WO2023216998A1 - 订单处理方法、装置、电子设备和计算机可读存储介质 - Google Patents

订单处理方法、装置、电子设备和计算机可读存储介质 Download PDF

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WO2023216998A1
WO2023216998A1 PCT/CN2023/092360 CN2023092360W WO2023216998A1 WO 2023216998 A1 WO2023216998 A1 WO 2023216998A1 CN 2023092360 W CN2023092360 W CN 2023092360W WO 2023216998 A1 WO2023216998 A1 WO 2023216998A1
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Prior art keywords
container
order
sku
processable
containers
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PCT/CN2023/092360
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English (en)
French (fr)
Inventor
牛智越
陈伟
魏锡光
韩昊
赵成业
谭文哲
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北京极智嘉科技股份有限公司
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Publication of WO2023216998A1 publication Critical patent/WO2023216998A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
    • G06Q30/0635—Processing of requisition or of purchase orders

Definitions

  • the present disclosure relates to the field of intelligent warehousing technology, and specifically, to an order processing method, an order processing device, an electronic device and a computer-readable storage medium.
  • a mapping relationship between product orders and inventory containers can be established based on the current inventory structure, and multiple containers that hit the product order can be determined based on the mapping relationship, thereby improving the hit rate. and picking efficiency.
  • a greedy algorithm is used to determine multiple containers that hit an item order. For example, in order to minimize the number of containers that are ultimately shipped out of each order, and to minimize the number of containers that are ultimately shipped out of all orders, the container with the largest number of single items can be prioritized based on the number of single items in each order.
  • the first aspect of the present disclosure provides an order processing method, including: first, obtaining information about all processable orders and information about all candidate containers, and setting the initial value of the filtered container set X to an empty set. Then, at least one container is selected from all candidate containers and added to the filtered container set X; where all containers in the filtered container set X satisfy all processable orders. Finally, hit every container that can handle an order among the containers in the filtered container set X.
  • the second aspect of the present disclosure provides an order processing method, including: first, obtaining a processable order set and a candidate container set corresponding to the processable order set; the processable order set includes multiple processable orders, and the candidate container
  • the collection includes multiple candidate containers.
  • multiple candidate containers are filtered to obtain at least one filtered container, and at least one filtered container is added to the filtered container set; wherein at least one filtered container meets the order requirements of the order set that can be processed.
  • a third aspect of the present disclosure provides an order processing device, including: a task information acquisition module, an inventory information acquisition module, an analysis and calculation module, and an output module.
  • the task information acquisition module is used to obtain order task information.
  • the inventory information acquisition module is used to obtain information about containers in the inventory.
  • the analysis and calculation module is used to perform the first and second aspects according to the order task information and container information. Any of the steps of the order processing method to hit the container for each order.
  • the output module is used to output information about the containers hit by each order.
  • a fourth aspect of the present disclosure provides an electronic device including: one or more processors and a memory.
  • the memory is used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement as described in any one of the first aspect and the second aspect. The order processing method described above.
  • a fifth aspect of the present disclosure provides a computer-readable storage medium with a computer program stored thereon.
  • the computer program is executed by a processor, the order processing as described in any one of the first and second aspects is implemented. method.
  • Figure 1 is a schematic diagram of an order processing method provided by some embodiments of the present disclosure.
  • Figure 2 is a schematic diagram of another order processing method provided by some embodiments of the present disclosure.
  • Figure 3 is a schematic diagram of yet another order processing method provided by some embodiments of the present disclosure.
  • Figure 4 is a schematic diagram of an order processing device provided by some embodiments of the present disclosure.
  • Figure 5 is a schematic diagram of an electronic device provided by some embodiments of the present disclosure.
  • a greedy algorithm can be used to prioritize the containers with the largest number of single types.
  • the container also called the container with the largest number of order lines
  • multiple orders cannot be hit together, resulting in a large number of containers required for all goods of multiple orders to be shipped out, and the picking efficiency is low.
  • the present disclosure provides an order processing method, which filters the candidate container set corresponding to the processable order set to limit the range of hit containers to the filtered container set, and then selects the candidate container set from the filtered container set. It can effectively control the range of hit containers (that is, the number of hit containers), reduce the number of containers required to process all goods in multiple orders in the order set, and improve picking efficiency.
  • the order processing method according to the present disclosure includes the following steps:
  • a processable order refers to an order that satisfies various shipping conditions in all orders.
  • the order that can be processed is an order that the inventory can satisfy, or the order that can be processed has a delivery time limit that meets the customer's delivery time limit requirements.
  • the order includes the order line (SKU) "10 bottles of shampoo". If there are less than 10 bottles of shampoo in the current inventory and the order cannot be satisfied, the order is an unprocessable order. If the shampoo in the current inventory is If the quantity of liquid is greater than or equal to 10 bottles and can satisfy the order, the order is a processable order.
  • step S10 orders that cannot be satisfied by existing inventory are eliminated from all orders, and the remaining orders after elimination are regarded as processable orders. In this way, only orders that can be satisfied by the inventory are hit in its container, and orders that cannot be satisfied by the inventory are not processed to avoid wasted work.
  • the SKU (storage unit) set of each container includes a variety of single products.
  • the staff When processing an order, the staff only cares about whether the container has the single products required in the order, that is, whether the SKU of the container is correct for the order. SKU contributes. Therefore, in some examples, in step S10, SKUs that are not needed for all processable orders among the SKUs of all containers are eliminated, and the unnecessary SKUs will be eliminated.
  • the container after the desired SKU is used as a candidate container.
  • the above-mentioned all processable orders may also be referred to as a processable order set, and the processable order set includes all processable orders received within a certain time period.
  • All the above candidate containers may also be called a candidate container set corresponding to the processable order set, and the candidate container set includes multiple candidate containers.
  • the candidate containers do not include empty containers.
  • the containers in the above-mentioned filtering container set A filter container is added to filter container set X.
  • at least one filtering container meets the order requirements that can process the order set.
  • the above-mentioned screening of multiple candidate containers in the candidate container set to obtain at least one screening container, and adding at least one screening container to the screening container set X includes: first, determining each of the multiple candidate containers. The overall satisfaction rate of candidate containers for the set of orders that can be processed. Then, the candidate container with the largest overall satisfaction rate among the plurality of candidate containers is determined as the first filtering container, and the first filtering container is added to the filtering container set X.
  • at least one screening container includes a first screening container.
  • the candidate container set and the processable order set may be updated.
  • the first target SKU information is the SKU information satisfied by the candidate container with the largest overall satisfaction rate among the SKU information that can process the order set.
  • the first target SKU information is the SKU information satisfied by the first filtering container.
  • the next filtering container (eg, the second filtering container) may be determined in the updated candidate container set.
  • an overall satisfaction rate of each candidate container in the updated set of candidate containers for the updated set of processable orders is determined.
  • the candidate container with the largest overall satisfaction rate in the updated candidate container set is determined as the second filtering container, and the second filtering container is added to the filtering container set.
  • at least one screening container includes a second screening container.
  • the candidate container is determined as the third screening container, and the third screening container is added to the screening container Set, sets the updated set of processable orders to the empty set.
  • at least one screening container includes a third screening container.
  • multiple second screening containers can be determined in sequence, until the overall satisfaction rate of the candidate containers in the candidate container set for the updated processable order set is 1,
  • the last filter container eg, the third filter container
  • the above-mentioned first filtering container, the plurality of second filtering containers and the third filtering container can meet the order requirements of the processable order set.
  • FIG. 2 shows another order processing method provided by some embodiments of the present disclosure.
  • the screening process of step S20 will be described in detail below with reference to Figure 2 .
  • step S20 includes the following steps.
  • the SKU of the target order Y is the information of all the goods that need to be shipped out of the warehouse (including the type and quantity of the goods), and all the SKUs of the container set S only include the type of goods to be shipped out of the warehouse. And the quantity can fully meet the delivery needs.
  • the container set S may also be called a candidate container set
  • the target order Y may also be called a processable order set.
  • the above determination of the overall satisfaction rate a of each container in the container set S for the target order Y can also be considered as determining the overall satisfaction rate a of each candidate container in the candidate container set for the processable order set.
  • determining the overall satisfaction rate of each candidate container in the candidate container set for the processable order set includes: determining the first item satisfaction rate of each candidate container for each item in the processable order set; according to the first order
  • the product satisfaction rate determines the overall satisfaction rate of each candidate container for the set of orders that can be processed.
  • step S22 the overall satisfaction rate a is calculated according to the following formula (1):
  • a is the overall satisfaction rate
  • n is the number of types of all SKU single products in the target order Y
  • c p is the response of a container in the container set S to the p-th single product in the target order Y first item satisfaction rate.
  • the first single-product satisfaction rate c p is 1; when the SKU of the container cannot satisfy the quantity of the p-th single product, the first single-product satisfaction rate c p is 1.
  • the single product satisfaction rate c p is the ratio of the quantity of the SKU of the container corresponding to the p-th single product to the quantity of the SKU of the target order Y corresponding to the p-th single product.
  • c p can also be calculated by the following formula (2):
  • v p is the quantity of the SKU of the container corresponding to the p-th single product
  • t p is the quantity of the SKU of the target order Y corresponding to the p-th single product.
  • the target order Y includes two order lines (SKUs) "10 bottles of shampoo” and “4 pieces of soap”, and the SKU of a container in the container set S includes “12 bottles of shampoo” and “2 pieces of soap.” Soap” (two SKUs).
  • the number n of single products including shampoo and soap that is, all SKUs in the target order Y, is 2.
  • the overall satisfaction rate a of each container in the container set S for the target order Y is calculated in turn, and the container j with the largest overall satisfaction rate a is added to the filtered container set X.
  • container j will be able to meet the demand for shipped items to the greatest extent in terms of quantity of single items.
  • the first single product satisfaction rate c p of each single product is calculated only for the single products included in the target order Y, and the first single product satisfaction rate c p for each single product is only included in the container but not in the target order Y.
  • the first item satisfaction rate For example, if the items contained in the target order Y are shampoo and soap, and the items contained in the container are shampoo, soap, and body soap, then the first order can be calculated only for the two items, shampoo and soap.
  • the product satisfaction rate is calculated instead of the first item satisfaction rate for shower gel.
  • step S10 if the SKUs in all containers that are not required for all processable orders have been eliminated in step S10, it will not happen here that there are more item types in the container than in the target order Y. Single type situation.
  • container j can meet the demand for shipped items to the greatest extent, it is added to the filtered container set X. Since container j cannot fully meet the shipping needs, it is necessary to continue screening containers from the remaining containers to make up for the order SKUs that container j cannot satisfy.
  • step S23 reconfigures the order's requirements and candidate containers for a new round of screening.
  • the target order Y in this round includes the order lines (SKUs) "10 bottles of shampoo” and "4 pieces of soap”.
