Time information sending method and device, electronic equipment and computer readable medium

Abstract

Embodiments of the present disclosure disclose a time information sending method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises: determining a service type of an item corresponding to order operation information; determining a time period capacity ratio corresponding to each peak level of the service type, obtaining a time period peak classification information set; obtaining a store capacity information set and an occupied capacity information set of the service type; determining a delivery unit time period information of an order corresponding to the service type, and updating an occupied capacity value corresponding to the delivery unit time period information; and sending the delivery unit time period information to a target terminal. This embodiment sets different types of capacity in each delivery time period. Only when the capacity is sufficient, the user can successfully place an order. When the capacity is insufficient, the user needs to select other delivery time periods with sufficient capacity to place an order. This can achieve peak-shaving allocation of orders, and thus improve the delivery efficiency of orders.

Description

Technical Field

[0001] Embodiments of this disclosure relate to the field of computer technology, and more specifically to methods, apparatus, electronic devices, and computer-readable media for transmitting time information. Background Technology

[0002] With the rapid development of the new retail industry, the assessment of delivery capabilities by stores has become increasingly important. As business becomes more complex, the order volume for different types of business varies at different times, resulting in different demands for delivery capacity. Currently, the common method for controlling order volume for different types of business at different times is to manually estimate a standard delivery capacity value based on daily order volume at the store's terminals, thereby limiting delivery capacity during specific time periods to control store delivery capacity. When deducting delivery capacity, it is done according to the order of delivery time selected by the user.

[0003] However, when deducting delivery capacity directly based on the user's selected delivery time period using the above method, the following technical problems often arise:

[0004] First, the inability to stagger delivery times can easily lead to a situation where there are many delivery tasks during peak hours and few delivery tasks during off-peak hours, thereby reducing the efficiency of order delivery.

[0005] Second, it cannot consolidate orders, thus preventing the centralized packaging of items from orders of the same business type, which reduces packaging efficiency;

[0006] Third, when orders for a certain business type are placed during a peak delivery period, the delivery capacity during that time period will be squeezed, making it difficult to meet the delivery needs of other business types. Summary of the Invention

[0007] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0008] Some embodiments of this disclosure provide time information transmission methods, apparatuses, electronic devices, and computer-readable media to address one or more of the technical problems mentioned in the background section above.

[0009] In a first aspect, some embodiments of this disclosure provide a method for sending time information. The method includes: in response to detecting user order operation information, determining the business type of the item corresponding to the order operation information, wherein the order operation information includes delivery time period information pre-selected by the user; in response to determining that the business type requires capacity verification, determining the time period capacity ratio corresponding to each peak level of the business type, obtaining a time period peak level classification information set, wherein the time period peak level classification information in the time period peak level classification information set includes peak level and time period capacity ratio; acquiring a store capacity information set and a time period capacity occupancy information set for the business type, wherein the store capacity information in the store capacity information set includes: unit time period information, total capacity value, and unit peak level, and the time period capacity occupancy information in the time period capacity occupancy information set includes unit time period information and occupancy capacity value; in response to determining that the capacity for the business type is sufficient within the delivery time period information, determining the delivery unit time period information of the order corresponding to the business type based on the time period peak level classification information set, the store capacity information set, and the time period capacity occupancy information set, and updating the occupancy capacity value corresponding to the delivery unit time period information; and sending the delivery unit time period information to a target terminal.

[0010] In some embodiments, in response to determining that there is sufficient capacity for the service type within the delivery time period information, determining the delivery unit time period information for the order corresponding to the service type based on the time period peak level information set, the store capacity information set, and the occupied capacity information set includes:

[0011] From the set of store capacity information, select the store capacity information whose time period represented by the unit time period information is within the time period represented by the delivery time period information as the target store capacity information, and obtain the target store capacity information set.

[0012] The target store capacity information set is sorted to obtain a target store capacity information sequence.

