Intelligent warehouse distribution integrated control method and system

Abstract

The invention relates to an intelligent warehouse distribution integrated control method and system, and relates to the technical field of warehouse logistics, and the method comprises the steps: receiving demand information and a demand position in response to an order signal; the storage number and the corresponding storage information are called; determining a corresponding storage position based on the storage number; calculating the storage position, the demand position, the storage information and the demand information based on a preset multi-dimensional algorithm to obtain a priority value; ranking the priority values according to the size to determine an optimal storage number; and controlling the warehouse corresponding to the optimal storage number to deliver goods according to the demand information and the demand position. The method has the effect of reducing the labor cost.

Description

Technical Field

[0001] This invention relates to the field of warehousing and logistics technology, and in particular to a smart warehousing and distribution integrated control method and system. Background Technology

[0002] Integrated warehousing and distribution is a deep integration of the two major links of warehousing and distribution. It aims to provide customers with a one-stop solution covering the entire process of goods storage, management and shipping through integrated services. This service focuses on the needs of the seller's supply chain and systematically solves many complex operations from goods receiving and storage to final delivery.

[0003] In related technologies, in the traditional warehousing and distribution model, warehousing and distribution are two independent and separate operational links, managed separately by different service providers or different departments within the enterprise.

[0004] Regarding the aforementioned technologies, in the traditional warehousing and distribution model, when an order is placed, the allocation and delivery of goods in the warehouse are usually done manually. This process relies entirely on human experience and a large amount of manual calculation, resulting in slow response, high error rate, and high labor costs. Summary of the Invention

[0005] To reduce labor costs, this invention provides an intelligent integrated warehousing and distribution control method and system.

[0006] In a first aspect, the present invention provides a smart warehousing and distribution integrated control method, which adopts the following technical solution: A smart warehousing and distribution integrated control method includes: Step S1: In response to the order signal, receive demand information and demand location; Step S2: Retrieve the warehouse number and corresponding warehouse information; Step S3: Determine the corresponding warehouse location based on the warehouse number; Step S4: Calculate the priority value based on the preset multi-dimensional algorithm for warehouse location, demand location, warehouse information, and demand information; Step S5: Sort the priority values ​​by size to determine the optimal warehouse number; Step S6: Control the warehouse corresponding to the optimal storage number to ship goods according to the demand information and the demand location.

[0007] By adopting the above technical solution, the system automatically receives demand information and location in response to order signals, then retrieves relevant warehouse numbers and information, and determines the warehouse location. A pre-set multi-dimensional algorithm calculates priority values ​​for key information, thereby determining the optimal warehouse number and ultimately controlling the corresponding warehouse to complete the shipment. This process achieves intelligent and automated integration of warehousing and distribution, significantly reducing reliance on human experience, minimizing human calculation errors, improving response speed and shipping accuracy, effectively reducing labor costs, and enhancing overall warehousing and distribution efficiency.

[0008] Optionally, methods for controlling the warehouse corresponding to the optimal storage number to ship goods according to demand information and demand location include: Step S60: Obtain the optimal storage quantity for the optimal warehouse number; Step S61: Decompose the demand information to obtain the demand quantity; Step S62: When the optimal storage quantity is greater than the demand quantity, control the warehouse corresponding to the optimal storage number to ship goods according to the demand information and demand location; Step S63: When the optimal storage quantity is less than the demand quantity, obtain the suboptimal storage number based on the priority value; Step S64: Obtain the suboptimal storage quantity for the suboptimal storage number; Step S65: When the suboptimal storage quantity exceeds the demand quantity, control the warehouse corresponding to the suboptimal storage number to ship goods according to the demand information and demand location; Step S66: When the suboptimal storage quantity is less than the demand quantity, recalculate the suboptimal storage number based on the priority value until the suboptimal storage quantity is greater than the demand quantity.

[0009] By adopting the above technical solution, after obtaining the optimal storage quantity for the optimal warehouse number and breaking down the demand information to obtain the demand quantity, the system can flexibly select a delivery strategy based on the comparison result between the optimal storage quantity and the demand quantity. When the optimal storage quantity is sufficient, the corresponding warehouse is directly controlled to deliver goods; when the optimal storage quantity is insufficient, the secondary optimal warehouse number is quickly located based on the priority value, and the storage quantity is compared with the demand quantity again to ensure the accuracy of delivery.

[0010] Optionally, another method is included, which controls the warehouse corresponding to the optimal storage number to ship goods according to demand information and demand location. This method includes: Step S67: Define the priority value corresponding to the optimal warehouse number as the optimal priority value; Step S68: When the optimal storage amount is less than the demand amount, obtain the supplementary amount based on the demand amount and the optimal storage amount; Step S69: Generate a first replenishment order signal based on the demand location and replenishment quantity, and re-execute steps S1 to S4 to obtain a priority value, which is defined as the first candidate priority value; Step S70: Based on the storage location and replenishment quantity corresponding to the optimal storage number, a second replenishment order signal is generated, and steps S1 to S4 are re-executed to obtain a priority value, which is defined as the second candidate priority value; Step S71: Calculate the comprehensive priority value based on the first candidate priority value, the second candidate priority value, and the optimal priority value; Step S72: Sort the comprehensive priority value and the priority values ​​other than the best priority value together to obtain the actual warehouse number group, wherein the actual warehouse number group includes at least one warehouse number; Step S73: Control the warehouse corresponding to the actual storage number group to ship goods according to the demand information and demand location.

[0011] By adopting the above technical solution, when the optimal storage capacity cannot meet the demand, this solution defines an optimal priority value and determines the replenishment quantity based on the difference between the demand and the optimal storage capacity. Subsequently, two replenishment order signals are generated according to the demand location and the optimal storage location, respectively, and a first and second candidate priority value are recalculated. By combining these two candidate priority values ​​with the optimal priority value, a comprehensive priority value is obtained, which is then ranked together with other priority values ​​to determine the actual warehouse number group. Finally, these warehouses are controlled to ship goods according to the demand information and demand location, ensuring the timeliness and accuracy of delivery and further improving warehousing and distribution efficiency.