  • the SKU of container j with the highest overall satisfaction rate a includes “4 bottles of shampoo” and "5 pieces of soap.””Soap”
  • the SKU details of container j that meets the target order Y are "4 bottles of shampoo” and "4 pieces of soap”
  • the SKU of the target order Y becomes "6 bottles of shampoo”
  • container j will no longer participate in the screening or the SKU of container j will be changed to "1 soap”.
  • SKU order line, order details, storage unit
  • SKU includes two dimensions, the name dimension (single product name) and the quantity dimension (single product quantity).
  • removing the detailed information of the SKUs satisfied by the SKU of container j from the SKU of the target order Y means adjusting the quantity dimension of the SKUs in the target order Y, that is, the detailed information at least includes the quantity of the single product.
  • Quantity subtract the satisfied quantity from the original quantity (subtract the quantity of the corresponding SKU in the container from the quantity of the current SKU of the target order Y). When the adjusted quantity is 0, the SKU can be eliminated as a whole.
  • Removing the SKU details that satisfy the target order Y from the SKU in container j also means adjusting the quantity dimension of the SKU in container j, that is, the detailed information at least includes the quantity of the single product, and the original quantity is subtracted from the matched (satisfied) Quantity (use the current SKU quantity of container j minus the quantity of SKU that meets the target order Y).
  • step S30 When the target order Y is an empty set, subsequent steps (eg step S30) are executed, and when the target order Y is not an empty set, step S22 is executed.
  • step S23 the SKUs in the target order Y will continue to be satisfied and thus decrease until the target order Y becomes an empty set.
  • the target order Y is an empty set, it means that all SKUs of all processable orders have been satisfied by the set of containers with the largest overall satisfaction rate a selected in step S22, that is, by the filtered container set X.
  • filtering all containers in the container set X can meet the shipping needs of all processable orders. Therefore, in the next step S30, it is only necessary to hit a container for each container in all processable orders among all containers in the filtered container set X.
  • the overall satisfaction rate a of the last candidate container that enters the filtered container set Therefore, in step S22, for example, when the overall satisfaction rate a of a container for target order Y is 1 (indicating that all required containers have been found), the container is added to the filtered container set X, and then directly set The target order Y is an empty set.
  • This approach is equivalent to no longer executing step S23 and step S24, but directly executing step S30, which reduces the amount of calculation to a certain extent.
  • step S22 when the overall satisfaction rate a of a container for the target order Y is 1, the container is added to the filtered container set X and step S30 is directly executed.
  • step S22 when there are multiple containers in the container set S that have the largest overall satisfaction rate a for target order Y, the first container with the largest overall satisfaction rate a can be used as container j ; Or, one can be randomly selected among multiple containers with the largest overall satisfaction rate a The container is used as container j; alternatively, container j can also be determined from multiple containers with the largest overall satisfaction rate a according to the location information of the container.
  • containers that are close to each other can be selected as container j in each round of screening, thereby saving the distance that equipment or personnel need to move between containers, reducing workload and improving work efficiency.
  • other rules may also be used to select one of multiple containers with the largest overall satisfaction rate a as container j according to actual needs. This is not limited in the embodiment of the present disclosure.
  • step S20 the purpose of step S20 is to narrow the scope of hit containers, so that in subsequent steps, it is only necessary to hit each container that can process orders among the containers in the filtered container set X, without hitting all candidate containers.
  • the containers added to the screening container set X in.
  • the overall satisfaction rate a is used as a standard to measure the contribution of the candidate container to the quantity of the single product of the order. The greater the overall satisfaction rate a, the greater the contribution of the candidate container to the quantity of the single product of the order.
  • all processable orders can be used as one order (ie, a processable order set) to determine the filtering container set X. If the candidate containers in the filtering container set The greater the contribution, the more concentrated the containers will be matched to all the orders that can be processed. That is, the better the candidate set, the more concentrated the final hit containers will be.
  • step S20 After the filtering container set X is obtained through step S20, it is necessary to sequentially hit the filtering containers corresponding to each processable order in all processable orders (ie, the processable order set) in the filtering container set X.
  • hitting each container that can process the order among the containers in the filtered container set X includes: determining the hit container based on the contribution of the containers in the filtered container set Containers with a large contribution to the quantity of single items are prioritized as hit containers.
  • the hit container is determined based on the contribution of the containers in the filtered container set
  • the order fulfillment rate of each filtering container for each processable order is determined, and among each filtering container, the filtering container with the largest order fulfillment rate is determined as the first hit container, and the first hit container is added to the hit container set.
  • the first hit container is one of the above hit containers.
  • the filtered container set and processable orders may be updated.
  • the filtered container with the largest order fulfillment rate (eg, the first hit container) can be deleted from the filtered container set, or the SKU information of the filtered container with the largest order fulfillment rate can be deleted.
  • Delete the second target SKU information to obtain the updated filtered container set.
  • delete the second target SKU information from the processable order to obtain an updated processable order.
  • the second target SKU information is the SKU information satisfied by the filtering container with the largest order fulfillment rate among the SKU information that can process the order.
  • the second target SKU information is the SKU information satisfied by the first hit container.
  • the next hit container (eg, the second hit container) may be determined in the updated filtered container set.
  • the order fulfillment rate of each filtering container in the updated filtering container set for the updated processable orders is determined; the filtering container with the largest order fulfillment rate in the updated filtering container set is determined as the second hits the container and adds the second hit container to the hit container collection.
  • the filtered container is determined to be the third hit container, and the third hit container is added to the hit container set. , set the updated processable orders to the empty set.
  • FIG. 3 is a schematic diagram of yet another order processing method provided by some embodiments of the present disclosure.
  • the hit process of step S30 will be described in detail below with reference to FIG. 3 .
  • step S30 includes the following steps.
  • i may be used to indicate the order sequence number at which the order can be processed. For example, when the quantity of orders that can be processed is m, m is a positive integer, and i can be expressed as any positive integer from 1 to m.
  • steps S32 and S33 the container hit by the i-th order is recorded in the corresponding hit container set Zi .
  • determining the order fulfillment rate of each screening container for each processable order includes: first, determining the second item fulfillment rate of each screening container for each item in the processable order; and then, based on the second The single product fulfillment rate determines the order fulfillment rate of each filtering container for the orders that can be processed.
  • the order fulfillment rate b of a certain container in the filtered container set X (that is, the filtered container) for the i-th processable order is calculated according to the following formula (3):
  • b is the order fulfillment rate
  • l is the number of types of SKUs of the i-th order that can be processed
  • d q is the response of a container in the filtering container set X to the q-th type of the i-th order that can be processed.
  • the first grade Second item satisfaction rate when the SKU of the container can satisfy the quantity of the q-th single product, the second single-product satisfaction rate d q is 1; when the SKU of the container cannot satisfy the quantity of the q-th single product, the second single-product satisfaction rate d q is 1.
  • the single product satisfaction rate d q is the ratio of the quantity of the SKU of the container corresponding to the q-th single product to the quantity of the i-th SKU that can process the order corresponding to the q-th single product.
  • d q can also be calculated by the following formula (4):
  • v q is the quantity of the q-th single product of the container's SKU
  • o q is the quantity of the q-th single product of the i-th SKU that can process the order.
  • the i-th processable order includes two order lines (SKUs) "10 bottles of shampoo” and “4 bars of soap", and the SKU of a certain container in the filtered container set X includes “12 bottles of shampoo” and "2 soaps” (two SKUs).
  • SKUs order lines
  • the SKU of a certain container in the filtered container set X includes "12 bottles of shampoo” and "2 soaps” (two SKUs).
  • there are two single products including shampoo and soap that is, the number of single product types of the i-th SKU that can process orders is 2.
  • the second single product satisfaction rate of the second single product for the second single product d 2 of the container
  • the order fulfillment rate b of each container in the filtered container set X for the ith processable order is calculated in turn, and the container k with the largest order fulfillment rate b is added to the hit container set Z i Among them, container k will be able to meet the demand for shipped items to the greatest extent in terms of quantity of single items.
  • each single product satisfaction rate d q is calculated only for the single product included in the i-th processable order, and for the single product only included in the container but not included in the i-th processable order, Single product satisfaction rate is not calculated. For example, if the i-th processable order only contains single-product shampoo and soap, and the container contains single-product shampoo, soap, and body wash, then the single-product satisfaction rate will only be calculated for the two single products, shampoo and soap. , without calculating the single product satisfaction rate for shower gel.
  • step S10 if SKUs in all containers that are not required for all processable orders have been eliminated in step S10, it will happen here that there are more item types in the container than in the i-th processable order. The probability of a single type will be reduced.
  • the i-th processable order includes the order line (SKU) "10 bottles of shampoo” and “4 bars of soap", and the SKU of container k with the largest order fulfillment rate b includes "14 bottles of shampoo” liquid” and “3 bars of soap”.
  • container k can satisfy the set of items that can process the i-th order (matching SKU) are "10 bottles of shampoo” and "4 bars of soap.” Therefore, in step S34, "10 bottles of shampoo” and “3 soap bars” will be eliminated from both the i-th SKU that can process the order and the SKU of container k.
  • the SKU of the i-th order that can be processed becomes "1 bar of soap", and the inventory SKU of container k becomes "4 bottles of shampoo”.
  • step S34 removing the detailed information of the SKUs satisfied by the matching SKU from the SKU of container k and the SKU of the i-th order that can be processed respectively means to respectively adjust the quantity dimension and the SKU of the i-th SKU in container k.
  • the quantity dimension of i SKUs that can process orders that is, the detailed information at least includes the quantity of single products, subtract the matched (satisfied) quantity from the original quantity (use the current quantity of SKU in container k minus the corresponding quantity in the matching SKU
  • the quantity of SKU is calculated by subtracting the quantity of the corresponding SKU in the matching SKU from the quantity of the current SKU that can process the i-th order).
  • the adjusted quantity is 0 (that is, the corresponding single product is matched as a whole), the SKU can be eliminated as a whole.
  • S35 Determine whether the set of SKUs that can process the i-th order is an empty set.
  • step S36 is executed; when the set of SKUs is not an empty set, step S33 is executed.
  • step S35 when all the containers in the hit container set Zi cannot meet the shipping requirements of the i-th processable order, in step S35, continue to select candidate containers according to the method in step S33. That is, find the container with the highest next order fulfillment rate b. Therefore, according to the method of the present disclosure, starting from the fact that the number of single items meets the demand for shipped items to the greatest extent, the number of hit containers is effectively reduced, that is, the container hits are more concentrated.
  • step S34 the SKUs in the i-th processable order will continue to be satisfied and thus decrease until the set of SKUs in the i-th processable order becomes an empty set.
  • the set of SKUs of the i-th order that can be processed is an empty set, it means that all the SKUs of the i-th order that can be processed have been satisfied by the set of containers with the largest order fulfillment rate b selected round by round in step S33, that is, Satisfied by the containers in the hit container set Z i . In other words, all containers in the hit container set Z i can meet the shipping needs of the i-th processable order.
  • step S33 when the order fulfillment rate b of a container for the i-th processable order is 1 (indicating that all containers required for the i-th processable order have been found), for example, the container Add the hit container set Z i , and then directly set the set of SKUs that can process the i-th order to the empty set.
