collection; P C The set of all common car models; warehouse w, w∈W; car model p, p∈P, B P The quantity of vehicle model p to be allocated in the warehouse on the day; D p The target inventory quantity of vehicle type p allocated to the remote warehouse on the day; The cumulative inventory of model p at warehouse w from the start of observation to the previous day; warehouse w is the initial inventory of model p on that day; K is the maximum number of warehouses that can be allocated for the same model; C is the inventory of model p on that day; w Warehouse w capacity; R W The target inventory allocation ratio after warehouse w enters the warehouse, w∈W E ; The target allocation ratio of the inventory of the hot-selling model after the warehouse w enters the warehouse, where w∈W E ; The target inventory quantity of the hot-selling models of warehouse w on that day (calculated based on historical data, target allocation ratio, and total inventory to be received on that day); N w The total target inventory volume of warehouse wv on the day (calculated based on historical data, target allocation ratio, and total volume to be received on the day); α, β, γ, θ objective function weight coefficients; M is an arbitrarily large number; Model p is assigned the incoming quantity of warehouse w; If vehicle type p is assigned to warehouse w, then otherwise: The difference between the total incoming inventory of warehouse w and the target incoming inventory.

[0075] Using the above model to perform operations:

[0076] Current operation process: proceed in the following steps:

[0077] ① Receive the next day's estimated production plan information;

[0078] ②Manually check the vehicle model information;

[0079] ③Manually check the planned vehicle model quantity;

[0080] ④Manually check the ratio of public iron to water;

[0081] ⑤Query the actual inventory situation of each warehouse area;

[0082] ⑥Query the historical storage status of each storage area;

[0083] ⑦ Calculate the distributable ratio;

[0084] ⑧Multiply the number of vehicles by the proportion;

[0085] ⑨Form the allocated quantity.

[0086] Introduce the algorithm operation process: proceed through the following steps in sequence:

[0087] ① Receive the next day's estimated production plan information;

[0088] ②Import algorithm;

[0089] ③ The algorithm automatically calculates based on data on vehicle models, inventory, and historical information;

[0090] ④Form the distribution quantity.

[0091] Figure 3 1 is a structural block diagram of an automatic allocation device for a commodity vehicle offline storage area according to one embodiment of the present invention. Figure 3 As shown, the device comprises:

[0092] The acquisition module 301 is used to acquire the attribute information of the target vehicle to be taken offline, wherein the attribute information at least includes the model information of the target vehicle and the number of target vehicles taken offline within a preset period;

[0093] The determination module 302 is used to obtain the status information of each warehouse, wherein the status information at least includes the distance information between each warehouse and the OEM, and the storage quantity constraint information of each warehouse;

[0094] The strategy generation module 303 generates a vehicle offline strategy set based on the state information and the attribute information, wherein the vehicle offline strategy set is at least used to allocate the target vehicle to the corresponding target warehouse for transfer.

[0095] Optionally, the strategy generation module 303 is also used to obtain the vehicle identification, brand code, model code and offline factory information in the attribute information, wherein the model information includes the model code, and the offline factory information includes at least one of the following: factory code, factory name, factory location information; based on the vehicle identification, brand code, model code and offline factory information, combined with the offline quantity and status information, a vehicle offline strategy set is generated.

[0096] Optionally, the strategy generation module 303 also determines the popularity of the target vehicle based on the vehicle identification and brand code, wherein the popularity includes the average vehicle popularity; determines the average inventory cycle of the target vehicle based on the vehicle identification, brand code, offline number and offline factory information; and generates a vehicle offline strategy set based on the popularity, average inventory cycle and status information.

[0097] Optionally, the strategy generation module 303 is also used to obtain the warehouse area identification information, warehouse area, standard storage capacity, available storage capacity for the day, warehouse location, warehouse-bound brand and vehicle model information and warehouse area properties in the status information of each warehouse, where the warehouse area properties include independent inventory, leased inventory and temporary inventory; based on the popularity, average inventory cycle and warehouse area identification information, warehouse area, standard storage capacity, available storage capacity for the day, warehouse location, warehouse-bound brand and vehicle model information and warehouse area properties, generate a vehicle offline strategy set.