[0012] Optionally, specific methods for controlling the warehouse corresponding to the actual warehouse number group to ship goods according to demand information and demand location include: Step S730: When the first candidate priority value is greater than the second candidate priority value, the storage number corresponding to the first candidate priority value is defined as the first candidate storage number; Step S731: Control the warehouse corresponding to the first candidate storage number to deliver goods according to the demand location and replenishment quantity, and control the warehouse corresponding to the optimal storage number to deliver goods according to the optimal storage quantity and demand location; Step S732: When the first candidate priority value is less than the second candidate priority value, the storage number corresponding to the second candidate priority value is defined as the second candidate storage number; Step S733: Control the warehouse corresponding to the second candidate warehouse number to ship goods according to the warehouse location and replenishment quantity corresponding to the optimal warehouse number; Step S734: When the optimal storage quantity is greater than the demand quantity, control the warehouse corresponding to the actual storage number group to ship goods according to the demand information and demand location.

[0013] By adopting the above technical solution, after determining the actual warehouse number group, the system flexibly selects a delivery strategy based on the relationship between the first and second candidate priority values. When the first candidate priority value is larger, the warehouse number corresponding to the first candidate priority value is set as the first candidate warehouse number, and that warehouse is controlled to deliver goods according to the required location and replenishment quantity. Simultaneously, the warehouse with the optimal warehouse number also delivers goods according to the optimal storage quantity and required location. If the second candidate priority value is larger, the warehouse number corresponding to the second candidate priority value is set as the second candidate warehouse number, and it is controlled to deliver goods according to the storage location and replenishment quantity of the optimal warehouse number. Furthermore, if the optimal storage quantity is already greater than the required quantity, the warehouse corresponding to the actual warehouse number group is directly controlled to deliver goods according to the required information and required location, without additional replenishment. This series of operations ensures the efficiency and accuracy of the delivery process, effectively improving the level of intelligence in integrated warehousing and distribution.

[0014] Optionally, methods for retrieving storage information corresponding to a storage number include: Step S20: Decompose the demand information to obtain the demand delivery time; Step S21: Determine the delivery time based on the warehouse location and the demand location; Step S22: Obtain surplus time based on demand delivery time and distance delivery time; Step S23: Obtain the self-replenishment speed of the warehouse corresponding to the warehouse number; Step S24: Calculate the replenishment amount based on surplus time and self-replenishment rate; Step S25: Obtain the currently stored information corresponding to the warehouse number; Step S26: Update the currently stored information based on the replenishment amount to obtain the storage information.

[0015] By adopting the above technical solution, when retrieving the storage information corresponding to the storage number, the system first breaks down the demand information to clarify the demand delivery time and the distance delivery time. Then, the system obtains the warehouse's self-replenishment speed and spare time to obtain the replenishment amount, and then updates the storage information based on the replenishment amount and the stored information.

[0016] Optionally, it also includes a delivery method for order cancellation, which includes: Step S7: Receive order cancellation signal; Step S8: Upon receiving a cancellation signal, obtain current cargo information, current location, and current information; Step S9: Calculate the recycling priority value based on the preset multi-dimensional algorithm for the warehouse location, current location, current information, and demand information; Step S10: Sort the recycling priority values ​​by size to determine the optimal recycling storage number; Step S11: Recycle the goods corresponding to the current goods information to the warehouse corresponding to the optimal recycling storage number.

[0017] By adopting the above technical solution, upon receiving a cancellation order signal, the system quickly obtains the current cargo information, location, and related status data. Using a pre-set multi-dimensional algorithm, it comprehensively considers the warehouse location, the current location of the cargo, the current information of the cargo, and the original demand information to accurately calculate the recycling priority value. Subsequently, the system sorts these recycling priority values ​​to determine the optimal recycling warehouse number, ensuring that the cargo can be efficiently and accurately recycled to the most suitable warehouse.

[0018] Optionally, it also includes a method for continuing delivery even when a cancellation signal is received, the method comprising: Step S12: Upon receiving a new order signal, receive the new demand information and the location of the new demand; Step S13: Calculate the delivery priority value based on the current location, new demand location, current information, and new demand information using a preset multi-dimensional algorithm; Step S14: Calculate and sort the warehouse location, new demand location, warehouse information, and new demand information according to their size based on a preset multi-dimensional algorithm to obtain a new priority value; Step S15: When the delivery priority value is greater than the new priority value, deliver the goods corresponding to the current goods information according to the new demand information and the new demand location; Step S16: When the delivery priority value is less than the new priority value, control the warehouse corresponding to the new priority value to ship the goods according to the new demand information and the new demand location.

[0019] By adopting the above technical solution, when a cancellation signal is received but a new order signal is received at the same time, the delivery priority value and the new priority value are judged to determine whether the goods of the cancelled order should continue to be delivered, or the goods should be shipped from the warehouse corresponding to the new priority value, so as to ensure maximum benefits.

[0020] Optionally, it also includes an optimization method for controlling the warehouses corresponding to the new priority values ​​to ship goods according to the new demand information and the new demand location, the method including: Step S160: Obtain the new demand based on the new order signal; Step S161: When the new demand is less than the demand, determine the demand difference information based on the new demand and the demand. Step S162: Calculate the new recycling priority value based on the preset multi-dimensional algorithm for the warehouse location, new demand location, new demand information, and demand difference information; Step S163: Sort the new recycling priority values ​​according to their size to determine the new optimal recycling storage number; Step S164: Find the corresponding waste priority value based on the demand difference information; Step S165: When the new recycling priority value is greater than the waste priority value, recycling is carried out based on the storage location corresponding to the new demand location and the new optimal recycling storage number.