[0013] Based on the peak time level information set and the target store capacity information sequence, the occupied capacity value corresponding to each target store capacity information in the target store capacity information sequence is checked and processed to obtain the check result;

[0014] In response to determining that the test result indicates that the capacity of the business type is sufficient within the delivery time period information, the unit time period information included in the occupied capacity information that meets the second preset condition is determined as the delivery unit time period information, wherein the second preset condition is that the occupied capacity value included in the occupied capacity information is less than the test value.

[0015] In some embodiments, the step of verifying the occupied capacity value corresponding to each target store's capacity information in the target store capacity information sequence based on the time-period peak level information set and the target store capacity information sequence, and obtaining the verification result, includes:

[0016] The product of the total capacity value included in the target store's capacity information and the proportion of capacity during the corresponding time period included in the time period peak classification information is determined as the test value;

[0017] In response to determining that the test value is greater than the corresponding occupied capacity value, the test result is updated to a value indicating that the capacity of the business type is sufficient within the delivery time period information, and the test process ends.

[0018] In response to determining that the test value is less than or equal to the corresponding occupied capacity value, the test result is updated to a value indicating insufficient capacity for the business type within the delivery time period information, and the test processing continues.

[0019] Secondly, some embodiments of this disclosure provide a time information transmission device, the device comprising: a first determining unit configured to, in response to detecting user order operation information, determine the service type of the item corresponding to the order operation information, wherein the order operation information includes delivery time period information pre-selected by the user; a second determining unit configured to, in response to determining that the service type requires capacity verification, determine the time period capacity ratio corresponding to each peak level of the service type, and obtain a time period peak level classification information set, wherein the time period peak level classification information in the time period peak level classification information set includes peak level and time period capacity ratio; and an acquiring unit configured to acquire a store capacity information set and the aforementioned service type. The set of occupied transportation capacity information, wherein the store transportation capacity information in the aforementioned store transportation capacity information set includes: unit time period information, total transportation capacity value, and unit peak level, and the occupied transportation capacity information in the aforementioned occupied transportation capacity information set includes unit time period information and occupied transportation capacity value; the determination and update unit is configured to, in response to determining that the transportation capacity of the aforementioned business type is sufficient within the aforementioned delivery time period information, determine the delivery unit time period information of the order corresponding to the aforementioned business type based on the aforementioned time period peak level information set, the aforementioned store transportation capacity information set, and the aforementioned occupied transportation capacity information set, and update the occupied transportation capacity value corresponding to the aforementioned delivery unit time period information; the sending unit is configured to send the aforementioned delivery unit time period information to the target terminal.

[0020] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0021] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

[0022] The above embodiments of this disclosure have the following beneficial effects: By using the time information sending method of some embodiments of this disclosure, different types of transportation capacity are set in each delivery time period. Only when the transportation capacity of a certain type of order is sufficient in the delivery time period selected by the user can the user successfully place an order. When the transportation capacity is insufficient, it is necessary to select other delivery time periods with sufficient transportation capacity to place an order. Thus, it is possible to achieve staggered allocation of orders, thereby improving the delivery efficiency of orders. Specifically, the reason for the low delivery efficiency of orders is that orders cannot be staggered, which easily leads to too many delivery tasks during peak hours and too few delivery tasks during off-peak hours. Based on this, the time information sending method of some embodiments of this disclosure. First, in response to detecting the user's order operation information, the business type of the item corresponding to the order operation information is determined, wherein the order operation information includes the delivery time period information pre-selected by the user. Thus, the business type of the order can be determined. Then, in response to determining that the business type requires transportation capacity verification, the time period transportation capacity ratio corresponding to each peak level of the business type is determined, and a time period peak level classification information set is obtained, wherein the time period peak level classification information in the time period peak level classification information set includes peak level and time period transportation capacity ratio. Therefore, by determining the proportion of orders for the aforementioned business types within each peak level, order distribution can be achieved, thereby realizing staggered order allocation and improving delivery efficiency. Next, a set of store capacity information and a set of occupied capacity information for the aforementioned business types are obtained. The store capacity information in the store capacity information set includes: unit time period information, total capacity value, and unit peak level; the occupied capacity information in the occupied capacity information set includes unit time period information and occupied capacity value. Thus, by obtaining the store capacity information for orders of the aforementioned business types, delivery time management for these orders can be achieved, making delivery personnel's delivery times more aligned with store staff scheduling, further improving delivery efficiency. Subsequently, in response to determining that there is sufficient capacity for the aforementioned business types within the aforementioned delivery time period information, the delivery unit time period information for the orders corresponding to the aforementioned business types is determined based on the aforementioned peak time period classification information set, the aforementioned store capacity information set, and the aforementioned occupied capacity information set, and the delivery unit time period information is updated accordingly. Therefore, by deducting delivery capacity within the available delivery time slots, the problem of reduced order volume for other service types due to orders of this service type crowding out delivery capacity during that time slot is avoided. Finally, the aforementioned delivery unit time slot information is sent to the target terminal. This reminds delivery personnel to deliver items within the specified delivery time slot in a timely manner, thereby improving the user experience.Because different types of delivery capacity are set for different delivery time periods, users can only place an order successfully when there is sufficient capacity for a certain type of order within the delivery time period selected by the user. When there is insufficient capacity, users need to choose other delivery time periods with sufficient capacity to place an order. This can achieve staggered allocation of orders and thus improve the delivery efficiency of orders. Attached Figure Description