[0098] Optionally, the strategy generation module 303 is also used to obtain the utilization rate of the autonomous inventory within a preset time period. When it is determined that the utilization rate of the autonomous inventory is lower than a first preset threshold, a first strategy in the vehicle offline strategy set is generated. The first strategy is used to preferentially allocate the target vehicles to be offline to the autonomous inventory for transfer.

[0099] Optionally, the strategy generation module 303 is also used to obtain the popularity level information of the target vehicle to be taken offline, and to obtain the extreme storage location occupancy ratio information of the autonomous inventory in the status information; when it is determined that the extreme storage location occupancy ratio information meets the second preset threshold, based on the level information and the average inventory cycle, a second strategy of the vehicle offline strategy set is generated, wherein the second strategy is used to allocate the target vehicle to the autonomous inventory for transfer; when it is determined that the extreme storage location occupancy ratio information does not meet the second preset threshold, based on the level information and the average inventory cycle, a third strategy of the vehicle offline strategy set is generated, wherein the third strategy is used to allocate the target vehicle with high level information to the autonomous inventory for transfer, and allocate the target vehicle with non-high level information to the rental inventory or temporary inventory.

[0100] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0101] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0102] Step S102, obtaining attribute information of the target vehicle to be taken offline, wherein the attribute information at least includes the model information of the target vehicle and the number of target vehicles taken offline within a preset period;

[0103] Step S104, obtaining status information of each warehouse, wherein the status information at least includes distance information between each warehouse and the OEM, and storage quantity constraint information of each warehouse;

[0104] Step S106, generating a vehicle offline strategy set based on the state information and the attribute information, wherein the vehicle offline strategy set is at least used to allocate the target vehicle to a corresponding target warehouse for transfer.

[0105] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0106] Optionally, in this embodiment, the computer program product may be configured as a computer program for executing the following steps:

[0107] Step S102, obtaining attribute information of the target vehicle to be taken offline, wherein the attribute information at least includes the model information of the target vehicle and the number of target vehicles taken offline within a preset period;

[0108] Step S104, obtaining status information of each warehouse, wherein the status information at least includes distance information between each warehouse and the OEM, and storage quantity constraint information of each warehouse;

[0109] Step S106, generating a vehicle offline strategy set based on the state information and the attribute information, wherein the vehicle offline strategy set is at least used to allocate the target vehicle to a corresponding target warehouse for transfer.

[0110] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0111] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0112] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0113] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0114] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it 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 all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0115] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for automatically allocating storage areas for commodity vehicles offline, characterized in that: include: Acquire attribute information of a target vehicle to be taken offline, wherein the attribute information at least includes the model information of the target vehicle and the number of target vehicles taken offline within a preset period; Acquire status information of each warehouse, wherein the status information at least includes distance information between each warehouse and the OEM, and storage quantity constraint information of each warehouse; A vehicle offline strategy set is generated based on the state information and the attribute information, wherein the vehicle offline strategy set is at least used to allocate the target vehicle to a corresponding target warehouse for transfer.

2. The method for automatically allocating storage areas for commodity vehicles offline according to claim 1 is characterized in that: Generating the vehicle offline strategy set based on the state information and the attribute information includes: Acquire the vehicle identification, brand code, model code and offline factory information in the attribute information, wherein the model information includes the model code, and the offline factory information includes at least one of the following: factory code, factory name, and factory location information; The vehicle offline strategy set is generated based on the vehicle identification, the brand code, the vehicle model code and the offline factory information, combined with the offline quantity and the status information.

