Even code layered intelligent modulation method and system based on binary bit operation

Abstract

The invention provides a binary bit operation-based full-code layered intelligent dispatching method and system. The method comprises the following steps of: performing dispatching in response to a selected goods and a plurality of participating shops: performing first cutting on a shop inventory to obtain a plurality of base number units; cutting the remaining inventory again to obtain a plurality of binary units; sorting receivers of all shops; performing priority classification on each binary unit and base number unit to obtain a shipper classification composed of a plurality of shipping units; sequentially matching candidate delivery units for the receiver based on the first operation according to the fact that the target inventory shortage of the receiver is from more to at least; and checking the matching condition of each candidate delivery unit for each receiver based on the second bit operation, extracting the delivery unit with the best matching and the highest priority, and updating the classification of the shipper and the sorting of the receivers. According to the scheme, through splitting, classification and layering processing, efficient inter-shop allocation strategy generation with the uniform code as the target in a complex scene can be realized, and the residual code rate is effectively reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of chain store uniform code allocation, and in particular relates to a uniform code layered intelligent allocation method and system based on binary bit operation. Background Art

[0002] For offline clothing and footwear stores, ensuring a full range of sizes is crucial. When customers visit offline stores to purchase clothing and footwear, they often expect to try them on and choose the right size. Frequently running out of sizes significantly diminishes the customer experience. For stores, a full range of sizes significantly increases sales opportunities. When customers can easily find the size that meets their needs, they are more likely to complete a purchase. Conversely, size shortages can directly lead to the loss of potential customers, especially during peak sales season, when popular styles cannot be sold due to size shortages, which can have a serious impact on store sales.

[0003] For chain stores, the same product can have different sales patterns across different stores. Over time, some stores may run out of stock, while others may experience inventory backlogs. Given the inventory pressures faced by stores with inventory backlogs, inter-store transfers are essential. The core principle of inter-store transfers is to minimize the occurrence of out-of-stock sizes (striving to ensure that the same store is either completely out of stock or has a full range of sizes for the same product). While some transfer software currently exists, these solutions suffer from computational overhead and inability to make timely decisions. Furthermore, they don't effectively address the issue of full-size transfers. Summary of the Invention

[0004] The purpose of the present invention is to provide a binary bit operation-based intelligent modulation method and system for uniform code layering in order to solve the above problems.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions: A binary bit operation-based, hierarchical intelligent allocation method that performs allocations in response to selected goods and a number of participating stores: The inventory of each participating store is divided into several base units according to the set base number; The remaining inventory of each store is divided into binary units again; Sort all stores by target inventory shortage and assign recipients accordingly; Priority classification is performed on each binary unit and base unit to obtain a shipper classification consisting of a number of shipping units with different priorities; According to the target inventory shortage of the recipient, the first-order operation is used to match the candidate delivery units for the recipient in order of highest to lowest, which can satisfy the requirement of consecutive / uniform numbers in the base unit after transfer. Based on the second operation, the matching status of each candidate delivery unit is calculated for each recipient, the delivery unit with the best match and the highest priority is extracted, and the shipper classification and recipient ranking are updated.

[0006] In the above-mentioned binary bit operation-based intelligent adjustment method for uniform code layers, the first bit operation is an “OR” operation; The second bit operation is an "AND" operation or an "XOR" operation; The base number for each store, product, and size is set from 1 to 10.

[0007] In the aforementioned binary bit operation-based tiered intelligent adjustment method, each store is sorted by recipients in such a way that the stores with more target inventory shortages are processed first. The target inventory shortage of each store is the target inventory of the corresponding product in the corresponding store minus the actual inventory; The target inventory is automatically calculated by the system based on one or more store parameters including sales volume, store ranking, inventory balance, days on the market, and days off the market, or is manually designed by the user; The target inventory shall not be less than the set base quantity of each size of the corresponding product in the corresponding store.