  • This approach reduces the computational complexity of step S34 to a certain extent.
  • the information of the container k added to the hit container set Z i includes at least the location information of the container k.
  • the first container with the largest order fulfillment rate b can be used as container k; or, multiple containers can be used. Randomly select one of the containers with the largest order fulfillment rate b as container k; or determine container k from multiple containers with the largest order fulfillment rate b based on the location information of the container.
  • step S34 since the SKU of each container in the filtered container set Remove container k from the container set X. In this way, subsequent processing of empty containers is avoided and wasted work is avoided.
  • the order in which orders can be processed includes but is not limited to natural order, product coding order, and other regular orders.
  • step S30 on the premise of ensuring the order item type, the container added to the hit container set Z i is determined based on the contribution of the candidate containers in the filtered container set
  • the preferred container is first added to the hit container set Z i . That is, in step S30, on the premise of ensuring the order item type, the hit container is determined based on the contribution of the candidate containers in the filtered container set for the hit container.
  • the order fulfillment rate b is used as a standard to measure the contribution of the candidate container to the quantity of the single product of the order. The greater the order fulfillment rate b, the greater the contribution of the candidate container to the quantity of the single product of the order.
  • the order processing method provided according to the embodiment of the present disclosure can be implemented in the filtered container set to determine the hit container for each processable order among all processable orders.
  • all orders can be first divided into two categories: non-single product single-piece (single product multiple pieces, multi-product single piece, multi-product single piece, multi-product single piece) orders and single product single-piece orders, and then in the filtering container set , first hit all non-single product single-piece orders as the corresponding hit container when the order can be processed, and then hit all single-product single-piece orders as the corresponding hit container when the order can be processed.
  • non-single product single-piece single product multiple pieces, multi-product single piece, multi-product single piece, multi-product single piece
  • all processable orders can be divided into non-single-product single-piece orders and single-product single-piece orders. Then, treat all non-single product single-piece orders as processable orders, and perform the above S10, S20 and S30 steps (including branch steps, etc.) on this part of the processable orders to obtain each processable order in this part of the processable orders. The hit container corresponding to the order. Finally, treat all single product orders as processable orders, and execute the above S10, S20 and S30 steps (including branch steps, etc.) on this part of the processable orders to obtain each processable order in this part of the processable orders. The corresponding hit container.
  • single-item orders can be filled with just one container, while non-item orders often require multiple containers to fill, and the chance of hitting multiple containers is higher.
  • the order processing method provided by the embodiment of the present disclosure is to give priority to containers that contribute more to the quantity of single items while ensuring the type of items, thus enabling concentrated hits of containers. For example, if a single product order is processed first, the quantity of the single product in the container will decrease, causing the container's single product quantity to satisfy the order's single product quantity to decrease. This may cause the container that could originally satisfy the order to become Not satisfied. Therefore, prioritizing non-item single-piece orders can better achieve concentrated container hits.
  • the orders that can be processed include a single product order "1 bottle of shampoo” and a single product multi-item order "5 bottles of shampoo”.
  • Container 1 includes “5 bottles of shampoo”, and container 2 includes “4 bottles of shampoo”. Hair Liquid”. If the single product multi-piece order "5 bottles of shampoo” is processed first, then container 1 has the best satisfaction rate for the single product multi-piece order (fully satisfied, satisfaction rate is 1), then the single product multi-piece order hits the container 1. Then the single-product single-piece order "1 bottle of shampoo” is processed, and the single-product single-piece order hits container 2. The processing result is that each of the two orders hits one container.
  • the single product order "1 bottle of shampoo” is processed first, since both container 1 and container 2 can satisfy the single product order, it is possible that the single product order will hit container 1.
  • the SKU of container 1 changes to include "4 bottles of shampoo.”
  • neither container 1 nor container 2 can satisfy the single-product multi-piece order "5 bottles of shampoo” on its own, so the single-product multi-piece order needs to hit two containers, container 1 and container 2. It can be seen that prioritizing non-single product orders can better achieve concentrated container hits.
  • the order processing device 100 includes a task information acquisition module 10 , an inventory information acquisition module 20 , an analysis and calculation module 30 and an output module 40 .
  • the task information obtaining module 10 is used to obtain order task information.
  • the inventory information acquisition module 20 is used to acquire information about containers in inventory.
  • the analysis and calculation module 30 is connected to the task information acquisition module 10 and the inventory information acquisition module 20, and is used to execute the steps of the above order processing method (for example, steps S10, S20 and S30) according to the order task information and container information to hit each Container for orders.
  • the output module 40 is also connected to the analysis and calculation module 30 and is used to output information about the containers hit by each order determined by the analysis and calculation module 30 .
  • the information output by the output module 40 at least includes the location information of the hit container, so that the equipment or staff can obtain the container.
  • the analysis and calculation module 30 is also used to: obtain a set of processable orders and a set of candidate containers corresponding to the set of processable orders; the set of processable orders includes multiple processable orders, and the set of candidate containers includes Multiple candidate containers; filter multiple candidate containers to obtain at least one filtering container, and add at least one filtering container to the filtering container collection; wherein at least one filtering container meets the order requirements of the order collection that can be processed; in the filtering container collection Hit the filter container corresponding to each order that can be processed.
  • an embodiment of the present disclosure provides an electronic device.
  • the electronic device includes one or more processors and memory.
  • Memory is used to store one or more programs. Among them, it should be When one or more programs are executed by the one or more processors, the one or more processors implement the order processing method of the above embodiment.
  • electronic device 800 includes processor 801, which can be loaded into random access memory (RAM) 803 according to a computer program stored in read only memory (ROM) 802 or from storage unit 808 computer program to perform various appropriate actions and processes.
  • RAM random access memory
  • ROM read only memory
  • RAM 803 various programs and data required for the operation of the device 800 can also be stored.
  • the processor 801, ROM 802 and RAM 803 are connected to each other through a bus 804.
  • An input/output (I/O) interface 805 is also connected to bus 804.
  • the input unit 806 may be any type of device capable of inputting information to the electronic device 800.
  • the input unit 806 may receive input numeric or character information and generate key signal input related to user settings and/or function control of the electronic device.
  • Output unit 807 may be any type of device capable of presenting information, and may include, but is not limited to, a display, speakers, video/audio output terminal, vibrator, and/or printer.
  • the storage unit 804 may include, but is not limited to, magnetic disks and optical disks.
  • the communication unit 809 allows the electronic device 800 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunications networks, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver and/or a chip Groups such as BluetoothTM devices, WiFi devices, WiMax devices, cellular communications devices and/or the like.
  • Processor 801 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processing processor (DSP), and any appropriate processor, controller, microcontroller, etc. Processor 801 performs various methods and processes described above. For example, in some embodiments, steps S10, S20, and S30 may be implemented as a computer software program that is tangibly embodied in a machine-readable medium, such as storage unit 808.
  • a machine-readable medium such as storage unit 808.
  • part or all of the computer program may be loaded and/or installed onto the electronic device 800 via the ROM 802 and/or the communication unit 809.
  • the processor 801 may be configured to perform steps S10, S20, and S30 in any other suitable manner (eg, by means of firmware).
  • Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that the program codes, when executed by the processor or controller, cause the functions specified in the flowcharts and/or block diagrams/ The operation is implemented.
  • the program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
  • Embodiments of the present disclosure provide a computer-readable storage medium.
  • a computer program is stored on the computer-readable storage medium.
  • the computer program is executed by the processor, The order processing method in the above embodiment is now described.
  • a computer-readable storage medium may be a tangible medium that may contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.
  • Computer-readable storage media may be machine-readable signal media or machine-readable media.
  • Machine-readable media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any suitable combination of the foregoing.
  • Computer readable storage media would include electrical connections based on one or more wires, laptop disks, hard drives, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • RAM random access memory
  • ROM read only memory
  • EPROM or flash memory erasable programmable read only memory
  • CD-ROM portable compact disk read-only memory
  • magnetic storage device or any suitable combination of the above.
  • machine-readable medium and “computer-readable storage medium” refer to any computer program product, device, and/or device for providing machine instructions and/or data to a programmable processor.
  • Devices e.g., magnetic disks, optical disks, memories, programmable logic devices (PLD)
  • machine-readable media that receive machine instructions as machine-readable signals.
  • machine-readable signal refers to a device that transmits machine instructions and/or data to any signal provided to the programmable processor.
  • the systems and techniques described herein may be implemented on a computer having a display device (eg, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user ); and a keyboard and pointing device (eg, a mouse or a trackball) through which a user can provide input to the computer.
  • a display device eg, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor
  • a keyboard and pointing device eg, a mouse or a trackball
  • Other kinds of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and may be provided in any form, including Acoustic input, voice input or tactile input) to receive input from the user.
  • the systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., A user's computer having a graphical user interface or web browser through which the user can interact with implementations of the systems and technologies described herein), or including such backend components, middleware components, or any combination of front-end components in a computing system.
  • the components of the system may be interconnected by any form or medium of digital data communication (eg, a communications network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.
  • Computer systems may include clients and servers.
  • Clients and servers are generally remote from each other and typically interact over a communications network.
  • the relationship of client and server is created by computer programs running on corresponding computers and having a client-server relationship with each other.
  • order processing apparatus, electronic equipment and computer-readable storage medium provided according to the embodiments of the present disclosure include the order processing method according to the present disclosure, they also include all features and effects of the order processing method provided according to the real-time examples of the present disclosure.