[0021] By adopting the above technical solution, during the process of controlling the warehouses corresponding to the new priority values ​​to ship goods according to the new demand information and new demand locations, when the new demand quantity is less than the original demand quantity, the system will further calculate the demand difference information. Subsequently, using a preset multi-dimensional algorithm, comprehensively considering the warehouse location, new demand location, new demand information, and demand difference information, the system accurately calculates the new recycling priority value. The system sorts these new recycling priority values ​​and determines the new optimal recycling warehouse number. At the same time, the system will also look up the corresponding waste priority value based on the demand difference information to evaluate the recycling efficiency. When the new recycling priority value is greater than the waste priority value, the system will control the relevant warehouses to perform recycling operations according to the new demand location and the warehouse location corresponding to the new optimal recycling warehouse number, to ensure the effective utilization of resources and the minimization of costs. This series of optimization measures further improves the intelligence and precision of warehousing and distribution integration.

[0022] Optionally, it also includes a method for predictively updating warehouse information, which includes: Step S27: Obtain the historical flow information corresponding to the current time and warehouse number; Step S28: Analyze historical traffic information based on the current time to obtain the estimated demand; Step S29: Replenish the warehouse based on the projected demand to update the storage information.

[0023] By adopting the above technical solution, and by acquiring historical traffic information corresponding to the current time and warehouse number, in-depth analysis of historical traffic data is performed to predict the expected demand. Based on the predicted demand, the warehouse is replenished to prevent insufficient storage capacity, effectively improving the operational efficiency and stability of the entire warehousing and distribution system.

[0024] Secondly, this invention provides an intelligent integrated warehousing and distribution control system, which adopts the following technical solution: A smart warehousing and distribution integrated control system includes: The acquisition module is used to acquire order signals, demand information, and demand location. A memory for storing the program of the intelligent warehousing and distribution integrated control method described above; The processor loads and executes programs from memory.

[0025] By adopting the above technical solution, the acquisition module can promptly capture order signals and corresponding demand information and location, providing basic data support for subsequent warehousing and distribution operations. The memory is responsible for storing the program of the intelligent warehousing and distribution integrated control method described in detail above. The processor, by loading and executing the program in the memory, can accurately complete a series of complex operations from receiving demand information to determining the shipping warehouse according to predetermined steps and algorithms, ensuring that the entire intelligent warehousing and distribution integrated control system can operate efficiently and stably, realizing the intelligent and automated integration of warehousing and distribution, improving warehousing and distribution efficiency, and reducing labor costs and error rates.

[0026] In summary, the present invention has at least one of the following beneficial technical effects: By automatically calculating warehouse priority values ​​through a preset multi-dimensional algorithm and dynamically determining warehouses based on the ranking results, the entire process of order processing, warehouse scheduling and delivery execution becomes more efficient and accurate. When the optimal warehouse inventory is insufficient, the system can quickly locate the second-best warehouse or intelligently split the order based on the priority value. Combined with the replenishment order signal and comprehensive priority value calculation, it can realize multi-warehouse collaborative delivery, ensuring the timeliness and accuracy of order fulfillment. Upon receiving a cancellation signal, the system can intelligently calculate the recycling priority value and determine the best recycling warehouse. It also supports dynamic route optimization and reallocation of goods in transit based on new order requirements, effectively reducing resource waste and improving the economy and intelligence level of the overall warehousing and distribution system. Attached Figure Description

[0027] Figure 1 This is a flowchart of an integrated intelligent warehousing and distribution control method in an embodiment of this application. Detailed Implementation

[0028] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0029] This invention discloses an integrated intelligent warehousing and distribution control method. (Refer to...) Figure 1 A smart warehousing and distribution integrated control method includes: Step S1: In response to the order signal, receive the demand information and the demand location.

[0030] An order signal refers to a signal initiated by a user through a client or system interface, containing requests related to the purchase and delivery of goods. This signal typically includes key information such as the specific details of the goods the user wishes to purchase, the expected delivery time, and the accurate delivery address. It is acquired by real-time monitoring and capturing order signal data streams transmitted from the client or external systems through a pre-set system interface program. Once an order signal conforming to a preset format and rules is detected, the data reception mechanism is immediately triggered.

[0031] Demand information refers to the specific requirements for goods explicitly stated in a user's order, including but not limited to detailed information such as the type, specifications, quantity, and quality standards of the goods. It is obtained by extracting and organizing data from the received order signal data stream according to data parsing rules.

[0032] Demand location refers to the specific geographical coordinates or detailed address information that the user expects the goods to be delivered to. This is obtained by extracting geolocation-related fields from the order data, such as the shipping address text.

[0033] Step S2: Retrieve the warehouse number and corresponding warehouse information.

[0034] Warehouse number refers to the unique identifier for each warehouse within the integrated warehousing and distribution system, such as Warehouse No. 1, Warehouse No. 2, and Warehouse No. 3. These warehouse numbers are manually assigned by staff and pre-entered into the warehouse information database (a database that centrally stores and manages information about each warehouse within the system).

[0035] Warehouse information refers to the information of the warehouse corresponding to each warehouse number. This information includes detailed details such as the types, specifications, quantities, quality standards, and storage locations of the stored goods. It is obtained by the system quickly retrieving the corresponding warehouse information data from the warehouse information database using the warehouse number index.

[0036] Step S3: Determine the corresponding warehouse location based on the warehouse number.

[0037] Warehouse location refers to the location of the warehouse corresponding to the warehouse number, usually presented as geographical coordinates or a detailed address. The warehouse location is obtained by the system performing a precise query in a pre-stored warehouse information database based on the unique identifier of the warehouse number, thereby obtaining the geographical coordinates or detailed address information of the warehouse closely associated with that warehouse number.

[0038] Step S4: Calculate the priority value based on the preset multi-dimensional algorithm for warehouse location, demand location, warehouse information and demand information.

[0039] A multi-dimensional algorithm is an algorithm that comprehensively considers multiple factors (including path, cost, and timeliness) to calculate a priority value. The multi-dimensional algorithm is obtained by staff through multiple simulations and calculations before being input into the system.

[0040] Priority value is a numerical value calculated using a multi-dimensional algorithm to measure the overall suitability of each warehouse number in meeting the current order requirements. The magnitude of the priority value directly reflects the quality of the corresponding warehouse in terms of storage location, the matching degree between storage information and demand location, and demand information.