[0023] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0024] Figure 1 This is a schematic diagram illustrating an application scenario of a time information transmission method according to some embodiments of this disclosure;

[0025] Figure 2 This is a flowchart of some embodiments of the time information transmission method according to this disclosure;

[0026] Figure 3 These are schematic diagrams illustrating the structure of some embodiments of the time information transmission apparatus according to this disclosure;

[0027] Figure 4 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0028] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0029] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0030] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0031] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0032] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0033] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0034] Figure 1 This is a schematic diagram illustrating an application scenario of a time information transmission method according to some embodiments of this disclosure.

[0035] exist Figure 1 In the application scenario, firstly, the computing device 101 can, in response to detecting the user's order operation information 102, determine the business type 103 of the item corresponding to the order operation information 102, wherein the order operation information 102 includes the user's pre-selected delivery time period information 1021. Then, in response to determining that the business type 103 requires capacity verification, the computing device 101 can determine the time period capacity ratio corresponding to each peak level of the business type 103, obtaining a time period peak level classification information set 104, wherein the time period peak level classification information in the time period peak level classification information set 104 includes peak level and time period capacity ratio. Next, the computing device 101 can obtain a store capacity information set 105 and a time period capacity occupancy information set 106 for the business type 103, wherein the store capacity information in the store capacity information set 105 includes: unit time period information, total capacity value, and unit peak level, and the time period capacity occupancy information in the time period capacity occupancy information set 106 includes unit time period information and occupancy capacity value. Subsequently, in response to determining that the delivery capacity of the aforementioned business type 103 is sufficient within the aforementioned delivery time period information 1021, the computing device 101 determines the delivery unit time period information 107 of the order corresponding to the aforementioned business type 103 based on the aforementioned peak time period classification information set 104, the aforementioned store capacity information set 105, and the aforementioned occupied capacity information set 106, and updates the occupied capacity value corresponding to the aforementioned delivery unit time period information 107. Finally, the computing device 101 can send the aforementioned delivery unit time period information 107 to the target terminal 108.

[0036] It should be noted that the aforementioned computing device 101 can be either hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the computing device is software, it can be installed within the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.

[0037] It should be understood that Figure 1 The number of computing devices shown is merely illustrative. Any number of computing devices can be used depending on implementation needs.

[0038] Continue to refer to Figure 2 The flowchart 200 illustrates some embodiments of a time information transmission method according to the present disclosure. This time information transmission method includes the following steps:

[0039] Step 201: In response to detecting the user's order operation information, determine the business type of the item corresponding to the order operation information.