3. The method for automatically allocating storage areas for commodity vehicles offline according to claim 1, characterized in that: Based on the vehicle identification, the brand code, the vehicle model code and the offline factory information, combined with the offline quantity and the status information, the vehicle offline strategy set is generated, including: Determining the popularity of the target vehicle based on the vehicle identification and the brand code, wherein the popularity includes an average vehicle popularity; Determine the average storage period of the target vehicle based on the vehicle identification, the brand code, the number of vehicles off the production line, and the factory information of the vehicle off the production line; The vehicle offline strategy set is generated based on the popularity, the average inventory cycle and the status information.

4. The method for automatically allocating storage areas for commodity vehicles offline according to claim 3 is characterized in that: Based on the popularity, the average inventory cycle and the status information, the vehicle offline strategy set is generated, including: Obtaining the warehouse identification information, warehouse area, standard storage capacity, available storage capacity on the day, warehouse location, warehouse-bound brand and vehicle model information, and warehouse nature in the status information of each warehouse, wherein the warehouse nature includes self-owned inventory, leased inventory, and temporary inventory; The vehicle offline strategy set is generated based on the popularity, the average inventory cycle and the warehouse area identification information, the warehouse area, the standard storage capacity, the available storage capacity on the day, the warehouse location, the warehouse-bound brand and model information, and the nature of the warehouse area.

5. The method for automatically allocating storage areas for commodity vehicles offline according to claim 4 is characterized in that: Based on the popularity, the average inventory cycle and the status information, the vehicle offline strategy set is generated, including: The utilization rate of the autonomous inventory within a preset time period is obtained, and when it is determined that the utilization rate of the autonomous inventory is lower than a first preset threshold, a first strategy in the vehicle offline strategy set is generated, wherein the first strategy is used to preferentially allocate the target vehicle to be offline to the autonomous inventory for transfer.

6. The method for automatically allocating storage areas for commodity vehicles offline according to claim 4 or 5, characterized in that: Based on the popularity, the average inventory cycle and the status information, the vehicle offline strategy set is generated, including: Obtaining the sales popularity level information of the target vehicle to be taken offline, and obtaining the limit storage space occupancy ratio information of the autonomous inventory in the status information; When it is determined that the limit storage location occupancy ratio information meets a second preset threshold, a second strategy of the vehicle offline strategy set is generated based on the level information and the average storage cycle, wherein the second strategy is used to allocate the target vehicle to the autonomous inventory for transfer; When it is determined that the limit storage location occupancy ratio information does not meet the second preset threshold, a third strategy of the vehicle offline strategy set is generated based on the level information and the average inventory cycle, wherein the third strategy is used to allocate the target vehicles with high-hot level information to the autonomous inventory for transfer, and allocate the target vehicles with non-high-hot level information to the rental inventory or the temporary inventory.

7. The method for automatically allocating storage areas for commodity vehicles offline according to claim 1, characterized in that: Generating the vehicle offline strategy set based on the state information and the attribute information includes: Obtaining the storage time in the attribute information of the target vehicle to be taken offline; Acquire historical allocation deviation information of each of the warehouses, limit storage capacity information of each of the warehouses, and area ratio information of the self-owned inventory, the leased inventory, and the temporary inventory in the status information; Based on the warehousing time, the historical allocation deviation information, the limit storage capacity information, and the area ratio information of the autonomous inventory, the rental inventory and the temporary inventory, combined with the offline quantity, the fourth strategy in the vehicle offline strategy set is generated, wherein the fourth strategy is used to transfer the target vehicle to be offline to the target warehouse for allocation.

8. An automatic distribution device for the storage area of ​​commodity vehicles offline, characterized in that: include: An acquisition module, used to acquire attribute information of a target vehicle to be taken offline, wherein the attribute information at least includes the model information of the target vehicle and the number of target vehicles taken offline within a preset period; A determination module, configured to obtain status information of each warehouse, wherein the status information at least includes distance information between each warehouse and the OEM, and storage quantity constraint information of each warehouse; The strategy generation module generates a vehicle offline strategy set based on the state information and the attribute information, wherein the vehicle offline strategy set is at least used to allocate the target vehicle to a corresponding target warehouse for transfer.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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