[0008] In the above-mentioned binary bit operation-based intelligent adjustment method for the full code layer, each store will be cut out into a base unit, and the base unit is a full code base or a residual code base; Full-size stock means that there is at least one piece of each size of the corresponding product in stock; off-size stock means that at least one size of the corresponding product is out of stock; The binary unit has a corresponding number of pieces of 0 or 1 for each size; The number of binary units that can be cut for each product in each store is max(x1-y1, x2-y2,…, xn-yn, 0), where x is the inventory quantity of the corresponding size of the corresponding product in the corresponding store, y is the set base number of the corresponding size of the corresponding product in the corresponding store, and n is the number of size types.

[0009] In the above-mentioned binary bit operation-based intelligent adjustment method for uniform codes, the priority classification of each binary unit and base unit specifically includes: For products with the same base unit number, the remaining inventory is divided into several binary units and given the first priority for shipment; For products with incomplete base unit codes, the remaining inventory is cut again into several binary units and assigned the second priority for shipment; The base units of the residual codes of unmarked stores are classified as the third priority for issuance.

[0010] In the above-mentioned binary bit operation-based intelligent adjustment method for the full code, the priority classification of each binary unit and the base unit also includes: the base unit of the full code of the unmarked store is classified as the fourth priority for issuance; the base unit of the incomplete code of the marked store is classified as the fifth priority for issuance; The method further includes binarizing each base unit to obtain a base binary unit; the binarization includes setting the number of dimensions whose quantity is non-zero to 1 and keeping the number of dimensions whose quantity is zero to 0; The non-binary base unit in the shipper classification is split into at least two binary shipping units. When the receiver to which the non-binary base unit belongs is successfully matched, the at least two binary shipping units obtained by the split are removed from the shipper classification. The method for matching candidate shipping units for a recipient includes performing an OR operation on the base binary unit and shipping units of at least a first shipping priority, a second shipping priority, and a third shipping priority, and screening the result of the operation for a continuous set size range / all 1s as the candidate shipping unit; The method of extracting the most matching one from the candidate delivery units includes performing an AND / XOR operation on the base binary unit and the candidate delivery unit, and extracting the result with the highest priority that makes the operation result continuously set the size range / all 0 / 1; Updating the shipper classification and receiver sorting specifically includes removing the successfully matched shipping units from the shipper classification and removing the successfully matched receivers from the receiver sorting.

[0011] In the above-mentioned smart allocation method based on binary bit operation and with the same code, before allocation, the stores with the same code base number are removed from the receiver's sorting; If the end conditions are not met after the first round of allocation, multiple rounds of allocation will be carried out.

[0012] In the above-mentioned binary bit operation-based intelligent adjustment method for uniform codes, the method further includes performing a virtual allocation on the successfully matched recipients and shipping units and determining whether the recipients after the virtual allocation fully meet the requirements; If not, the recipient after the virtual transfer will be stacked until the demand is fully met and then removed from the stack; when the recipient has the same code, the demand is considered to be fully met; Receivers that are not successfully matched are placed in the unsuccessful queue; The unsuccessful queue and the demand stack are used as new receiver queues to execute the next round of allocation. The termination condition is that one of the receiver queue or the shipper classification is cleared.

[0013] In the aforementioned binary bit-based, hierarchical intelligent dispatching method, in non-first-round dispatching, an OR operation is performed on the recipient queue and the delivery unit one by one, and the delivery unit that results in more than 1 in the operation is selected as the second candidate delivery unit for the corresponding recipient; When a shipment unit is matched as a second candidate shipment unit for multiple recipients, a continuous XOR operation is performed on the second candidate shipment unit and the multiple recipients. If the operation results are all 0 or 1, it is considered that the second candidate shipment unit is matched with multiple recipients at the same time. The successfully matched shipment unit is removed from the shipment classification, and the successfully matched recipient is removed from the recipient queue; The number of recipients matched simultaneously does not exceed the set value.