[0040] In some embodiments, the execution subject of the time information sending method (such as...) Figure 1 The computing device 101 shown can, in response to detecting a user's order operation information, determine the business type of the item corresponding to the order operation information. The order operation information includes the delivery time period information pre-selected by the user. This delivery time period information represents the fulfillment time period selected by the user when placing the order. For example, the delivery time period information could be 9:00-10:30. The items corresponding to the order operation information have the same business type. This business type can be used to classify the items. For example, the business type could be a pre-order service, etc.

[0041] This allows us to determine the business type of the order.

[0042] Step 202: In response to the requirement of capacity verification for determining the business type, determine the time period capacity ratio corresponding to each peak level of the business type, and obtain a set of time period peak level classification information.

[0043] In some embodiments, the aforementioned executing entity may, in response to determining that the aforementioned business type requires capacity verification, determine the time-period capacity proportion corresponding to each peak level of the aforementioned business type within a preset time period, thereby obtaining a time-period peak grading information set. The preset time period can be the 7 days prior to the user's order placement time (excluding major promotions and special dates). The time-period peak grading information set includes peak level and time-period capacity proportion. The peak level is used to characterize the magnitude of capacity demand. The peak level can be divided into three levels: high, medium, and low. The capacity represents the order fulfillment capability. The time-period capacity proportion represents the proportion of the capacity value of the aforementioned business type to the total capacity value within the preset time period.

[0044] Therefore, by determining the proportion of orders of the above-mentioned business types in each peak level, it is possible to divert orders, thereby achieving staggered order allocation and improving delivery efficiency.

[0045] In some optional implementations of certain embodiments, the execution entity, in response to determining that the above-mentioned business type requires capacity verification, determines the time-period capacity proportion corresponding to each peak level of the above-mentioned business type, and obtains a time-period peak level classification information set, may include the following steps:

[0046] The first step is to obtain the updated peak level classification information for each time period, thus obtaining a set of updated peak level classification information.

[0047] The updated peak grading information for each unit time period can be obtained from the peak update pool to obtain an updated peak grading information set. The peak update pool can be a collection of peak gradings for each store within each unit time period. The updated peak grading information set includes unit time period information and peak level. The unit time period information can be time period information divided according to a preset time granularity. For example, the preset time granularity can be half an hour. The unit time period information can be 09:00-09:30. The updated peak grading information set can be {09:00-09:30: Low, 09:30-10:00: Medium, 10:00-10:30: Low}.

[0048] The second step is to group the updated peak level information in the above updated peak level information set according to the peak level, so as to obtain the updated peak level information group set.

[0049] In this context, each updated peak level information group in the aforementioned updated peak level information group set includes the same peak level. For example, the aforementioned updated peak level information group set could be {[09:00-09:30: Low, 10:00-10:30: Low], [09:30-10:00: Medium]}.

[0050] The third step is to determine the historical peak classification information group within each time unit of the preset time period based on the above updated peak classification information group set, thus obtaining the historical peak classification information group set.

[0051] The historical peak grading information set mentioned above includes peak level and historical capacity share. The preset time period is an integer multiple of the time unit mentioned above. For example, the time unit could be 1 day. The preset time period could be 7 days.

[0052] The fourth step is to determine the weighted average of the historical capacity proportions of the historical peak classification information with the same peak level in the above historical peak classification information set as the time period capacity proportion, thus obtaining the time period peak classification information set.

[0053] For example, the set of peak value classification information for the above time period can be {high: 20%, medium: 20%, low: 60%}.

[0054] Therefore, we can obtain the capacity allocation ratio of this business type of orders in each peak level within the preset time period.

[0055] In some optional implementations of certain embodiments, the execution entity determines the historical peak classification information group for each time unit within a preset time period based on the updated peak classification information group set, which may include the following steps:

[0056] The first step is to obtain the unit capacity value and the target capacity value corresponding to the above business type within each time period of the above time unit, thus obtaining a set of historical capacity information.