[0041] Step S5: Sort the priority values ​​by size to determine the optimal warehouse number.

[0042] The optimal warehouse number is the one that ranks first among all warehouse numbers after being sorted by priority value. This means it has the highest overall suitability and best meets the current order's requirements. It is determined by the system sorting priority values ​​from highest to lowest, and the warehouse number that ranks first is the optimal warehouse number.

[0043] Step S6: Control the warehouse corresponding to the optimal storage number to ship goods according to the demand information and the demand location.

[0044] Among them, the methods for controlling the warehouse corresponding to the optimal warehouse number to ship goods according to demand information and demand location include: Step S60: Obtain the optimal storage quantity for the optimal warehouse number.

[0045] Optimal storage capacity refers to the storage capacity of the warehouse corresponding to the optimal warehouse number. This is obtained by the system retrieving the corresponding warehouse storage capacity data from the warehouse information database based on the optimal warehouse number index.

[0046] Step S61: Decompose the demand information to obtain the demand quantity.

[0047] Demand quantity refers to the quantity of goods that users expect to purchase, as stated in the demand information. It is obtained by the system breaking down and parsing the demand information to extract specific numerical information regarding the demand quantity of goods.

[0048] Step S62: When the optimal storage quantity is greater than the demand quantity, control the warehouse corresponding to the optimal storage number to ship goods according to the demand information and demand location.

[0049] When the optimal storage capacity exceeds the demand, it means that the storage capacity of the warehouse corresponding to the optimal storage number can meet the customer's demand. In this case, the goods can be shipped through the warehouse corresponding to the optimal storage number to meet the customer's demand.

[0050] Step S63: When the optimal storage quantity is less than the demand quantity, obtain the suboptimal storage number based on the priority value.

[0051] The second-best warehouse ID is the warehouse ID that ranks second only to the best warehouse ID in the priority ranking. It represents the most suitable warehouse for shipping, besides the warehouse corresponding to the best warehouse ID. The second-best warehouse ID is obtained by the system sorting the priority values ​​from largest to smallest, and the warehouse ID that ranks second in the priority ranking is the second-best warehouse ID.

[0052] When the optimal storage capacity is less than the demand, it means that the storage capacity of the warehouse corresponding to the optimal storage number is insufficient to meet the customer's demand, and other warehouses need to ship goods to meet the customer's demand.

[0053] Step S64: Obtain the suboptimal storage quantity for the suboptimal storage number.

[0054] The suboptimal storage capacity refers to the storage capacity of the warehouse corresponding to the suboptimal warehouse number. It is obtained by the system retrieving the corresponding warehouse storage capacity data from the warehouse information database based on the suboptimal warehouse number index.

[0055] Step S65: When the suboptimal storage quantity exceeds the demand quantity, control the warehouse corresponding to the suboptimal storage number to ship goods according to the demand information and demand location; When the amount of suboptimal storage exceeds the demand, it means that the storage capacity of the warehouse corresponding to the suboptimal storage number can meet the customer's demand. In this case, the goods can be shipped through the warehouse corresponding to the suboptimal storage number to meet the customer's demand.

[0056] Step S66: When the suboptimal storage quantity is less than the demand quantity, recalculate the suboptimal storage number based on the priority value until the suboptimal storage quantity is greater than the demand quantity.

[0057] When the amount of storage in the second-best warehouse is less than the demand, it means that the storage capacity of the warehouse corresponding to the second-best warehouse number is insufficient to meet the customer's demand. It is necessary to continue searching for the next number in the priority ranking (for example, if the numbers in the priority ranking from largest to smallest are warehouse number 1, warehouse number 2, warehouse number 3, and warehouse number 4, then the optimal warehouse number is warehouse number 1, the first second-best warehouse number found is warehouse number 2, and if the storage capacity of warehouse number 2 is still insufficient to meet the customer's demand, then the next second-best warehouse number found will be warehouse number 3), until the storage capacity of the warehouse corresponding to the second-best warehouse number can meet the customer's demand.

[0058] This also includes another method for controlling the warehouse corresponding to the optimal storage number to ship goods according to demand information and demand location, which includes: Step S67: Define the priority value corresponding to the optimal warehouse number as the optimal priority value.

[0059] The optimal priority value refers to the priority value corresponding to the optimal warehouse number.

[0060] Step S68: When the optimal storage amount is less than the demand amount, obtain the supplementary amount based on the demand amount and the optimal storage amount.

[0061] The replenishment quantity refers to the difference between the demand and the optimal storage quantity. It represents the missing portion between the storage capacity of the warehouse corresponding to the optimal storage number and the customer's demand. It is obtained by subtracting the optimal storage quantity from the demand. For example, if the customer's demand is 100 and the optimal storage quantity is 80, then the replenishment quantity is 100 minus 80, which is 20. Here, 20 is the replenishment quantity (for ease of understanding, the values ​​here and thereafter are represented by pure numbers without units).

[0062] Step S69: Generate a first replenishment order signal based on the demand location and replenishment quantity, and re-execute steps S1 to S4 to obtain a priority value, which is defined as the first candidate priority value.

[0063] The first replenishment order signal is a new order signal generated based on the demand location and replenishment quantity. It is a signal formed with the demand location as the benchmark. If a warehouse number that meets the conditions can be found later, the warehouse corresponding to the warehouse number that meets the conditions will directly ship the goods to the demand location. For example, if the demand location is point A, and the warehouse location corresponding to the optimal warehouse number is point B, then a new warehouse C that meets the requirements will be found, and the goods will be shipped to point A according to the replenishment quantity. The first replenishment order signal is generated by the system combining the specific geographical coordinates or detailed address information of the demand location with the specific value of the replenishment quantity based on the demand location and replenishment quantity, according to the preset order signal generation rules (the order signal generation rules are rules that are integrated and entered into the system by staff based on order information in real life, which can generate order signals based on key information such as demand quantity and demand location).