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Abstract

本公开提供一种订单处理方法、装置、电子设备和计算机可读存储介质。该方法包括：获取全部可处理订单的信息和全部候选容器的信息，设置筛选容器集合X的初始值为空集；从全部候选容器中筛选出至少一个容器并将其加入筛选容器集合X，其中，筛选容器集合X中的全部容器满足全部可处理订单；在筛选容器集合X中的容器中命中每个可处理订单的容器。

Description

订单处理方法、装置、电子设备和计算机可读存储介质
本申请要求于2022年05月10日提交的申请号为202210508141.9的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本公开涉及智能仓储技术领域，具体地，涉及一种订单处理方法、订单处理装置、电子设备和计算机可读存储介质。
背景技术
在智能仓库系统中，在对商品或货物进行拣选时，可以基于当前库存结构，建立商品订单和库存容器的映射关系，并根据该映射关系确定命中该商品订单的多个容器，从而提高命中率以及拣选效率。
通常，采用贪心算法确定命中商品订单的多个容器。例如，为了使得拣选每个订单最终出库的容器数量最少，以及所有订单最终出库的容器数量最少，可以根据各订单中的单品种类数量，优先命中单品种类数量最多的容器。
发明内容
在发明内容部分中引入了一系列简化形式的概念，这将在具体实施方式部分中进一步详细说明。本公开的发明内容部分并不意味着要试图限定出所要求保护的技术方案的关键特征和必要技术特征，更不意味着试图确定所要求保护的技术方案的保护范围。
本公开的第一方面提供了一种订单处理方法，包括：首先，获取全部可处理订单的信息和全部候选容器的信息，设置筛选容器集合X的初始值为空集。然后，从全部候选容器中筛选出至少一个容器并将其加入筛选容器集合X；其中，筛选容器集合X中的全部容器满足全部可处理订单。最后，在筛选容器集合X中的容器中命中每个可处理订单的容器。
本公开的第二方面提供了一种订单处理方法，包括：首先，获取可处理订单集合和可处理订单集合对应的候选容器集合；该可处理订单集合中包括多个可处理订单，该候选容器集合包括多个候选容器。然后，对多个候选容器进行筛选，得到至少一个筛选容器，并将至少一个筛选容器添加至筛选容器集合；其中，至少一个筛选容器满足可处理订单集合的订单需求。最后，在筛选容器集合中命中各可处理订单对应的筛选容器。
本公开第三方面提供一种订单处理装置，包括：任务信息获取模块、库存信息获取模块、分析计算模块以及输出模块。其中，任务信息获取模块用于获取订单任务信息。库存信息获取模块用于获取库存中的容器的信息。分析计算模块用于根据订单任务信息和容器的信息执行第一方面和第二方面中 任一项所述的订单处理方法的步骤，以命中每个订单的容器。输出模块用于输出每个订单所命中的容器的信息。
本公开的第四方面提供一种电子设备，包括：一个或多个处理器以及存储器。其中，存储器用于存储一个或多个程序，其中，当一个或多个程序被一个或多个处理器执行时，一个或多个处理器实现如第一方面和第二方面中任一项所述的订单处理方法。
本公开的第五方面提供一种计算机可读存储介质，其上存储有计算机程序，当该计算机程序被处理器执行时，实现如第一方面和第二方面中任一项所述的订单处理方法。
附图说明
本公开的下列附图在此作为本公开的一部分用于理解本公开。附图中示出了本公开的实施方式及其描述，用来解释本公开的原理。在附图中：
图1为本公开一些实施例提供的一种订单处理方法的示意图；
图2为本公开一些实施例提供的另一种订单处理方法的示意图；
图3为本公开一些实施例提供的又一种订单处理方法的示意图；
图4为本公开一些实施例提供的一种订单处理装置的示意图；
图5为本公开一些实施例提供的一种电子设备的示意图。
具体实施方式
在下文的描述中，给出了大量具体的细节以便提供对本公开更为彻底的理解。然而，对于本领域技术人员而言显而易见的是，本公开可以无需一个或多个这些细节而得以实施。在其他的例子中，为了避免与本公开发生混淆，对于本领域公知的一些技术特征未进行描述。
为了彻底理解本公开，将在下列的描述中提出详细的描述。应当理解的是，提供这些实施方式是为了使得本公开的公开彻底且完整，并且将这些示例性实施方式的构思充分传达给本领域普通技术人员。显然，本公开实施方式的施行并不限定于本领域的技术人员所熟悉的特殊细节。本公开的较佳实施方式详细描述如下，然而除了这些详细描述外，本公开还可以具有其他实施方式。
应予以注意的是，这里所使用的术语仅是为了描述具体实施方式，而非意图限制根据本公开的示例性实施方式。如在这里所使用的，除非上下文另外明确指出，否则单数形式也意图包括复数形式。此外，还应当理解的是，当在本说明书中使用术语“包含”和/或“包括”时，其指明存在特征、整体、步骤、操作、元件和/或组件，但不排除存在或附加一个或多个其他特征、整体、步骤、操作、元件、组件和/或它们的组合。
本公开中所引用的诸如“第一”和“第二”的序数词仅仅是标识，而不具有 任何其他含义，例如特定的顺序等。而且，例如，术语“第一部件”其本身不暗示“第二部件”的存在，术语“第二部件”本身不暗示“第一部件”的存在。
需要说明的是，本文中所使用的术语“上”、“下”、“前”、“后”、“左”、“右”、“内”、“外”以及类似的表述只是为了说明的目的，并非限制。
通常，在对商品或货物进行拣选时，可以采用贪心算法优先命中单品种类数量最多的容器。但是，在对多个订单的商品进行拣选时，由于每个订单中的单品种类数量不同，如果仅根据每个订单中的单品种类数量，优先命中该订单对应的单品种类数量最多的容器(也可以称为订单行数最多的容器)，会使得一个订单的命中变得零碎化。而且多个订单不能集中命中，导致多个订单的所有商品出库所需的容器数量较多，拣选效率较低。
为了解决上述问题，本公开提供一种订单处理方法，该方法通过对可处理订单集合对应的候选容器集合进行筛选，以将命中容器的范围限缩在筛选容器集合中，然后再从筛选容器集合中命中容器，因此能够有效地控制命中容器的范围(也即命中容器的数量)，减少可处理订单集合中的多个订单的所有商品出库所需的容器数量，提高拣选效率。
现在，将参照附图更详细地描述根据本公开的示例性实施方式。
本公开实施例提供了一种订单处理方法。如图1所示，在一些实施例中，根据本公开的订单处理方法包括以下步骤：
S10、获取全部可处理订单的信息和全部候选容器的信息，设置筛选容器集合X的初始值为空集。
S20、从全部候选容器中筛选出至少一个容器，并将其加入筛选容器集合X，其中，筛选容器集合X中的全部容器满足全部可处理订单。
S30、在筛选容器集合X中的容器中命中每个可处理订单的容器。
在步骤S10中，可处理订单是指全部订单中的各种出货条件均满足的订单。例如，可处理订单为库存能够满足的订单，或者可处理订单为发货时限满足客户发货时限要求的订单。例如，订单中包括订单行(SKU)“10瓶洗发液”，如果当前库存量中洗发液不足10瓶，无法满足该订单，则该订单为不可处理订单，如果当前库存量中洗发液的数量大于或等于10瓶，能够满足该订单，则该订单为可处理订单。
示例性地，在步骤S10中，对全部订单中现有库存无法满足的订单进行剔除，将剔除后的剩余订单作为可处理订单。这样，只针对库存可满足的订单命中其容器，而不处理库存不能满足的订单，避免做无用功。
通常，每一个容器的SKU(储存单元)集合中包括多种单品，而在处理订单时，工作人员仅关心容器中是否有订单中所需要的单品，也即容器的SKU是否对订单的SKU有贡献。因此，在一些示例中，在步骤S10中，对全部容器的SKU中的全部可处理订单均不需要的SKU进行剔除，将剔除了该不需 要的SKU后的容器作为候选容器。
例如，全部可处理订单只涉及洗发液和香皂两种单品，则对全部容器的SKU中的除洗发液和香皂以外的其他SKU均进行剔除，也即使候选容器的SKU中只包括洗发液和香皂的条目。同时，在一些示例中，在对全部容器的SKU中的全部可处理订单均不需要的SKU进行剔除后，再对空容器进行剔除，使得候选容器中不包括空容器。在这样，候选容器的SKU与订单的SKU吻合度更好，可以减轻后续的计算压力。
在一些实施例中，上述全部可处理订单也可以称为可处理订单集合，该可处理订单集合包括某一时间段内接收的到全部可处理订单。上述全部候选容器也可称为可处理订单集合对应的候选容器集合，该候选容器集合为包括多个候选容器。示例性地，该候选容器不包括空容器。
在一些实施例中，上述筛选容器集合X中的容器也可称为筛选容器，上述步骤S20可以认为是对候选容器集合中的多个候选容器进行筛选，得到至少一个筛选容器，并将该至少一个筛选容器添加至筛选容器集合X。其中，至少一个筛选容器满足可处理订单集合的订单需求。
在一些实施例中，上述对候选容器集合中的多个候选容器进行筛选，得到至少一个筛选容器，并将至少一个筛选容器添加至筛选容器集合X，包括：首先，确定多个候选容器中各候选容器对可处理订单集合的总体满足率。然后，将多个候选容器中，总体满足率最大的候选容器确定为第一筛选容器，并将第一筛选容器添加至筛选容器集合X。其中，至少一个筛选容器包括第一筛选容器。
示例性地，在将第一筛选容器添加至筛选容器集合X之后，可以对候选容器集合和可处理订单集合进行更新。
在一些实施例中，在将第一筛选容器添加至筛选容器集合X之后，首先可以在候选容器集合中删除总体满足率最大的候选容器(如，第一筛选容器)，或者，从总体满足率最大的候选容器的SKU信息中删除第一目标SKU信息，得到更新后的候选容器集合。然后，从可处理订单集合中删除第一目标SKU信息，得到更新后的可处理订单集合。其中，第一目标SKU信息为可处理订单集合的SKU信息中，总体满足率最大的候选容器所满足的SKU信息。例如，第一目标SKU信息为第一筛选容器所满足的SKU信息。
示例性地，在对候选容器集合和可处理订单集合进行更新之后，可以在更新后的候选容器集合中确定下一筛选容器(如，第二筛选容器)。
在一些实施例中，确定更新后的候选容器集合中各候选容器对更新后的可处理订单集合的总体满足率。将更新后的候选容器集合中，总体满足率最大的候选容器确定为第二筛选容器，并将第二筛选容器添加至筛选容器集合。其中，至少一个筛选容器包括第二筛选容器。
示例性地，当更新后的候选容器集合中候选容器对更新后的可处理订单集合的总体满足率为1时，将候选容器确定为第三筛选容器，并将第三筛选容器添加至筛选容器集合，将更新后的可处理订单集合设置为空集。其中，至少一个筛选容器包括第三筛选容器。
也就是说，不断循环上述第二筛选容器的确定步骤，可以依次确定出多个第二筛选容器，直至将候选容器集合中候选容器对更新后的可处理订单集合的总体满足率为1时，确定出最后一个筛选容器(如，第三筛选容器)。上述第一筛选容器、多个第二筛选容器和第三筛选容器能够满足可处理订单集合的订单需求。