[0014] A binary bit operation-based intelligent code adjustment system comprising: A cutting module is used to perform a first cutting of the inventory of each participating store according to a set base number to obtain a number of base units, and to perform a second cutting of the remaining inventory of each store according to a binary number to obtain a number of binary units; The hierarchical module is used to sort the recipients of all stores according to the target inventory shortage, and to prioritize each binary unit and base unit to obtain a shipper classification consisting of several shipping units with different priorities; The combination matching module is used to match candidate delivery units that satisfy the requirement of consecutive / uniform codes for the base unit after transfer, based on the first operation, according to the target inventory shortage of the recipient. Based on the second operation, the matching status of each candidate delivery unit is calculated for each recipient, and the delivery unit with the best match and highest priority is extracted to update the delivery category and recipient ranking. The inventory adjustment module is used to execute transfers and update inventory data based on matching results.

[0015] The advantages of the present invention are: through splitting, classification and layered processing, this solution can realize the efficient generation of inter-store transfer strategies with the goal of uniformity in complex scenarios; This solution is based on binary logic for inventory matching, which only requires the most basic computer operations. It is very simple for computers to process, so the computational complexity is low and the operational performance is strong, allowing users to make quick decisions at any time. The layered and binary matching method proposed in this solution can effectively reduce the incomplete code rate and provide a higher level of complete code guarantee for chain stores. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of the method for intelligently adjusting the code layer based on binary bit operation of the present invention; Figure 2This is the core flow chart of the allocation method of the present invention based on binary bit operation and layered intelligent allocation; Figure 3 This is an example of the removal process after the residual code base of store A and store C is successfully matched in the binary bit operation-based intelligent adjustment method for the uniform code layer of the present invention; Figure 4 This is a block diagram of the module structure of the binary bit operation-based intelligent modulation system for uniform codes.

[0017] Reference numerals: cutting module 1; layering module 2; combination and matching module 3; inventory adjustment module 4. DETAILED DESCRIPTION

[0018] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] Example 1 like Figure 1 and Figure 2 As shown, this solution discloses a method for intelligent allocation based on binary bit operations. After the user selects the product and participating stores and clicks "Execute", allocation is started based on the selected product and several participating stores: The inventory of each participating store is cut for the first time according to the set base number to obtain several base units.

[0020] Each store will be divided into a base number unit. For example, with five participating stores (in practice, more than 10 stores will participate in most cases), each store will have a set base number for each size of each product. This base number can be set by the user or by the system based on certain rules, such as the store's sales capacity for the product, historical sales data, and the popularity of the size. The base number for each size of each product in each store can range from 1 to 10, and for footwear and apparel, the base number is generally 1 to 3.

[0021] After selecting a product and executing it, processing five stores will generate five base number units. Each base number unit contains the store identifier (store name or code, etc.) and the base number of each size of the corresponding product, similar to the following Table 1, where S represents the store identifier and 34 to 40 are shoe sizes: Table 1 If the quantity of a particular size is at least the set base quantity, the value corresponding to that size in the base quantity unit is the set base quantity. Otherwise, the value corresponding to that size in the base quantity unit is the actual quantity. For example, if the set base quantity of a size 38 women's shoe in a store is 1 and the actual inventory is 2, the value corresponding to size 38 in the base quantity unit will be 1. If the actual inventory is 0, the value corresponding to size 38 in the base quantity unit will be 0.

[0022] Therefore, each store's base unit may be either a full-size base or a reduced-size base, depending on the actual situation. A full-size base means that there is at least one item in stock in each size of the corresponding product; a reduced-size base means that at least one size of the corresponding product is out of stock.

[0023] Table 2 In Table 2 above, row S1 is the base of the incomplete code, and row S2 is the base of the complete code.

[0024] The remaining inventory of each store is further divided into binary units to obtain several binary units.