[0064] The first candidate priority value refers to the priority value calculated for the first replenishment order signal. This priority value reflects the overall suitability of other warehouse numbers in meeting the replenishment order requirements, after considering the replenishment quantity. The calculation method for the first candidate priority value is the same as that for the priority value, both based on a preset multi-dimensional algorithm that comprehensively considers multiple factors such as warehouse location, demand location, warehouse information, and demand information.

[0065] Step S70: Based on the storage location and replenishment quantity corresponding to the optimal storage number, a second replenishment order signal is generated, and steps S1 to S4 are re-executed to obtain a priority value, which is defined as the second candidate priority value.

[0066] The second replenishment order signal is a new order signal generated based on the warehouse location corresponding to the optimal warehouse number and the replenishment quantity. It's a signal formed with the warehouse location corresponding to the optimal warehouse number as the benchmark. If a warehouse number that meets the conditions can be found subsequently, the warehouse corresponding to that warehouse number will ship the goods to the warehouse location corresponding to the optimal warehouse number. After the warehouse corresponding to the optimal warehouse number receives the replenishment quantity, it will then ship the goods. For example, if the demand location is point A, and the warehouse location corresponding to the optimal warehouse number is point B, then a new point C that meets the requirements will be found, and the replenishment quantity will be shipped to the warehouse corresponding to the optimal warehouse number at point B. Then, the warehouse corresponding to the optimal warehouse number at point B will ship the goods to point A.

[0067] The second candidate priority value refers to the priority value calculated for the second replenishment order signal. This priority value reflects the overall suitability of other warehouse numbers in transporting the replenished goods to the warehouse corresponding to the optimal warehouse number, after considering the replenishment quantity. The calculation method for the second candidate priority value is the same as the priority value, both based on a preset multi-dimensional algorithm, comprehensively considering multiple factors such as warehouse location, the warehouse location corresponding to the optimal warehouse number, warehouse information, and replenishment quantity.

[0068] Step S71: Calculate the comprehensive priority value based on the first candidate priority value, the second candidate priority value, and the optimal priority value.

[0069] The overall priority value refers to the priority value calculated by comparing the first and second candidate priority values ​​with the optimal priority value. The overall priority value represents the comprehensive suitability of the entire shipping process. For example, if the overall priority value obtained by combining the first candidate priority value with the optimal priority value is 70, and the overall priority value obtained by combining the second candidate priority value with the optimal priority value is 80, then it means that the shipping method corresponding to the second supplementary order signal is more suitable (such as lower transportation costs or shorter delivery time).

[0070] Step S72: Sort the comprehensive priority value and the priority values ​​other than the best priority value together to obtain the actual warehouse number group, wherein the actual warehouse number group includes at least one warehouse number.

[0071] The actual warehouse number group refers to the warehouse number group that actually ships goods to the requested location. For example, in the above example, if the combined priority value calculated from the first candidate priority value and the best priority value is 70, and the combined priority value calculated from the second candidate priority value and the best priority value is 80, and there are other warehouse number priority values ​​besides the best priority value, such as 60, 50, etc., the system will sort these combined priority values ​​70, 80, and other priority values ​​(60, 50, etc.) in descending order. The resulting warehouse number group corresponds to the first-ranked priority value, 80.

[0072] Step S73: Control the warehouse corresponding to the actual storage number group to ship goods according to the demand information and demand location.

[0073] The specific methods for controlling the warehouses corresponding to actual warehouse number groups to ship goods according to demand information and demand location include: Step S730: When the first candidate priority value is greater than the second candidate priority value, the storage number corresponding to the first candidate priority value is defined as the first candidate storage number.

[0074] When the first priority value is greater than the second priority value, it means that the warehouse number corresponding to the first priority value is more suitable in terms of meeting the replenishment order requirements. Taking the example in step S69, it means that it is more suitable for point C to directly ship the goods to point A based on the replenishment quantity (such as less transportation costs or shorter time).

[0075] Step S731: Control the warehouse corresponding to the first candidate storage number to deliver goods according to the required location and replenishment quantity, and control the warehouse corresponding to the optimal storage number to deliver goods according to the optimal storage quantity and required location.

[0076] Taking step S69 as an example, the warehouse corresponding to the first candidate storage number, i.e., the warehouse at point C, is controlled to deliver goods to the demand location at point A according to the replenishment quantity, and the warehouse corresponding to the optimal storage number located at point B is controlled to deliver goods to the demand location at point A according to the optimal storage quantity.

[0077] Step S732: When the first candidate priority value is less than the second candidate priority value, the storage number corresponding to the second candidate priority value is defined as the second candidate storage number.

[0078] When the first priority value is less than the second priority value, it means that the warehouse number corresponding to the second priority value is more suitable in terms of meeting the replenishment order requirements. Taking the example in step S70, it means that it is more suitable for point C to directly ship to point B according to the replenishment quantity, and then point B to ship to point A according to the demand quantity (such as less transportation costs or shorter time).

[0079] Step S733: Control the warehouse corresponding to the second candidate warehouse number to ship goods according to the warehouse location and replenishment quantity corresponding to the optimal warehouse number.

[0080] Taking step S70 as an example, the warehouse corresponding to the second candidate storage number located at point C is controlled to deliver goods to the storage location corresponding to the optimal storage number located at point B according to the replenishment quantity.

[0081] Step S734: When the optimal storage quantity is greater than the demand quantity, control the warehouse corresponding to the actual storage number group to ship goods according to the demand information and demand location.

[0082] When the optimal storage capacity exceeds the demand, it indicates that the storage capacity of the warehouse corresponding to the actual storage number group can meet the demand. Taking step S70 as an example, the warehouse corresponding to the actual storage number group located at point B is controlled to deliver goods to the demand location located at point A according to the demand.

[0083] The methods for retrieving the storage information corresponding to the storage number include: Step S20: Decompose the demand information to obtain the demand delivery time.

[0084] The required delivery time refers to the specific time when the user needs the goods to be delivered, as stated in the demand information. This is obtained by the system parsing the demand information and extracting the specific requirements regarding delivery time. For example, a user may explicitly request to receive the goods on a specific date and within a specific time period; the system accurately extracts this key information as the required delivery time.