图2为本公开一些实施例提供的另一种订单处理方法，下面结合图2，对步骤S20的筛选过程进行详细说明。如图2所示，步骤S20包括以下步骤。
S21、将全部可处理订单按照SKU的种类维度合并成一个目标订单Y，设置容器集合S的初始值为包括全部候选容器。
在步骤S21中，目标订单Y的SKU则为全部需要出库的货物的信息(包括货物的种类和数量)，容器集合S的全部SKU在货物的种类上只包括要出库的货物的种类，并且数量完全能够满足出库需要。
示例性地，容器集合S也可称为候选容器集合，目标订单Y也可称为可处理订单集合。
S22、计算容器集合S中的每个容器对目标订单Y的总体满足率a，将该总体满足率a最大的容器j加入筛选容器集合X。
在一些示例中，上述确定容器集合S中的每个容器对目标订单Y的总体满足率a，也可以认为是确定候选容器集合中各候选容器对可处理订单集合的总体满足率。
示例性地，确定候选容器集合中各候选容器对可处理订单集合的总体满足率，包括：确定各候选容器对可处理订单集合中的各单品的第一单品满足率；根据第一单品满足率，确定各候选容器对可处理订单集合的总体满足率。
在步骤S22中，总体满足率a按以下公式(1)计算：
公式(1)中，a为总体满足率，n为目标订单Y中的全部SKU的单品的种类数，cp为容器集合S中的某个容器对目标订单Y中的第p种单品的第一单品满足率。其中，当该容器的SKU能够满足第p种单品的数量时，该第一单品满足率cp为1；当该容器的SKU不能够满足第p种单品的数量时，该第一单品满足率cp为该容器的SKU的对应于第p种单品的数量与目标订单Y的SKU的对应于第p种单品的数量的比值。换句话说，cp也可以通过以下公式(2)计算：
其中，vp为容器的SKU的对应于第p种单品的数量，tp为目标订单Y的SKU的对应于第p种单品的数量。
例如，目标订单Y中包括两个订单行(SKU)“10瓶洗发液”和“4块香皂”，容器集合S中的某个容器的SKU包括“12瓶洗发液”和“2块香皂”(两个SKU)。此时，包括洗发液和香皂两种单品，即目标订单Y中的全部SKU的单品的种类数n为2。对于第一种单品洗发液，由于该容器的SKU能够满足该单品的数量(12>＝10)，因此，该容器对第一种单品的第一单品满足率c1＝1。对于第二种单品香皂，由于该容器的SKU不能够满足该单品的数量(2<4)，因此，该容器对第二种单品的第一单品满足率c2＝该容器的SKU的对应于第二种单品的数量/目标订单Y的SKU的对应于第二种单品的数量＝2/4＝0.5。则，该容器对目标订单Y的总体满足率a＝(c1+c2)/2＝0.75。
按照上述方法，依次计算容器集合S中的每个容器对目标订单Y的总体满足率a，将该总体满足率a最大的容器j加入筛选容器集合X。其中，容器j在单品数量上将能够最大程度地满足出货物品的需求。
例如，在步骤S22中，只对目标订单Y中所包含的单品计算各个单品的第一单品满足率cp，对仅在容器中包含、而不在目标订单Y中包含的单品不计算第一单品满足率。例如，目标订单Y中包含的单品为洗发液和香皂，容器中包含的单品为洗发液、香皂和沐浴液，则可以只对洗发液和香皂两种单品计算第一单品满足率，而不对沐浴液计算第一单品满足率。
在一些示例中，如果在步骤S10中已经对全部容器的SKU中的全部可处理订单均不需要的SKU进行了剔除，则此处不会发生容器中的单品种类多于目标订单Y中的单品种类的情况。
S23、从容器集合S中除去容器j或者从容器j的SKU中除去满足目标订单Y的SKU明细信息，从目标订单Y的SKU中除去被容器j的SKU所满足的SKU的明细信息。
由于容器j能够最大程度地满足出货物品的需求，因此将其加入筛选容器集合X。由于容器j尚不能完全满足出货需要，因此需要从剩下的容器中继续筛选容器，以补足容器j不能满足的订单SKU。
在一些示例中，步骤S23为新一轮的筛选重新配置了订单的需求和候选容器。例如，本轮目标订单Y中包括订单行(SKU)“10瓶洗发液”和“4块香皂”，总体满足率a最高的容器j的SKU包括“4瓶洗发液”和“5块香皂”，容器j满足目标订单Y的SKU明细信息为“4瓶洗发液”和“4块香皂”，则在下一轮筛选中，目标订单Y的SKU变为“6瓶洗发液”，并且在下一轮筛选中，容器j将不再参加筛选或者容器j的SKU变为“1块香皂”。
在一些示例中，SKU(订单行、订单明细、储存单元)包括两个维度，名称维度(单品名称)和数量维度(单品数量)。例如，在步骤S23中，从目标订单Y的SKU中除去被容器j的SKU所满足的SKU的明细信息，是指调整目标订单Y中的SKU的数量维度，也即明细信息至少包括单品的数量，用原数量减去被满足的数量(用目标订单Y当前的SKU的数量减去容器中对应的SKU的数量)。当调整后的数量为0时，该SKU可以被整体剔除。从容器j的SKU中除去满足目标订单Y的SKU明细信息，也是指调整容器j中的SKU的数量维度，也即明细信息至少包括单品的数量，用原数量减去被匹配(满足)的数量(用容器j的当前的SKU的数量减去满足目标订单Y的SKU的数量)。
S24、判断目标订单Y是否为空集。
当目标订单Y为空集时执行后续步骤(例如步骤S30)，当目标订单Y不为空集时执行步骤S22。
在一些示例中，当筛选容器集合X中的全部容器还不能满足全部可处理订单的出货需求时，可以按步骤S22中的方法对候选容器继续进行筛选，也即找出下一个总体满足率a最高的容器。因此，根据本公开的方法，从单品数量最大程度地满足出货物品的需求出发，使得命中容器的数量有效减少，也即使得容器命中更加集中。
例如，随着筛选轮数的增加，由于步骤S23，目标订单Y中的SKU将不断被满足从而减少，直至目标订单Y为空集。当目标订单Y为空集时，说明全部可处理订单的全部SKU已被在步骤S22中逐轮筛选出的总体满足率a最大的容器的集合满足，也即被筛选容器集合X满足。也就是说，筛选容器集合X中的全部容器已能满足全部可处理订单的出货需要。因此，在下一步骤S30中，只需在筛选容器集合X中的全部容器中为全部可处理订单中的每一个命中容器即可。
在一些示例中，最后一个进入筛选容器集合X的候选容器对目标订单Y的总体满足率a一定为1(该候选容器能够满足目标订单Y中全部单品的全部数量需求)。因此，在步骤S22中，示例性地，当有容器对目标订单Y的总体满足率a为1时(说明全部所需的容器已经都找到)，将该容器加入筛选容器集合X，然后直接设置目标订单Y为空集。这一做法相当于不再执行步骤S23和步骤S24，而直接执行步骤S30，在一定程度减少了运算量。或者，在步骤S22中，当有容器对目标订单Y的总体满足率a为1时，将该容器加入筛选容器集合X后直接执行步骤S30。
示例性地，在步骤S22中，当容器集合S中的容器对目标订单Y的总体满足率a最大的容器有多个时，可以将第一个得到的总体满足率a最大的容器作为容器j；或者，可以在多个总体满足率a最大的容器中随机选择的一个 容器作为容器j；或者，也可以根据容器的位置信息从多个总体满足率a最大的容器中确定容器j。
例如，可以根据容器的位置信息，在每轮筛选中尽量选择相互靠近的容器作为容器j，从而可以节省设备或人员在容器之间移动的距离，减少工作量、提供工作效率。例如，也可以根据实际需要，采用其他规则从多个总体满足率a最大的容器中选择一个作为容器j，本公开实施例对此不作限定。
通过上述介绍可知，步骤S20的目的是为了缩小命中容器的范围，使得后续步骤中只需在筛选容器集合X中的容器中命中每个可处理订单的容器，而不需在全部候选容器中命中每个可处理订单的容器。在步骤S20中，在保证订单单品种类的前提下，根据候选容器对订单的单品数量的贡献确定加入筛选容器集合X中的容器，将对单品数量贡献大的容器优先加入筛选容器集合X中。其中，把总体满足率a作为衡量候选容器对订单的单品数量的贡献的标准，总体满足率a越大，候选容器对订单的单品数量的贡献越大。
在一些示例中，在步骤S10和S20中，可以将全部可处理订单作为一个订单(即可处理订单集合)来确定筛选容器集合X，如果筛选容器集合X中的候选容器对全部可处理订单的贡献越大，那么最终为所有可处理订单匹配到的容器也越集中。也即，候选集越好，最终命中的容器也越集中。
示例性地，在经过步骤S20筛选得到筛选容器集合X后，需要在该筛选容器集合X中，依次命中全部可处理订单(即可处理订单集合)中的各可处理订单对应的筛选容器。
在一些实施例中，在筛选容器集合X中的容器中命中每个可处理订单的容器，包括：根据筛选容器集合X中的容器对订单的单品数量的贡献确定命中容器，将对订单的单品数量的贡献大的容器优先确定为命中容器。
在一些示例中，上述筛选容器集合X中的容器对订单的单品数量的贡献也可以称为订单满足率，对订单的单品数量的贡献大的容器也可以成为订单满足率大的容器。
在一些实施例中，根据筛选容器集合X中的容器对订单的单品数量的贡献确定命中容器，将对订单的单品数量的贡献大的容器优先确定为命中容器，也可以认为是：确定各筛选容器对各可处理订单的订单满足率，并将各筛选容器中，将订单满足率最大的筛选容器确定为第一命中容器，并将第一命中容器添加至命中容器集合。其中，第一命中容器为上述命中容器中的一个容器。
示例性地，在将第一命中容器添加至命中容器集合之后，可以对筛选容器集合和可处理订单进行更新。
在一些实施例中，可以在筛选容器集合中删除订单满足率最大的筛选容器(如，第一命中容器)，或者，从订单满足率最大的筛选容器的SKU信息 中删除第二目标SKU信息，得到更新后的筛选容器集合。以及，从可处理订单中删除第二目标SKU信息，得到更新后的可处理订单。其中，第二目标SKU信息为可处理订单的SKU信息中，订单满足率最大的筛选容器所满足的SKU信息。例如，第二目标SKU信息为第一命中容器所满足的SKU信息。
示例性地，在对筛选容器集合和可处理订单进行更新之后，可以在更新后的筛选容器集合中确定下一命中容器(如，第二命中容器)。
在一些实施例中，确定更新后的筛选容器集合中各筛选容器对更新后的可处理订单的订单满足率；将更新后的筛选容器集合中，订单满足率最大的筛选容器，确定为第二命中容器，并将第二命中容器添加至命中容器集合。
示例性地，当更新后的筛选容器集合中筛选容器对更新后的可处理订单的总体满足率为1时，将筛选容器确定为第三命中容器，并将第三命中容器添加至命中容器集合，将更新后的可处理订单设置为空集。
图3为本公开一些实施例提供的又一种订单处理方法的示意图，下面结合图3，对步骤S30的命中过程进行详细说明。如图3所示，步骤S30包括以下步骤。
S31、设置i＝1，其中i为正整数。
在一些示例中，i可以用于指示可处理订单的订单序号。例如，当可处理订单的数量为m时，m为正整数，i可以表示为从1到m中的任一正整数。
S32，设置与第i个可处理订单对应的命中容器集合Zi的初始值为空集。