[0057] The historical capacity information set can be obtained from the capacity deduction data service pool by retrieving the unit capacity value of the target store within each unit time period and the target capacity value corresponding to the above business type. The capacity deduction data service pool can be a collection of the capacity values ​​occupied by each business type in the target store. The target store is the store where the user placed the order. The unit capacity value represents the sum of the capacity values ​​occupied by each business type. The target capacity value represents the capacity value occupied by the above business type. The historical capacity information in the historical capacity information set includes unit time period information, unit capacity value, and target capacity value. For example, the historical capacity information set could be {09:00-09:30 / / 30 / / 15, 09:30-10:00 / / 40 / / 15, 10:00-10:30 / / 50 / / 25}. The above 09:00-09:30, 09:30-10:00, and 10:00-10:30 are unit time periods. The above 30, 40, and 50 are unit capacity values. The above 15, 15, and 25 are target capacity values.

[0058] The second step is to use each updated peak level information group in the above-mentioned updated peak level information group set to determine the sum of the unit capacity values ​​of each historical capacity information that meets the first preset condition in the above-mentioned historical capacity information set as the historical total capacity value.

[0059] The first preset condition is that the unit time period information included in the historical capacity information is the same as the unit time period information included in any of the updated peak classification information in the updated peak classification information group.

[0060] As an example, the above set of updated peak level classification information groups can be {[09:00-09:30: Low, 10:00-10:30: Low], [09:30-10:00: Medium]}. The above set of historical capacity information can be {09:00-09:30 / / 30 / / 15, 09:30-10:00 / / 40 / / 15, 10:00-10:30 / / 50 / / 25}. The sum of the unit capacity values ​​of 30 and 50 within the time periods of 09:00-09:30 and 10:00-10:30, which satisfy the information [09:00-09:30 / / 30 / / 15, 09:30-10:00 / / 40 / / 15, 10:00-10:30 / / 50 / / 25], can be used to determine the first historical total capacity value. The unit capacity value of 40 that satisfies the unit time period information of 09:30-10:00 can be determined as the second historical total capacity value by using [09:30-10:00: Middle].

[0061] The third step is to use each updated peak level information group in the above-mentioned updated peak level information group set to determine the sum of the target capacity values ​​in each historical capacity information that meets the first preset condition in the above-mentioned historical capacity information set as the historical target total capacity value.

[0062] As an example, the above set of updated peak level classification information groups can be {[09:00-09:30: Low, 10:00-10:30: Low], [09:30-10:00: Medium]}. The above set of historical capacity information can be {09:00-09:30 / / 30 / / 15, 09:30-10:00 / / 40 / / 15, 10:00-10:30 / / 50 / / 25}. The first historical target total capacity value can be determined by using the historical capacity information of {09:00-09:30: low, 10:00-10:30: low}, which includes the target capacity values ​​of 15 and 25, and 40, within the time period information of 09:00-09:30 and 10:00-10:30. The target capacity value of 15 included in the historical capacity information of {09:00-09:30 / / 30 / / 15, 09:30-10:00 / / 40 / / 15, 10:00-10:30 / / 50 / / 25} that satisfies the unit time period information of 09:30-10:00 can be used as the second historical target total capacity value.

[0063] The fourth step is to determine the historical capacity percentage by taking the total historical target capacity value and the ratio of the total historical target capacity value to the total historical capacity value corresponding to the same updated peak level information group. This results in a set of historical capacity percentages.