[0085] Step S21: Determine the delivery time based on the warehouse location and the demand location.

[0086] Delivery time refers to the time required to travel from the warehouse location to the desired location. This time is obtained by the system using a built-in map navigation algorithm (which is pre-input into the system after numerous experiments, taking into account various factors such as road congestion, traffic control information, and average driving speeds on different road sections), combined with real-time traffic information, to accurately calculate the time required to reach the desired location from the warehouse location.

[0087] Step S22: Obtain surplus time based on demand delivery time and distance delivery time.

[0088] Surplus time refers to the difference between the demand delivery time and the travel delivery time; it represents the amount of extra time during the actual delivery process. It is obtained by subtracting the travel delivery time from the demand delivery time.

[0089] Step S23: Obtain the self-replenishment speed of the warehouse corresponding to the warehouse number.

[0090] Self-replenishment speed refers to the speed at which goods are replenished in a warehouse (here, replenishment refers to the speed at which each warehouse is replenished by a corresponding production line). The self-replenishment speed is pre-input by staff based on the production speed of the corresponding production line for each warehouse.

[0091] Step S24: Calculate the replenishment amount based on the surplus time and self-replenishment rate.

[0092] The replenishment quantity refers to the amount of goods that a warehouse can increase through self-replenishment during the surplus time, calculated based on surplus time and self-replenishment rate. It is obtained by multiplying the self-replenishment rate by the surplus time.

[0093] Step S25: Obtain the currently stored information corresponding to the warehouse number.

[0094] Stored information refers to the quantity of goods currently stored in the warehouse corresponding to the warehouse number. This information is retrieved by the system from the warehouse information database, based on the warehouse number index, to show the specific quantity of goods currently stored in the corresponding warehouse. This data reflects the warehouse's current inventory status in real time.

[0095] Step S26: Update the currently stored information based on the replenishment amount to obtain the storage information.

[0096] The storage information is updated based on the replenishment amount and the stored information. For example, if the original stored information in the storage information was 80 and the replenishment amount was 20, then the updated storage information will have a storage amount of 100.

[0097] This also includes delivery methods for order cancellations, which include: Step S7: Receive the order cancellation signal.

[0098] A cancellation order signal is an instruction to cancel an order. It is obtained by the system monitoring the user interface in real time or receiving instructions from other relevant systems (such as customer service systems, sales systems, etc.). Once a cancellation order-related operation or instruction is detected, it is immediately converted into a cancellation order signal for subsequent processing.

[0099] Step S8: Upon receiving a cancellation signal, obtain the current cargo information, current location, and current information.

[0100] Current cargo information refers to the specific status information of the goods involved in the order, including the type, quantity, and specifications of the goods. This information is obtained by the system retrieving records associated with the order from the system to accurately retrieve the current cargo information.

[0101] The current location refers to the geographical location of the goods when the order cancellation signal is received. This is obtained by the system reading location information through a built-in positioning device (such as a GPS positioning module).

[0102] Current information refers to comprehensive information about currently cancelled orders, including the type and quantity of goods. It is obtained by the system retrieving and analyzing data related to the order.

[0103] Step S9: Calculate the recycling priority value based on the preset multi-dimensional algorithm for the warehouse location, current location, current information and demand information.

[0104] The recycling priority value is a quantitative assessment indicator of the suitability of warehouses corresponding to various storage numbers for recycling goods in the event of order cancellation. It is calculated by the system using a pre-set multi-dimensional algorithm. This algorithm comprehensively considers the distance between the warehouse location and the current location, the specific details of the current goods (such as whether the goods are easy to recycle, whether special handling is required, etc.), and demand information (such as the original urgency of the demand, etc., which may influence the recycling decision). The higher the recycling priority value, the more suitable the warehouse is for recycling the goods.

[0105] Step S10: Sort the recycling priority values ​​by size to determine the optimal recycling storage number.

[0106] The optimal recycling warehouse number refers to the warehouse number corresponding to the most suitable warehouse for recycling goods from canceled orders. It is obtained by sorting recycling priority values ​​in descending order; the warehouse number corresponding to the highest recycling priority value is the optimal recycling warehouse number.

[0107] Step S11: Recycle the goods corresponding to the current goods information to the warehouse corresponding to the optimal recycling storage number.

[0108] This also includes a method for continuing delivery even after receiving a cancellation signal, the method comprising: Step S12: Upon receiving a new order signal, receive the new demand information and the location of the new demand.

[0109] The new order signal refers to the signal of a newly received order. The acquisition method is the same as that for the order signal in step S1, and will not be repeated here.

[0110] New demand information refers to specific information about goods in new order signals, including but not limited to details such as the type, quantity, specifications, and quality standards of the goods. This information is obtained by the system parsing the new order signal data, accurately extracting these key details, and integrating them into the new demand information.

[0111] The new demand location refers to the delivery location of goods specified by the user in a new order, which is usually a specific geographical coordinate or detailed address. The system obtains the relevant location description from the new order signal and converts it into geographic information data that the system can recognize and process.

[0112] Step S13: Calculate the delivery priority value based on the current location, new demand location, current information and new demand information using a preset multi-dimensional algorithm.

[0113] Delivery priority value refers to a quantitative indicator derived from a comprehensive evaluation of the new order and the current status of the goods when a cancellation signal has been received but there is still a delivery need. The higher the delivery priority value, the more worthwhile the cancelled goods are to be used for delivery to the new order. The calculation method for delivery priority value is the same as that for priority value calculation in step S4, and will not be repeated here.

[0114] Step S14: Calculate the warehouse location, new demand location, warehouse information, and new demand information based on the preset multi-dimensional algorithm, and sort them according to size to obtain a new priority value.

[0115] The new priority value is a numerical value calculated using a multi-dimensional algorithm to measure the overall suitability of each warehouse number in meeting the requirements of new orders. The calculation method for the new priority value is the same as that for the priority value in step S4, and will not be repeated here.