[0025] Binary unit, each size corresponds to a quantity of 0 or 1, similar to the following table 3: Table 3 The number of binary units that can be cut for each product in each store is max(x1-y1, x2-y2,…, xn-yn, 0), where x is the inventory quantity of the corresponding size of the corresponding product in the corresponding store, y is the set base number of the corresponding size of the corresponding product in the corresponding store, and n is the number of size types.

[0026] If a store has no more inventory after the base unit is cut out, no binary unit will be obtained for that store. If a store has other inventory after the base unit is cut out, it will be cut into binary units again. The more inventory a store has left, the more binary units it will obtain. For example, if a store sets the base number for each size of a shoe to be 1, the inventory of sizes 34 to 38 is 3, and the inventory of sizes 39 and 40 is 2, then after removing the base unit, the remaining inventory can be cut into two binary units S1 and S2, similar to the following table 4: Table 4 Next, all stores are sorted into recipients according to the target inventory shortage of the currently selected goods.

[0027] Stores are prioritized by receiving orders based on the number of stores with the highest target inventory shortage. Stores with higher sales have higher target inventory settings, but may have less inventory, resulting in higher target inventory shortages. Stores ranked last in the order of lowest to highest will be ranked first in the order of highest to lowest.

[0028] The target inventory shortage for each store is the target inventory for the corresponding item in that store minus the actual inventory. For example, if the target inventory for a certain item in a store is 20 and the actual inventory is 5, the target inventory shortage is 15.

[0029] Target inventory is automatically calculated by the system based on one or more store parameters, including sales volume, store ranking, remaining inventory, days on market, and days off market, or can be manually set by the user. This is not the core of this solution and will not be limited or elaborated on in detail here.

[0030] Preferably, the target inventory is no less than the sum of the base inventory for each size of the corresponding product. Furthermore, since the sales of each size of each product may vary, each size preferably has a corresponding target inventory. Each store's target inventory for the current product refers to the sum of the target inventory for all sizes of that product.

[0031] Priority classification is performed on each binary unit and base unit to obtain a shipper classification consisting of a number of shipping units with different priorities; the shipping units will be allocated to the receiver according to the priority.

[0032] Prioritization of each binary unit and base unit specifically includes: For products with uniform base unit numbers, the remaining inventory is divided into several binary units and classified as the first priority for shipment. This type of product is called uniform base unit redundancy. Figure 2 Line D2 in the shipper classification, Figure 2 In this example, the base number for each size in each store is 1.

[0033] For products with incomplete base unit codes, the remaining inventory is cut again to obtain several binary units and is classified as the second priority for shipment. This type of product is called incomplete base unit redundancy. Figure 2 Line C1 in the shipper classification.

[0034] The residual code base unit without protection mark is classified as the third priority, which is called residual code base. Figure 2 C2 and E in the shipper classification. Before starting the execution, users can manually set protection for the store. The protected store will be marked, and its base number, regardless of whether it is aligned with the code, will not be called out. Therefore, it will not participate in the shipper classification and will not be matched by the receiver.

[0035] The first priority has the highest sending priority. When multiple shipping units are matched at the same time after two bit operations, the shipping unit with the highest sending priority is selected.

[0036] It should be noted that this method focuses on uniform allocation. When put into use, it can be used alone or in combination with other methods, such as a decision-making algorithm that takes into account factors such as distance, number of packages, and package upper limit to make the final allocation decision. The details are not discussed here.

[0037] Next, according to the target inventory shortage of the recipient, candidate delivery units that satisfy the requirement of making the base units have consecutive codes or uniform codes are matched to the base units of the recipient in order of most to least based on the OR operation.