S33、计算筛选容器集合X中的每个容器对第i个可处理订单的订单满足率b，将该订单满足率b最大的容器k的信息加入命中容器集合Zi。
在步骤S32和S33中，将第i个订单所命中的容器记录在对应的命中容器集合Zi中。
在一些示例中，上述计算筛选容器集合X中的每个容器对第i个可处理订单的订单满足率b，也可以认为是确定筛选容器集合中各筛选容器对各可处理订单的订单满足率。
在一些实施例中，确定各筛选容器对各可处理订单的订单满足率，包括：首先，确定各筛选容器对可处理订单中的各单品的第二单品满足率；然后，根据第二单品满足率，确定各筛选容器对可处理订单的订单满足率。
其中，筛选容器集合X中的某个容器(即筛选容器)对第i个可处理订单的订单满足率b按以下公式(3)计算：
其中，b为订单满足率，l为第i个可处理订单的SKU的单品的种类数，dq为筛选容器集合X中的某个容器对第i个可处理订单中的第q种单品的第 二单品满足率。其中，当该容器的SKU能够满足第q种单品的数量时，该第二单品满足率dq为1；当该容器的SKU不能够满足第q种单品的数量时，该第二单品满足率dq为该容器的SKU的对应于第q种单品的数量与第i个可处理订单的SKU的对应于第q种单品的数量的比值。换句话说，dq也可以通过以下公式(4)计算：
其中，vq为容器的SKU的对应于第q种单品的数量，oq为第i个可处理订单的SKU的对应于第q种单品的数量。
例如，第i个可处理订单中包括两个订单行(SKU)“10瓶洗发液”和“4块香皂”，筛选容器集合X中的某个容器的SKU包括“12瓶洗发液”和“2块香皂”(两个SKU)。此时，包括洗发液和香皂两种单品，即第i个可处理订单的SKU的单品的种类数为2。对于第一种单品洗发液，由于该容器的SKU能够满足该单品的数量(12>＝10)，因此，该容器对第一种单品的第二单品满足率d1＝1。对于第二种单品香皂，由于该容器的SKU不能够满足该单品的数量(2<4)，因此，该容器对第二种单品的第二单品满足率d2＝该容器的SKU的对应于第二种单品的数量/第i个可处理订单的SKU的对应于第二种单品的数量＝2/4＝0.5。则，该容器对第i个可处理订单的订单满足率b＝(d1+d2)/2＝0.75。
按照上述方法，依次计算筛选容器集合X中的每个容器对第i个可处理订单的订单满足率b，将该订单满足率b最大的容器k加入命中容器集合Zi。其中，容器k在单品数量上将能够最大程度地满足出货物品的需求。
例如，在步骤S33中，只对第i个可处理订单中所包含的单品计算各个单品满足率dq，对仅在容器中包含、而不在第i个可处理订单中包含的单品不计算单品满足率。例如，第i个可处理订单中只包含单品洗发液和香皂，容器中包含单品洗发液、香皂和沐浴液，则只对洗发液和香皂两种单品计算单品满足率，而不对沐浴液计算单品满足率。
在一些示例中，如果在步骤S10中已经对全部容器的SKU中的全部可处理订单均不需要的SKU进行了剔除，则此处发生容器中的单品种类多于第i个可处理订单中的单品种类的几率将会降低。
S34、从容器k的SKU中除去被匹配SKU所满足的SKU的明细信息，从第i个可处理订单的SKU中除去被匹配SKU所满足的SKU的明细信息，其中该匹配SKU为第i个可处理订单的SKU中被容器k所满足的单品的集合。
例如，在步骤S33中，第i个可处理订单中包括订单行(SKU)“10瓶洗发液”和“4块香皂”，订单满足率b最大的容器k的SKU包括“14瓶洗发液”和“3块香皂”。则，容器k能够满足第i个可处理订单的单品的集合(匹配 SKU)为“10瓶洗发液”和“4块香皂”。因此，在步骤S34中，第i个可处理订单的SKU和容器k的SKU中都将剔除掉“10瓶洗发液”和“3块香皂”。则，在步骤S34中，第i个可处理订单的SKU变为“1块香皂”，容器k的库存SKU变为“4瓶洗发液”。
例如，在步骤S34中，分别从容器k的SKU中和第i个可处理订单的SKU中除去该匹配SKU所满足的SKU的明细信息，是指分别调整容器k中的SKU的数量维度和第i个可处理订单的SKU的数量维度，也即明细信息至少包括单品的数量，用原数量减去被匹配(满足)的数量(用容器k的当前的SKU的数量减去匹配SKU中对应的SKU的数量，用第i个可处理订单的当前的SKU的数量减去匹配SKU中对应的SKU的数量)。当调整后的数量为0时(也即相应的单品被整体匹配)，该SKU可以被整体剔除。
S35、判断第i个可处理订单的SKU的集合是否为空集。
当该SKU的集合为空集时，执行步骤S36；当该SKU的集合不为空集时，执行步骤S33。
S36、输出命中容器集合Zi。
在步骤S35和S36中，当命中容器集合Zi中的全部容器还不能满足第i个可处理订单的出货需求时，在步骤S35中，按步骤S33中的方法对候选容器继续进行挑选，也即找出下一个订单满足率b最高的容器。因此，根据本公开的方法，从单品数量最大程度地满足出货物品的需求出发，使得命中容器的数量有效减少，也即使得容器命中更加集中。
在一些示例中，伴随挑选轮数的增加，由于步骤S34，第i个可处理订单中的SKU将不断被满足从而减少，直至第i个可处理订单的SKU的集合为空集。当第i个可处理订单的SKU的集合为空集时，说明第i个可处理订单的全部SKU已被在步骤S33中逐轮挑选出的订单满足率b最大的容器的集合满足，也即被命中容器集合Zi中的容器满足。换句话说，命中容器集合Zi中的全部容器已能满足第i个可处理订单的出货需要。
示例性地，最后一个进入命中容器集合Zi的候选容器对第i个可处理订单的订单满足率b一定为1(该候选容器能够满足第i个可处理订单中全部单品的全部数量需求)。因此，在步骤S33中，当有容器对第i个可处理订单的订单满足率b为1时(说明第i个可处理订单所需的全部容器已经都找到)，示例性地，将该容器加入命中容器集合Zi，然后直接设置第i个可处理订单的SKU的集合为空集。这一做法在一定程度减少了步骤S34运算量。
示例性地，被加入命中容器集合Zi的容器k的信息至少包括容器k的位置信息。
在一些实施例中，当在步骤S33中订单满足率b最大的容器有多个时，可以将第一个得到的订单满足率b最大的容器作为容器k；或者，可以在多 个订单满足率b最大的容器中随机选择一个作为容器k；或者，根据容器的位置信息从多个订单满足率b最大的容器中确定容器k。
例如，根据容器的位置信息，在每轮挑选中尽量选择相互靠近的容器k，从而可以节省设备或人员在容器之间移动的距离，减少工作量、提供工作效率。例如，也可以根据实际需求，采用其它规则从多个订单满足率b最大的容器中选择一个作为容器k。
在步骤S34中，由于筛选容器集合X中的每个容器的SKU会被不断删减，示例性地，在从容器k的SKU中除去匹配SKU后，若容器k变为空容器，则从筛选容器集合X中剔除容器k。这样，避免了后续对空容器进行处理，避免做无用功。
S37、确定i是否等于m。
当i＝m时，结束订单处理流程；当i≠m时，将i的数值加1(如i＝i+1)然后执行步骤S32。
在步骤S37中，i的序号加1，即将要对下一个可处理订单进行处理。处理完全部可处理订单后(即i＝m时)，结束订单命中容器的处理流程。在本公开实施例中，可处理订单的顺序包括但不限于自然顺序、商品编码顺序以及其他规律顺序等。
在步骤S30中，在保证订单单品种类的前提下，根据筛选容器集合X中的候选容器对订单的单品数量的贡献确定加入命中容器集合Zi中的容器，将对单品数量贡献大的优选容器优先加入命中容器集合Zi中。也即，在步骤S30中，在保证订单单品种类的前提下，根据筛选容器集合X中的候选容器对订单的单品数量的贡献确定命中容器，将对单品数量贡献大的容器优先确定为命中容器。其中，把订单满足率b作为衡量候选容器对订单的单品数量的贡献的标准，订单满足率b越大，候选容器对订单的单品数量的贡献越大。
通过上述步骤，根据本公开实施例提供的的订单处理方法可以实现在筛选容器集合中，确定对全部可处理订单中每个可处理订单的命中容器。
在一些实施例中，可以先将全部订单分为非单品单件(单品多件、多品单件、多品多件)订单和单品单件订单两类，然后在筛选容器集合中，首先命中全部非单品单件订单作为可处理订单时对应的命中容器，再命中全部单品单件订单作为可处理订单时对应的命中容器。
示例性地，可以先将全部可处理订单分为非单品单件订单和单品单件订单。然后，将全部非单品单件订单作为可处理订单，对这部分可处理订单执行上述的S10、S20和S30步骤(包括其中的分支步骤等)，得到这部分可处理订单中每个可处理订单对应的命中容器。最后，将全部单品单件订单作为可处理订单，对这部分可处理订单执行上述的S10、S20和S30步骤(包括其中的分支步骤等)，得到这部分可处理订单中每个可处理订单对应的命中容器。
在一些示例中，单品单件订单只需一个容器即可满足，而非单品单件通常需要多个容器满足，命中多个容器的几率更高。本公开实施例提供的的订单处理方法是在保证单品种类的前提下，优先选择对单品数量贡献更高的容器，因而能够使容器集中命中。例如，如果先处理单品单件订单，则会使容器中的单品数量下降，使得容器的单品数量对订单的单品数量的满足率下降，从而可能使本来能够满足订单的容器变为不满足。因此，优先处理非单品单件订单能够更好地实现容器集中命中。
例如，可处理订单包括单品单件订单“1瓶洗发液”和单品多件订单“5瓶洗发液”，容器1包括“5瓶洗发液”，容器2包括“4瓶洗发液”。如果先行处理单品多件订单“5瓶洗发液”，则容器1对该单品多件订单的满足率最好(完全满足，满足率为1)，则该单品多件订单命中容器1。然后处理单品单件订单“1瓶洗发液”，该单品单件订单命中容器2。处理结果为两个订单各自命中1个容器。如果先行处理单品单件订单“1瓶洗发液”，由于容器1和容器2均能满足该单品单件订单，那么有可能该单品单件订单会命中容器1。在处理完该单品单件订单后，容器1的SKU变为包括“4瓶洗发液”。在这种情况下，容器1和容器2各自均不能单独满足单品多件订单“5瓶洗发液”，则该单品多件订单需要命中容器1和容器2两个容器。由此可知，优先处理非单品单件订单可以更好地实现容器集中命中。
本公开实施例提供一种订单处理装置。如图4所示，在一些实施例中，订单处理装置100包括任务信息获取模块10、库存信息获取模块20、分析计算模块30和输出模块40。
其中，任务信息获取模块10用于获取订单任务信息。库存信息获取模块20用于获取库存中的容器的信息。分析计算模块30连接至任务信息获取模块10和库存信息获取模块20，用于根据订单任务信息和容器的信息执行上述订单处理方法的步骤(例如，步骤S10、S20和S30)，以命中每个订单的容器。输出模块40也与分析计算模块30相连接，用于输出由分析计算模块30所确定的每个订单所命中的容器的信息。其中，输出模块40所输出的信息至少包括被命中的容器的位置信息，以便于设备或工作人员获取该容器。