[0116] Step S15: When the delivery priority value is greater than the new priority value, deliver the goods corresponding to the current goods information according to the new demand information and the new demand location.

[0117] When the delivery priority value is greater than the new priority value, it means that it is more appropriate to use the goods of the previously canceled order to ship the new order. Therefore, the goods of the canceled order are delivered according to the new demand information and the new demand location.

[0118] Step S16: When the delivery priority value is less than the new priority value, control the warehouse corresponding to the new priority value to ship the goods according to the new demand information and the new demand location.

[0119] This includes an optimization method for controlling the warehouses corresponding to the new priority values ​​to ship goods according to the new demand information and the new demand location. This method includes: Step S160: Obtain the new demand based on the new order signal.

[0120] New demand refers to the specific quantity of goods required by a user in a new order. It is obtained by the system parsing the new order signal and precisely extracting the explicit requirements regarding the quantity of goods. For example, a user may explicitly request to purchase a certain quantity of a particular product; the system extracts this quantity information as the new demand.

[0121] Step S161: When the new demand is less than the demand, determine the demand difference information based on the new demand and the demand.

[0122] When the new demand is less than the demand, it means that the quantity of goods in the cancelled order is still slightly surplus after meeting the needs of the new order. The difference information refers to the difference between the new demand and the demand, obtained by subtracting the new demand from the demand.

[0123] Step S162: Calculate the new recycling priority value based on the preset multi-dimensional algorithm for the warehouse location, new demand location, new demand information and demand difference information.

[0124] The new recovery priority value is used to measure the appropriateness of recovering the excess quantity of goods from cancelled orders for each warehouse number after meeting the required quantity in a new order. The calculation method for the new recovery priority value is the same as that for the priority value in step S4, and will not be repeated here.

[0125] Step S163: Sort the new recycling priority values ​​by size to determine the new optimal recycling storage number.

[0126] The optimal recycling warehouse number refers to the warehouse number that ranks first among all warehouse numbers after being sorted by the new recycling priority value. This indicates the warehouse number with the highest overall suitability and best meets the current new recycling needs. It is determined by the system sorting the new recycling priority values ​​from largest to smallest, and the warehouse number that ranks first in the sorting is the new optimal recycling warehouse number.

[0127] Step S164: Find the corresponding waste priority value based on the demand difference information.

[0128] Waste priority value refers to the priority value for discarding the excess quantity of goods from a cancelled order after meeting the requirements of a new order. Waste priority values ​​are obtained by having staff pre-calculate the waste priority value corresponding to different quantities of each item, record it in a waste priority value lookup table, and then enter it into the system. The system then looks up the waste priority value in the waste priority value lookup table based on the demand difference information.

[0129] Step S165: When the new recycling priority value is greater than the waste priority value, recycling is carried out based on the storage location corresponding to the new demand location and the new optimal recycling storage number.

[0130] When the new recycling priority value is greater than the waste priority value, it means that the benefit of recycling the excess quantity of goods from the cancelled order after meeting the quantity required in the new order is greater than the benefit of directly discarding it. Therefore, the excess quantity is recycled to the warehouse corresponding to the new optimal recycling warehouse number.

[0131] This also includes a method for predictively updating warehouse information, which includes: Step S27: Obtain the historical flow information corresponding to the current time and warehouse number.

[0132] The current time refers to the specific point in time. The current time is obtained by the system automatically calling the built-in clock module (such as a GPS time clock).

[0133] Historical flow information refers to the records of goods entering and leaving the warehouse corresponding to the warehouse number throughout history, including data such as inbound and outbound flow. It is obtained by the system retrieving goods entry and exit records for the warehouse within a past time period from the warehouse information database based on the warehouse number index, and then processing and analyzing the data.

[0134] Step S28: Analyze historical traffic information based on the current time to obtain the estimated demand.

[0135] Projected demand refers to the quantity of goods that a warehouse may need to meet in the future, predicted based on current time and historical traffic information. This is achieved by the system using a built-in data analysis algorithm (pre-built and input into the system by staff based on extensive historical traffic data, combined with time series analysis and other techniques). Based on the patterns and trends of goods demand in historical traffic information, and combined with the current time, the system predicts the projected demand for the future period.

[0136] Step S29: Replenish the warehouse based on the projected demand to update the storage information.

[0137] Replenish the warehouse according to the expected demand to avoid inventory shortages, and update the warehousing information according to the replenishment amount corresponding to the expected demand.

[0138] Based on the same inventive concept, embodiments of the present invention provide an integrated intelligent warehousing and distribution control system.

[0139] One of the intelligent warehousing and distribution integrated control systems includes: The acquisition module is used to acquire order signals, demand information, and demand location. A memory used to store the program for an integrated intelligent warehousing and distribution control method; The processor loads and executes programs from memory.

[0140] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A smart warehousing and distribution integrated control method, characterized in that, include: Step S1: In response to the order signal, receive demand information and demand location; Step S2: Retrieve the warehouse number and corresponding warehouse information; Step S3: Determine the corresponding warehouse location based on the warehouse number; Step S4: Calculate the priority value based on the preset multi-dimensional algorithm for warehouse location, demand location, warehouse information, and demand information; Step S5: Sort the priority values ​​by size to determine the optimal warehouse number; Step S6: Control the warehouse corresponding to the optimal storage number to ship goods according to the demand information and the demand location.

2. The intelligent warehousing and distribution integrated control method according to claim 1, characterized in that, Methods for controlling the warehouse corresponding to the optimal storage number to ship goods according to demand information and demand location include: Step S60: Obtain the optimal storage quantity for the optimal warehouse number; Step S61: Decompose the demand information to obtain the demand quantity; Step S62: When the optimal storage quantity is greater than the demand quantity, control the warehouse corresponding to the optimal storage number to ship goods according to the demand information and demand location; Step S63: When the optimal storage quantity is less than the demand quantity, obtain the suboptimal storage number based on the priority value; Step S64: Obtain the suboptimal storage quantity for the suboptimal storage number; Step S65: When the suboptimal storage quantity exceeds the demand quantity, control the warehouse corresponding to the suboptimal storage number to ship goods according to the demand information and demand location; Step S66: When the suboptimal storage quantity is less than the demand quantity, recalculate the suboptimal storage number based on the priority value until the suboptimal storage quantity is greater than the demand quantity.