[0038] like Figure 2 In the example, the order of the five stores ABCDE according to the target inventory shortage is A, B, C, E, and D. When the base number is set to be greater than 1, non-binary values may appear in the base unit. For example, if the base number of a size 37 women's shoe in a store is set to 2 and the inventory is also 2, then the base unit corresponding to the store may be as shown in Table 5. Table 5 In this regard, this solution performs binarization processing on each base unit to obtain a base binary unit. The binarization processing includes setting 1 for the size whose quantity is non-zero and keeping the size whose quantity is zero as 0. The results after binarization processing of the above example in Table 5 are as follows: Table 6 Table 6 Similarly, when a non-binary value appears in the base unit, the non-binary base unit at the shipper classification is split into at least two binary shipping units. Still taking Table 5 as an example, after splitting, the result is: Table 7 Perform OR operations on the base binary unit and the binary units of the first, second, and third priority levels, respectively. The results of the screening operation are continuous size range settings or all 1 results as candidate delivery units. Continuous size range settings of 1 indicate that after merging with the corresponding delivery unit, the recipient can continue to size within the set size range, such as Figure 2 After A and C1 are combined, the result is 11110. All 1s indicate that after combining with the corresponding delivery unit, the receiver can align the code, such as Figure 2 In the example, after B and C2 are combined, the result is 11111. That is, after the OR operation, C1 is matched as the candidate delivery unit of store A, and C2 is matched as the candidate delivery unit of store B.

[0039] In actual applications, there may be multiple delivery units that can meet the needs of the receiving store for the same or consecutive numbers. The logic of this solution to optimize inventory is that after the transfer, the inventory of the relevant goods in each store is either consecutive or not. As a result, some candidate delivery units may be transferred and some may be left. For example, if Figure 2 If A is 11010, then C1 cannot be exhausted after being merged with it, and it is not the best choice at this time.

[0040] In this regard, this solution performs a further AND operation on the candidate delivery units screened out based on the OR operation, and extracts the results that make the operation results continuously set the size range / all 0 and have the highest priority. Figure 2 The results of the AND operation between A and C1, and between B and C2 are both 0, so C1 is considered the best choice for A, and C2 is considered the best choice for B.

[0041] The above method can quickly and efficiently match the receiver with the sender, which can not only meet the receiver's need for continuous codes, but also avoid the situation where the sender's code is adjusted to be incomplete.

[0042] After the above matching is completed, C1 and C2 are exhausted and removed from the shipper classification. Stores A and B are allocated as receivers. Therefore, if the base units of stores A and B are included in the shipper classification, the base units of store A and store B are also removed from the shipper classification. At the same time, stores A and B are removed from the receiver sorting. Since the base units of store C are allocated, they are also removed from the receiver sorting.

[0043] Figure 3 An example of the removal process after the residual code base of store A and store C is successfully matched is given.

[0044] Furthermore, since the allocation purpose of this solution is to allocate with the same code, before executing the allocation, the stores with the same code base number will be removed from the recipient sorting.

[0045] In addition, one round of allocation often cannot meet the code consistency requirement. Therefore, this solution determines the end condition after the first round of allocation. If it is not met, a second round of allocation will be carried out. The end condition is that either the receiving queue or the shipping category is cleared.

[0046] In the first round of allocation, the recipient queue is the recipient ranking. After the first round of allocation, a virtual allocation is performed on the successfully matched recipients and shipping units to determine whether the recipients after the virtual allocation fully meet the demand. If the recipient codes are consistent, it is considered to fully meet the demand.

[0047] If not, at this time, it means that the outgoing side is exhausted, but the incoming side is not yet complete, then the receiver after the virtual allocation will be put into the demand stack as the new receiver to perform the next round of allocation until the demand is fully met and then popped out of the stack.

[0048] Recipients that are not successfully matched are placed in the unsuccessful queue as recipients for the next round of allocation.

[0049] In non-first-round transfers, the receiver queue includes the demand stack and the unsuccessful queue.

[0050] In non-first round allocation, all receivers in the receiver queue are ORed with the shipping units one by one. Assume that there are 8 receivers in the receiver queue and 10 shipping units in the shipper category. Then, these 8 receivers are ORed with the 10 shipping units respectively.