在一些实施例中，分析计算模块30还用于：获取可处理订单集合和所述可处理订单集合对应的候选容器集合；该可处理订单集合中包括多个可处理订单，该候选容器集合包括多个候选容器；对多个候选容器进行筛选，得到至少一个筛选容器，并将至少一个筛选容器添加至筛选容器集合；其中，至少一个筛选容器满足可处理订单集合的订单需求；在筛选容器集合中命中各可处理订单对应的筛选容器。
本公开实施例提供一种电子设备。在一些实施例中，该电子设备包括一个或多个处理器以及存储器。存储器用于存储一个或多个程序。其中，当该 一个或多个程序被该一个或多个处理器执行时，该一个或多个处理器实现上述实施例的订单处理方法。
如图5所示，在一些实施例中，电子设备800包括处理器801，其可以根据存储在只读存储器(ROM)802中的计算机程序或者从存储单元808加载到随机访问存储器(RAM)803中的计算机程序，来执行各种适当的动作和处理。在RAM 803中，还可存储设备800操作所需的各种程序和数据。处理器801、ROM 802以及RAM 803通过总线804彼此相连。输入/输出(I/O)接口805也连接至总线804。
电子设备800中的多个部件连接至I/O接口805，包括：输入单元806、输出单元807、存储单元808以及通信单元809。输入单元806可以是能向电子设备800输入信息的任何类型的设备，输入单元806可以接收输入的数字或字符信息，以及产生与电子设备的用户设置和/或功能控制有关的键信号输入。输出单元807可以是能呈现信息的任何类型的设备，并且可以包括但不限于显示器、扬声器、视频/音频输出终端、振动器和/或打印机。存储单元804可以包括但不限于磁盘、光盘。通信单元809允许电子设备800通过诸如因特网的计算机网络和/或各种电信网络与其他设备交换信息/数据，并且可以包括但不限于调制解调器、网卡、红外通信设备、无线通信收发机和/或芯片组，例如蓝牙TM设备、WiFi设备、WiMax设备、蜂窝通信设备和/或类似物。
处理器801可以是各种具有处理和计算能力的通用和/或专用处理组件。处理器801的一些示例包括但不限于中央处理单元(CPU)、图形处理单元(GPU)、各种专用的人工智能(AI)计算芯片、各种运行机器学习模型算法的处理器、数字信号处理器(DSP)、以及任何适当的处理器、控制器、微控制器等。处理器801执行上文所描述的各个方法和处理。例如，在一些实施例中，步骤S10、S20和S30可被实现为计算机软件程序，其被有形地包含于机器可读介质，例如存储单元808。在一些实施例中，计算机程序的部分或者全部可以经由ROM 802和/或通信单元809而被载入和/或安装到电子设备800上。在一些实施例中，处理器801可以通过其他任何适当的方式(例如，借助于固件)而被配置为执行步骤S10、S20和S30。
用于实施本公开的方法的程序代码可以采用一个或多个编程语言的任何组合来编写。这些程序代码可以提供给通用计算机、专用计算机或其他可编程数据处理装置的处理器或控制器，使得程序代码当由处理器或控制器执行时使流程图和/或框图中所规定的功能/操作被实施。程序代码可以完全在机器上执行、部分地在机器上执行，作为独立软件包部分地在机器上执行且部分地在远程机器上执行或完全在远程机器或服务器上执行。
本公开实施例提供一种计算机可读存储介质。在一些实施例中，该计算机可读存储介质上存储有计算机程序，当该计算机程序被处理器执行时，实 现上述实施例中的订单处理方法。
在本公开的上下文中，计算机可读存储介质可以是有形的介质，其可以包含或存储以供指令执行系统、装置或设备使用或与指令执行系统、装置或设备结合地使用的程序。计算机可读存储介质可以是机器可读信号介质或机器可读介质。机器可读介质可以包括但不限于电子的、磁性的、光学的、电磁的、红外的、或半导体系统、装置或设备，或者上述内容的任何合适组合。计算机可读存储介质的更具体示例会包括基于一个或多个线的电气连接、便携式计算机盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦除可编程只读存储器(EPROM或快闪存储器)、光纤、便捷式紧凑盘只读存储器(CD-ROM)、光学储存设备、磁储存设备、或上述内容的任何合适组合。
如本公开使用的，术语“机器可读介质”和“计算机可读存储介质”指的是用于将机器指令和/或数据提供给可编程处理器的任何计算机程序产品、设备、和/或装置(例如，磁盘、光盘、存储器、可编程逻辑装置(PLD)，包括，接收作为机器可读信号的机器指令的机器可读介质。术语“机器可读信号”指的是用于将机器指令和/或数据提供给可编程处理器的任何信号。
为了提供与用户的交互，可以在计算机上实施此处描述的系统和技术，该计算机具有：用于向用户显示信息的显示装置(例如，CRT(阴极射线管)或者LCD(液晶显示器)监视器)；以及键盘和指向装置(例如，鼠标或者轨迹球)，用户可以通过该键盘和该指向装置来将输入提供给计算机。其它种类的装置还可以用于提供与用户的交互；例如，提供给用户的反馈可以是任何形式的传感反馈(例如，视觉反馈、听觉反馈、或者触觉反馈)；并且可以用任何形式(包括声输入、语音输入或者、触觉输入)来接收来自用户的输入。
可以将此处描述的系统和技术实施在包括后台部件的计算系统(例如，作为数据服务器)、或者包括中间件部件的计算系统(例如，应用服务器)、或者包括前端部件的计算系统(例如，具有图形用户界面或者网络浏览器的用户计算机，用户可以通过该图形用户界面或者该网络浏览器来与此处描述的系统和技术的实施方式交互)、或者包括这种后台部件、中间件部件、或者前端部件的任何组合的计算系统中。可以通过任何形式或者介质的数字数据通信(例如，通信网络)来将系统的部件相互连接。通信网络的示例包括：局域网(LAN)、广域网(WAN)和互联网。
计算机系统可以包括客户端和服务器。客户端和服务器一般远离彼此并且通常通过通信网络进行交互。通过在相应的计算机上运行并且彼此具有客户端-服务器关系的计算机程序来产生客户端和服务器的关系。
由于根据本公开实施例提供的订单处理装置、电子设备和计算机可读存储介质包括了根据本公开的订单处理方法，因此其也包括根据本公开实时例提供的订单处理方法的全部特征和效果。
除非另有定义，本文中所使用的技术和科学术语与本公开的技术领域的技术人员通常理解的含义相同。本文中使用的术语只是为了描述具体的实施目的，不是旨在限制本公开。
本公开已经通过上述实施方式进行了说明，但应当理解的是，上述实施方式只是用于举例和说明的目的，而非意在将本公开限制于所描述的实施方式范围内。此外本领域技术人员可以理解的是，本公开并不局限于上述实施方式，根据本公开的教导还可以做出更多种的变型和修改，这些变型和修改均落在本公开所要求保护的范围以内。

Claims (28)

  1. 一种订单处理方法，包括：
    获取全部可处理订单的信息和全部候选容器的信息，设置筛选容器集合X的初始值为空集；
    从全部所述候选容器中筛选出至少一个所述容器并将其加入所述筛选容器集合X，其中，所述筛选容器集合X中的全部容器满足全部所述可处理订单：
    在所述筛选容器集合X中的所述容器中命中每个所述可处理订单的容器。
  2. 根据权利要求1所述的订单处理方法，其中，所述从全部所述候选容器中筛选出至少一个所述容器并将其加入所述筛选容器集合X，包括：
    根据所述候选容器对订单的单品数量的贡献确定加入所述筛选容器集合X中的容器，将对所述订单的单品数量的贡献大的容器优先加入所述筛选容器集合X中。
  3. 根据权利要求2所述的订单处理方法，其中，将总体满足率a作为衡量所述候选容器对所述订单的单品数量的贡献的标准；所述总体满足率a越大，所述候选容器对所述订单的单品数量的贡献越大；其中，所述总体满足率a为：
    其中，n为所述订单中的全部SKU的单品的种类数，cp为所述候选容器对所述订单中的第p种单品的单品满足率；
    其中，当所述候选容器的SKU能够满足所述第p种单品的数量时，所述单品满足率cp为1；当所述候选容器的SKU不能够满足所述第p种单品的数量时，所述单品满足率cp为所述候选容器的SKU的对应于所述第p种单品的数量与所述订单的SKU的对应于所述第p种单品的数量的比值；
    其中，只对所述订单中所包含的单品计算所述单品满足率。
  4. 根据权利要求3所述的订单处理方法，其中，所述从全部所述候选容器中筛选出至少一个所述容器并将其加入所述筛选容器集合X，包括：
    S21、将全部所述可处理订单按照SKU的种类维度合并成一个目标订单Y，设置容器集合S的初始值为包括全部所述候选容器，然后执行步骤S22；
    S22、计算所述容器集合S中的每个容器对所述目标订单Y的所述总体满足率a，将所述总体满足率a最大的容器j加入所述筛选容器集合X，然后执行步骤S23；
    S23、从所述容器集合S中除去所述容器j或者从所述容器j的SKU中 除去满足所述目标订单Y的SKU明细信息，从所述目标订单Y的SKU中除去被所述容器j的SKU所满足的SKU的明细信息，然后执行步骤S24；
    S24、判断所述目标订单Y是否为空集，当所述目标订单Y为空集时执行后续步骤，当所述目标订单Y不为空集时执行步骤S22；
    其中，所述明细信息包括单品的数量，所述总体满足率a为：
    其中，n为所述目标订单Y中的全部SKU的单品的种类数，cp为所述容器对所述目标订单Y中的第p种单品的单品满足率；
    其中，当所述容器的SKU能够满足所述第p种单品的数量时，所述单品满足率cp为1，当所述容器的SKU不能够满足所述第p种单品的数量时，所述单品满足率cp为所述容器的SKU的对应于所述第p种单品的数量与所述目标订单Y的SKU的对应于所述第p种单品的数量的比值；
    其中，只对所述目标订单Y中所包含的单品计算所述单品满足率。
  5. 根据权利要求4所述的订单处理方法，其中，在步骤S22中，当有所述容器对所述目标订单Y的所述总体满足率a为1时，将该容器加入所述筛选容器集合X，然后设置所述目标订单Y为空集。
  6. 根据权利要求4所述的订单处理方法，其中，在步骤S22中，当所述总体满足率a最大的容器有多个时：将第一个得到的所述总体满足率a最大的容器作为所述容器j，或者，随机选择多个所述总体满足率a最大的容器中的一个作为所述容器j，或者，根据容器的位置信息从多个所述总体满足率a最大的容器中确定所述容器j。
  7. 根据权利要求1所述的订单处理方法，其中，所述在所述筛选容器集合X中的所述容器中命中每个所述可处理订单的容器，包括：
    根据所述筛选容器集合X中的所述容器对订单的单品数量的贡献确定命中容器，将对所述订单的单品数量的贡献大的容器优先确定为所述命中容器。
  8. 根据权利要求7所述的订单处理方法，其中，把订单满足率b作为衡量所述筛选容器集合X中的所述容器对所述订单的单品数量的贡献的标准；所述订单满足率b越大，所述筛选容器集合X中的所述容器对所述订单的单品数量的贡献越大；其中，所述订单满足率b为：