3. The intelligent warehousing and distribution integrated control method according to claim 1, characterized in that, It also includes another method for controlling the warehouse corresponding to the optimal storage number to ship goods according to demand information and demand location, which includes: Step S67: Define the priority value corresponding to the optimal warehouse number as the optimal priority value; Step S68: When the optimal storage amount is less than the demand amount, obtain the supplementary amount based on the demand amount and the optimal storage amount; Step S69: Generate a first replenishment order signal based on the demand location and replenishment quantity, and re-execute steps S1 to S4 to obtain a priority value, which is defined as the first candidate priority value; Step S70: Based on the storage location and replenishment quantity corresponding to the optimal storage number, a second replenishment order signal is generated, and steps S1 to S4 are re-executed to obtain a priority value, which is defined as the second candidate priority value; Step S71: Calculate the comprehensive priority value based on the first and second candidate priority values ​​and the optimal priority value respectively; Step S72: Sort the comprehensive priority value and the priority values ​​other than the best priority value together to obtain the actual warehouse number group, wherein the actual warehouse number group includes at least one warehouse number; Step S73: Control the warehouse corresponding to the actual storage number group to ship goods according to the demand information and demand location.

4. The intelligent warehousing and distribution integrated control method according to claim 3, characterized in that, Specific methods for controlling the warehouse corresponding to the actual warehouse number group to ship goods according to demand information and demand location include: Step S730: When the first candidate priority value is greater than the second candidate priority value, the storage number corresponding to the first candidate priority value is defined as the first candidate storage number; Step S731: Control the warehouse corresponding to the first candidate storage number to deliver goods according to the demand location and replenishment quantity, and control the warehouse corresponding to the optimal storage number to deliver goods according to the optimal storage quantity and demand location; Step S732: When the first candidate priority value is less than the second candidate priority value, the storage number corresponding to the second candidate priority value is defined as the second candidate storage number; Step S733: Control the warehouse corresponding to the second candidate warehouse number to ship goods according to the warehouse location and replenishment quantity corresponding to the optimal warehouse number; Step S734: When the optimal storage quantity is greater than the demand quantity, control the warehouse corresponding to the actual storage number group to ship goods according to the demand information and demand location.

5. The intelligent warehousing and distribution integrated control method according to claim 1, characterized in that, Methods for retrieving warehouse information corresponding to warehouse numbers include: Step S20: Decompose the demand information to obtain the demand delivery time; Step S21: Determine the delivery time based on the warehouse location and the demand location; Step S22: Obtain surplus time based on demand delivery time and distance delivery time; Step S23: Obtain the self-replenishment speed of the warehouse corresponding to the warehouse number; Step S24: Calculate the replenishment amount based on surplus time and self-replenishment rate; Step S25: Obtain the currently stored information corresponding to the warehouse number; Step S26: Update the currently stored information based on the replenishment amount to obtain the storage information.

6. The intelligent warehousing and distribution integrated control method according to claim 1, characterized in that, It also includes delivery methods for order cancellations, which include: Step S7: Receive order cancellation signal; Step S8: Upon receiving a cancellation signal, obtain current cargo information, current location, and current information; Step S9: Calculate the recycling priority value based on the pre-set multi-dimensional algorithm for the warehouse location, current location, current information, and demand information; Step S10: Sort the recycling priority values ​​by size to determine the optimal recycling storage number; Step S11: Recycle the goods corresponding to the current goods information to the warehouse corresponding to the optimal recycling storage number.

7. The intelligent warehousing and distribution integrated control method according to claim 6, characterized in that, It also includes a method for continuing delivery even when an order cancellation signal is received, the method comprising: Step S12: Upon receiving a new order signal, receive the new demand information and the location of the new demand; Step S13: Calculate the delivery priority value based on the current location, new demand location, current information, and new demand information using a preset multi-dimensional algorithm; Step S14: Calculate and sort the warehouse location, new demand location, warehouse information, and new demand information according to their size based on a preset multi-dimensional algorithm to obtain a new priority value; Step S15: When the delivery priority value is greater than the new priority value, deliver the goods corresponding to the current goods information according to the new demand information and the new demand location; Step S16: When the delivery priority value is less than the new priority value, control the warehouse corresponding to the new priority value to ship the goods according to the new demand information and the new demand location.

8. The intelligent warehousing and distribution integrated control method according to claim 7, characterized in that, It also includes an optimization method for controlling the warehouses corresponding to the new priority values ​​to ship goods according to the new demand information and the new demand location. This method includes: Step S160: Obtain the new demand based on the new order signal; Step S161: When the new demand is less than the demand, determine the demand difference information based on the new demand and the demand. Step S162: Calculate the new recycling priority value based on the preset multi-dimensional algorithm for the warehouse location, new demand location, new demand information, and demand difference information; Step S163: Sort the new recycling priority values ​​according to their size to determine the new optimal recycling storage number; Step S164: Find the corresponding waste priority value based on the demand difference information; Step S165: When the new recycling priority value is greater than the waste priority value, recycling is carried out based on the storage location corresponding to the new demand location and the new optimal recycling storage number.

9. The intelligent warehousing and distribution integrated control method according to claim 1, characterized in that, It also includes a method for predicting and updating warehouse information, which includes: Step S27: Obtain the historical flow information corresponding to the current time and warehouse number; Step S28: Analyze historical traffic information based on the current time to obtain the estimated demand; Step S29: Replenish the warehouse based on the projected demand to update the storage information.

10. A smart warehousing and distribution integrated control system, characterized in that, include: The acquisition module is used to acquire order signals, demand information, and demand location. A memory for storing a program of an integrated intelligent warehousing and distribution control method as described in any one of claims 1 to 9; The processor loads and executes programs from memory.

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