[0051] Shipments with more 1s than the recipient's after the operation are considered second candidate shipments for the corresponding recipient. That is, if a shipment has more 1s than the recipient after the operation, it means that at least one size of the shipment can be allocated to the recipient, and these shipments are considered second candidate shipments for the corresponding recipient.

[0052] When a shipment unit is matched as a second candidate shipment unit for multiple recipients, a series of XOR operations are performed on the second candidate shipment unit and the multiple recipients. If the operation results are all 0 or 1, the second candidate shipment unit is considered to be matched with multiple recipients. If the number of recipients is even, the operation results are all 0, which is considered a successful match. If the number of recipients is odd, the operation results are all 1, which is considered a successful match. For example: If a shipping unit E1 is 1111111, a receiver I1 is 1110000, and a receiver I2 is 0001111, then the shipping unit E1 will be simultaneously used as the second candidate shipping unit for the two receivers I1 and I2. XORing 1111111 with 1110000 will result in 0001111, and XORing 0001111 with 0001111 will result in 0000000. Therefore, E1 is considered to match I1 and I2. E1 will allocate a part to I1 and the other part to I2. Finally, E1 will be cleared.

[0053] If a shipment unit E1 has a value of 1111111, a recipient I1 has a value of 1111000, a recipient I2 has a value of 0011111, and a recipient I3 has a value of 1100111, then shipment unit E1 will be considered as the second shipment unit candidate for both recipients I1, I2, and I3. XORing 1111111 with 1111000 yields 0000111. XORing 0000111 with 0011111 yields 0011000. XORing 0011000 with 1100111 yields 1111111. Therefore, E1 is considered a match for I1, I2, and I3. E1 allocates a portion to I1, a portion to I2, and the remainder to I3. In non-first round allocations, OR operations can be performed out of sequence to determine the corresponding second shipment candidate for each recipient. The XOR operation is performed based on the order of recipients or shippers. The specific order of recipients is determined by those skilled in the art or automatically generated by the system, with the recipient at the top of the list being the preferred order. Shippers are sorted by priority, which is determined by those skilled in the art or automatically generated by the system within the same priority level.

[0054] Each time a match is successful, the successfully matched shipment unit is removed from the shipper's classification. Similarly, if the base unit of the store corresponding to the successfully matched I1, I2, or I3 is still in the shipper's classification, it will be removed from the shipper's classification. The successfully matched receiver is also removed from the receiver queue. If the successfully matched E1 is in the receiver queue, it is also removed from the receiver queue. When subsequent receivers and shipment units are XOR-matched, the removed receivers and shipment units will no longer participate.

[0055] Preferably, the number of recipients matched simultaneously does not exceed a set value, typically 3, to prevent a store from being assigned to too many stores simultaneously. The number of recipients matched simultaneously can be limited to 2 in the second round, 3 in the third round, and so on, until the set number of recipients matched simultaneously is reached or the termination condition is met.

[0056] This solution uses the most primitive bit operations of computers to execute inter-store transfer decisions for the purpose of aligning codes, and can achieve decisions with extremely low residual code rates at an extremely fast speed.

[0057] Example 2 This embodiment is similar to the first embodiment, differing in that, in this embodiment, candidate shipping units that meet the consecutive / uniform size requirements for the base unit are matched sequentially based on the recipient's target inventory shortage, using an OR operation. Subsequently, a further XOR operation is performed on the candidate shipping units selected by the OR operation to extract the result with the highest priority, resulting in a continuous size range or all 1s.

[0058] Example 3 This embodiment is similar to the first or second embodiment, except that the priority classification of binary units and base units in this embodiment also includes: base units with complete codes from unmarked stores are classified as the fourth priority for dispatch; base units with incomplete codes from marked stores are classified as the fifth priority for dispatch. In each round of allocation, the highest priority dispatch unit is matched first.

[0059] The fourth priority and the fifth priority are subjected to bit operation matching calculation at least starting from the second round. Preferably, the fourth priority is subjected to bit operation matching calculation at the third round, and the fifth priority is subjected to bit operation matching calculation at least starting from the fourth round.