    其中，l为所述订单的SKU的单品的种类数，dq为所述容器对所述订单中的第q种单品的单品满足率；
    其中，当所述容器的SKU能够满足所述第q种单品的数量时，所述单品 满足率dq为1，当所述容器的SKU不能够满足所述第q种单品的数量时，所述单品满足率dq为所述容器的SKU的对应于所述第q种单品的数量与所述订单的SKU的对应于所述第q种单品的数量的比值；
    其中，只对所述订单中所包含的单品计算所述单品满足率。
  9. 根据权利要求8所述的订单处理方法，其中，所述在所述筛选容器集合X中的所述容器中命中每个所述可处理订单的容器，包括：
    S31、设置i＝1，其中i为正整数，然后执行步骤S32；
    S32，设置与第i个所述可处理订单对应的命中容器集合Zi的初始值为空集，然后执行步骤S33；
    S33、计算所述筛选容器集合X中的每个容器对第i个所述可处理订单的所述订单满足率b，将所述订单满足率b最大的容器k的信息加入所述命中容器集合Zi，然后执行步骤S34；
    S34、从所述容器k的SKU中除去被匹配SKU所满足的SKU的明细信息，从所述第i个可处理订单的SKU中除去被所述匹配SKU所满足的SKU的明细信息，其中所述匹配SKU为所述第i个可处理订单的SKU中被所述容器k所满足的单品的集合，然后执行步骤S35；
    S35、判断第i个所述可处理订单的SKU的集合是否为空集，当所述SKU的集合为空集时执行步骤S36，当所述SKU的集合不为空集时执行步骤S33；
    S36、输出所述命中容器集合Zi，然后执行步骤S37；
    S37、当i＝m时结束订单处理流程，当i≠m时使i的数值加1然后执行步骤S32；
    其中，所述明细信息包括单品的数量，m为所述可处理订单的数量，m为正整数，所述订单满足率b为：
    其中，l为第i个所述可处理订单的SKU的单品的种类数，dq为所述容器对第i个所述可处理订单中的第q种单品的单品满足率；
    其中，当所述容器的SKU能够满足所述第q种单品的数量时，所述单品满足率dq为1，当所述容器的SKU不能够满足所述第q种单品的数量时，所述单品满足率dq为所述容器的SKU的对应于所述第q种单品的数量与第i个所述可处理订单的SKU的对应于所述第q种单品的数量的比值；
    其中，只对第i个所述可处理订单中所包含的单品计算所述单品满足率。
  10. 根据权利要求9所述的订单处理方法，其中，在步骤S33中，当有所述容器对第i个所述可处理订单的所述订单满足率b为1时，将所述容器加入命中容器集合Zi，然后设置第i个所述可处理订单的SKU的集合为空集。
  11. 根据权利要求9所述的订单处理方法，其中，步骤S34还包括：
    在从所述容器k的SKU中除去所述匹配SKU后，若所述容器k变为空容器，则从所述筛选容器集合X中剔除所述容器k。
  12. 根据权利要求1-11中任一项所述的订单处理方法，其中，所述获取全部可处理订单的信息和全部容器的信息，设置筛选容器集合X的初始值为空集，包括：
    对全部订单中现有库存无法满足的订单进行剔除，将剔除后的剩余订单作为所述可处理订单；
    对全部容器的SKU中的全部所述可处理订单均不需要的SKU进行剔除，将剔除了所述不需要的SKU后的容器作为所述候选容器；其中，所述候选容器中不包含空容器。
  13. 一种订单处理方法，包括：
    获取可处理订单集合和所述可处理订单集合对应的候选容器集合；所述可处理订单集合中包括多个可处理订单，所述候选容器集合包括多个候选容器；
    对所述多个候选容器进行筛选，得到至少一个筛选容器，并将所述至少一个筛选容器添加至筛选容器集合；其中，所述至少一个筛选容器满足所述可处理订单集合的订单需求；
    在所述筛选容器集合中命中各所述可处理订单对应的筛选容器。
  14. 根据权利要求13所述的订单处理方法，其中，所述对所述多个候选容器进行筛选，得到至少一个筛选容器，并将所述至少一个筛选容器添加至筛选容器集合，包括：
    确定所述多个候选容器中各候选容器对所述可处理订单集合的总体满足率；
    将所述多个候选容器中，总体满足率最大的候选容器确定为第一筛选容器，并将所述第一筛选容器添加至所述筛选容器集合；其中，所述至少一个筛选容器包括所述第一筛选容器。
  15. 根据权利要求14所述的订单处理方法，其中，所述确定所述多个候选容器中各候选容器对所述可处理订单集合的总体满足率，包括：
    确定各所述候选容器对所述可处理订单集合中的各单品的第一单品满足率；
    根据所述第一单品满足率，确定各所述候选容器对所述可处理订单集合的总体满足率。
  16. 根据权利要求15所述的订单处理方法，其中，所述总体满足率通过如下公式得到：
    其中，a为所述总体满足率，n为所述可处理订单集合中的单品的种类数，cp为所述候选容器对所述可处理订单集合中的第p种单品的第一单品满足率；
    其中，当所述候选容器的SKU能够满足所述第p种单品的数量时，所述第一单品满足率cp为1；当所述候选容器的SKU不能满足所述第p种单品的数量时，所述第一单品满足率cp为所述候选容器的SKU对应的所述第p种单品的数量与所述可处理订单集合中的SKU对应的所述第p种单品的数量的比值。
  17. 根据权利要求16所述的订单处理方法，其中，在所述将所述多个候选容器中，所述总体满足率最大的候选容器确定为所述筛选容器，并将所述筛选容器添加至所述筛选容器集合之后，所述方法还包括：
    在所述候选容器集合中删除所述总体满足率最大的候选容器，或者，从所述总体满足率最大的候选容器的SKU信息中删除第一目标SKU信息，得到更新后的候选容器集合；
    从所述可处理订单集合中删除所述第一目标SKU信息，得到更新后的可处理订单集合；其中，所述第一目标SKU信息为所述可处理订单集合的SKU信息中，所述总体满足率最大的候选容器所满足的SKU信息。
  18. 根据权利要求17所述的订单处理方法，其中，所述对所述多个候选容器进行筛选，得到至少一个筛选容器，并将所述至少一个筛选容器添加至筛选容器集合，还包括：
    确定所述更新后的候选容器集合中各所述候选容器对所述更新后的可处理订单集合的总体满足率；
    将所述更新后的候选容器集合中，总体满足率最大的候选容器确定为第二筛选容器，并将所述第二筛选容器添加至所述筛选容器集合；其中，所述至少一个筛选容器包括所述第二筛选容器。
  19. 根据权利要求18所述的订单处理方法，其中，所述对所述多个候选容器进行筛选，得到至少一个筛选容器，并将所述至少一个筛选容器添加至筛选容器集合，还包括：
    当所述更新后的候选容器集合中候选容器对所述更新后的可处理订单集合的总体满足率为1时，将所述候选容器确定为第三筛选容器，并将所述第三筛选容器添加至所述筛选容器集合；其中，所述至少一个筛选容器包括所述第三筛选容器；
    将所述更新后的可处理订单集合设置为空集。
  20. 根据权利要求13-19中任一项所述的订单处理方法，其中，所述在所述筛选容器集合中命中各所述可处理订单对应的筛选容器，包括：
    确定各所述筛选容器对各所述可处理订单的订单满足率；
    将所述各筛选容器中，订单满足率最大的筛选容器确定为第一命中容器， 并将所述第一命中容器添加至命中容器集合。
  21. 根据权利要求20所述的订单处理方法，其中，所述确定各所述筛选容器对各所述可处理订单的订单满足率，包括：
    确定各所述筛选容器对所述可处理订单中的各单品的第二单品满足率；
    根据所述第二单品满足率，确定各所述筛选容器对所述可处理订单的订单满足率。
  22. 根据权利要求21所述的订单处理方法，其中，所述订单满足率通过如下公式得到：
    其中，b为所述订单满足率，l为所述可处理订单中的单品的种类数，dq为所述筛选容器对所述可处理订单中的第q种单品的第二单品满足率；
    其中，当所述筛选容器的SKU能够满足所述第q种单品的数量时，所述第二单品满足率dq为1；当所述筛选容器的SKU不能满足所述第q种单品的数量时，所述第二单品满足率dq为所述筛选容器的SKU对应的所述第q种单品的数量与所述可处理订单的SKU对应的所述第q种单品的数量的比值。
  23. 根据权利要求22所述的订单处理方法，其中，所述在所述各筛选容器中，命中订单满足率最大的筛选容器，并将所述订单满足率最大的筛选容器添加至命中容器集合之后，所述方法还包括：
    在所述筛选容器集合中删除所述订单满足率最大的筛选容器，或者，从所述订单满足率最大的筛选容器的SKU信息中删除第二目标SKU信息，得到更新后的筛选容器集合；
    从所述可处理订单中删除所述第二目标SKU信息，得到更新后的可处理订单；其中，所述第二目标SKU信息为所述可处理订单的SKU信息中，所述订单满足率最大的筛选容器所满足的SKU信息。
  24. 根据权利要求23所述的订单处理方法，其中，所述在所述筛选容器集合中命中各所述可处理订单对应的筛选容器，还包括：
    确定所述更新后的筛选容器集合中各所述筛选容器对所述更新后的可处理订单的订单满足率；
    将所述更新后的筛选容器集合中，订单满足率最大的筛选容器，确定为第二命中容器，并将所述第二命中容器添加至所述命中容器集合。
  25. 根据权利要求24所述的订单处理方法，其中，所述在所述筛选容器集合中命中各所述可处理订单对应的筛选容器，还包括：
    当所述更新后的筛选容器集合中筛选容器对所述更新后的可处理订单的总体满足率为1时，将所述筛选容器确定为第三命中容器，并将所述第三命中容器添加至所述命中容器集合；
    将所述更新后的可处理订单设置为空集。
  26. 一种订单处理装置，包括：
    任务信息获取模块，用于获取订单任务信息；
    库存信息获取模块，用于获取库存中的容器的信息；
    分析计算模块，用于根据所述订单任务信息和所述容器的信息执行根据权利要求1-25中任一项所述的订单处理方法的步骤，以命中每个订单的容器；和
    输出模块，用于输出每个所述订单所命中的所述容器的信息。
  27. 一种电子设备，包括：
    一个或多个处理器；和
    存储器，用于存储一个或多个程序，
    其中，当所述一个或多个程序被所述一个或多个处理器执行时，所述一个或多个处理器实现根据权利要求1-25中任一项所述的订单处理方法。
  28. 一种计算机可读存储介质，其上存储有计算机程序，其中，当所述计算机程序被处理器执行时，实现根据权利要求1-25中任一项所述的订单处理方法。
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