[0060] Example 4 This embodiment provides a binary bit operation-based intelligent modulation system. Figure 4 As shown, it includes a cutting module for performing a first cutting of the inventory of each participating store according to a set base number to obtain a number of base units, and performing a second cutting of the remaining inventory of each store according to a binary number to obtain a number of binary units; The hierarchical module 1 is used to sort the recipients of all stores according to the target inventory shortage, and to classify the priorities of the binary units and the base units to obtain a shipper classification consisting of several shipping units with different priorities; Combination matching module 2 is used to match candidate delivery units that meet the requirement of consecutive / uniform codes for the base unit after transfer based on the target inventory shortage of the recipient, from most to least, based on the first operation. Based on the second operation, it calculates the matching status of each candidate delivery unit for each recipient, extracts the delivery unit with the best match and the highest priority, and updates the delivery category and recipient ranking. The inventory adjustment module 3 is used to execute transfers and update inventory data according to the matching results.

[0061] The specific embodiments described herein are merely illustrative of the spirit of the present invention. Persons skilled in the art may make various modifications, additions, or substitutions to the described specific embodiments without departing from the spirit of the present invention or exceeding the scope of the appended claims.

[0062] Although this document frequently uses terms such as cutting module 1, layering module 2, combination and matching module 3, and inventory adjustment module 4, the use of other terms is not excluded. These terms are used solely to more conveniently describe and explain the essence of the present invention; interpreting them as any additional limitations would be contrary to the spirit of the present invention.

Claims

1. A method for intelligent modulation of uniform codes based on binary bit operation, characterized in that: The method performs a transfer in response to the selected item and a number of participating stores: The inventory of each participating store is divided into several base units according to the set base number; The remaining inventory of each store is divided into binary units again; Sort all stores by target inventory shortage and assign recipients accordingly; Priority classification is performed on each binary unit and base unit to obtain a shipper classification consisting of a number of shipping units with different priorities; According to the target inventory shortage of the recipient, the first-order operation is used to match the candidate delivery units for the recipient in order of highest to lowest, which can satisfy the requirement of consecutive / uniform numbers in the base unit after transfer. Based on the second operation, the matching status of each candidate delivery unit is calculated for each recipient, the delivery unit with the best match and the highest priority is extracted, and the shipper classification and recipient ranking are updated.

2. The binary bit operation-based intelligent adjustment method for uniform codes according to claim 1, characterized in that: The first operation is an "OR" operation; The second bit operation is an "AND" operation or an "XOR" operation; The base number for each store, product, and size is set from 1 to 10.

3. The binary bit operation-based intelligent adjustment method for uniform codes according to claim 1, characterized in that: Each store is sorted by recipients in such a way that the store with the greater target inventory shortage will be processed first. The target inventory shortage of each store is the target inventory of the corresponding product in the corresponding store minus the actual inventory; The target inventory is automatically calculated by the system based on one or more store parameters including sales volume, store ranking, inventory balance, days on the market, and days off the market, or is manually designed by the user; The target inventory shall not be less than the set base quantity of each size of the corresponding product in the corresponding store.

4. The method for intelligently adjusting the code layer by layer based on binary bit operation according to claim 1, characterized in that: Each store will be cut out into a base unit, and the base unit is a full-size base or a partial-size base; Full-size stock means that there is at least one piece of each size of the corresponding product in stock; off-size stock means that at least one size of the corresponding product is out of stock; The binary unit has a corresponding number of pieces of 0 or 1 for each size; The number of binary units that can be cut for each product in each store is max(x1-y1, x2-y2,…, xn-yn, 0), where x is the inventory quantity of the corresponding size of the corresponding product in the corresponding store, y is the set base number of the corresponding size of the corresponding product in the corresponding store, and n is the number of size types.

5. The binary bit operation-based intelligent adjustment method for uniform codes according to claim 4, characterized in that: Prioritization of each binary unit and base unit specifically includes: For products with the same base unit number, the remaining inventory is divided into several binary units and given the first priority for shipment; For products with incomplete base unit codes, the remaining inventory is cut again into several binary units and assigned the second priority for shipment; The base units of the residual codes of unmarked stores are classified as the third priority for issuance.

6. The binary bit operation-based intelligent modulation method for uniform codes according to claim 5, characterized in that: Priority classification of each binary unit and base unit also includes: base units with complete codes of unmarked stores are classified as the fourth priority for issuance; base units with incomplete codes of marked stores are classified as the fifth priority for issuance; The method further includes binarizing each base unit to obtain a base binary unit; The binarization process includes setting the number of non-zero dimensions to 1 and keeping the number of zero dimensions to 0. Cut the non-binary base unit at the shipper classification into at least two binary shipping units; The method for matching candidate shipping units for a recipient includes performing an OR operation on the base binary unit and shipping units of at least a first shipping priority, a second shipping priority, and a third shipping priority, and screening the result of the operation for a continuous set size range / all 1s as the candidate shipping unit; The method of extracting the most matching one from the candidate delivery units includes performing an AND / XOR operation on the base binary unit and the candidate delivery unit, and extracting the result with the highest priority that makes the operation result continuously set the size range / all 0 / 1; Updating the shipper classification and receiver sorting specifically includes removing the successfully matched shipping units from the shipper classification and removing the successfully matched receivers from the receiver sorting.

7. The binary bit operation-based intelligent adjustment method for uniform code layers according to claim 6, characterized in that: Before the transfer, remove the stores with the same base number from the recipient's order; If the end conditions are not met after the first round of allocation, multiple rounds of allocation will be carried out.

8. The binary bit operation-based intelligent modulation method for uniform codes according to claim 7, characterized in that: The method further includes performing a virtual transfer on the successfully matched recipient and the shipping unit and determining whether the recipient after the virtual transfer fully meets the demand; If not, the recipient after the virtual transfer will be stacked until the demand is fully met and then removed from the stack; when the recipient has the same code, the demand is considered to be fully met; Receivers that are not successfully matched are placed in the unsuccessful queue; The unsuccessful queue and the demand stack are used as new receiver queues to execute the next round of allocation. The termination condition is that one of the receiver queue or the shipper classification is cleared.

9. The binary bit operation-based intelligent modulation method for uniform codes according to claim 8, characterized in that: In non-first round allocations, perform OR operations on the recipient queues and shipping units one by one, and select the shipping unit that has more than 1 shipping unit after the operation as the second candidate shipping unit for the corresponding recipient; When a shipment unit is matched as a second candidate shipment unit for multiple recipients, a continuous XOR operation is performed on the second candidate shipment unit and the multiple recipients. If the operation results are all 0 or 1, it is considered that the second candidate shipment unit is matched with multiple recipients at the same time. The successfully matched shipment unit is removed from the shipment classification, and the successfully matched recipient is removed from the recipient queue; The number of recipients matched simultaneously does not exceed the set value.

10. A binary bit operation-based intelligent modulation system for uniform code layers, characterized in that: include, A cutting module is used to perform a first cutting of the inventory of each participating store according to a set base number to obtain a number of base units, and to perform a second cutting of the remaining inventory of each store according to a binary number to obtain a number of binary units; The hierarchical module is used to sort the recipients of all stores according to the target inventory shortage, and to prioritize each binary unit and base unit to obtain a shipper classification consisting of several shipping units with different priorities; The combination matching module is used to match candidate delivery units that satisfy the requirement of consecutive / uniform codes for the base unit after transfer, based on the first operation, according to the target inventory shortage of the recipient. Based on the second operation, the matching status of each candidate delivery unit is calculated for each recipient, and the delivery unit with the best match and highest priority is extracted to update the delivery category and recipient ranking. The inventory adjustment module is used to execute transfers and update inventory data based on matching results.

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