[0064] As an example, the historical target total capacity values ​​obtained above can be {40, 15}. The historical target total capacity value 40 is determined by the sum of target capacity values ​​15 and 25 included in the historical capacity information for the unit time periods 09:00-09:30 and 10:00-10:30. Therefore, the updated peak load classification information group corresponding to the historical target total capacity value 40 is [09:00-09:30: Low, 10:00-10:30: Low]. The historical target total capacity value 15 is determined by the target capacity value 15 included in the historical capacity information for the unit time period 09:30-10:00. Therefore, the updated peak load classification information group corresponding to the historical target total capacity value 15 is [09:30-10:00: Medium]. The historical total capacity values ​​obtained above can be {80, 40}. The aforementioned historical total capacity value of 80 is determined by the sum of unit capacity values ​​of 30 and 50 included in the historical capacity information for the unit time periods of 09:00-09:30 and 10:00-10:30. Therefore, the updated peak load classification information group corresponding to the aforementioned historical total capacity value of 80 is [09:00-09:30: Low, 10:00-10:30: Low]. The aforementioned historical total capacity value of 40 is determined by the unit capacity value of 40 included in the historical capacity information for the unit time period of 09:30-10:00. Therefore, the updated peak load classification information group corresponding to the aforementioned historical total capacity value of 40 is [09:30-10:00: Medium]. Therefore, the ratio of 50% between the historical target total capacity value of 40 and the historical total capacity value of 80, corresponding to the updated peak classification information group [09:00-09:30: Low, 10:00-10:30: Low], can be determined as the first historical capacity share, and the ratio of 37.5% between the historical target total capacity value of 15 and the historical total capacity value of 40, corresponding to the updated peak classification information group [09:30-10:00: Medium], can be determined as the second historical capacity share, resulting in the set of historical capacity shares as {50%, 37.5%}.

[0065] The fifth step is to determine each historical capacity share and its corresponding peak level in the above historical capacity share set as historical peak level information, thus obtaining a historical peak level information group.

[0066] Each historical capacity share in the above historical capacity share set and the peak level included in the updated peak level information in the corresponding updated peak level information group can be determined as historical peak level information, thus obtaining the historical peak level information group.

[0067] As an example, the historical capacity percentage set above is {50%, 37.5%}. The historical capacity percentage of 50% can be determined as the historical peak level information "Low: 50%" by combining the peak level "Low" included in the updated peak level information groups [09:00-09:30: Low, 10:00-10:30: Low] with the peak level "Medium" included in the updated peak level information group [09:30-10:00: Medium]. Similarly, the historical capacity percentage of 37.5% can be determined as the historical peak level information "Medium: 37.5%" by combining the peak level "Medium" included in the updated peak level information group [09:30-10:00: Medium]. This yields the historical peak level information group [Low: 50%, Medium: 37.5%].

[0068] Therefore, we can obtain the capacity allocation of orders for this business type corresponding to each peak level within each time unit.

[0069] Step 203: Obtain the set of store capacity information and the set of capacity occupancy information for business types.

[0070] In some embodiments, the aforementioned executing entity may obtain from the capacity pool a set of store capacity information for the target store on the day of the aforementioned delivery time period, and from the capacity deduction data service pool a set of capacity occupancy information for the aforementioned business type on the day of the aforementioned delivery time period. The capacity pool may include a set of capacity information for each store within each unit time period. The store capacity information in the aforementioned store capacity information set includes: unit time period information, total capacity value, and unit peak level. The capacity occupancy information in the aforementioned capacity occupancy information set includes unit time period information and capacity occupancy value.

[0071] Therefore, by obtaining the store's delivery capacity information and the set of delivery capacity occupancy information for the above-mentioned business types, it is possible to manage the delivery time of the above-mentioned business types of orders, so that the delivery time of delivery personnel is more in line with the store's personnel scheduling, thereby improving delivery efficiency.

[0072] Step 204: In response to the determination that there is sufficient capacity for the business type within the delivery time period information, the delivery unit time period information of the order corresponding to the business type is determined based on the time period peak level information set, the store capacity information set, and the occupied capacity information set, and the occupied capacity value corresponding to the delivery unit time period information is updated.

[0073] In some embodiments, the executing entity may, in response to determining that the capacity of the business type is sufficient within the delivery time period information, select the occupied capacity information from the occupied capacity information set whose time period represented by the unit time period information is within the time period represented by the delivery time period information, and sequentially verify whether the occupied capacity information meets the deduction conditions according to the order of the unit time period information. The unit time period information included in the first occupied capacity information that meets the deduction conditions is determined as the delivery unit time period information of the order corresponding to the business type. The deduction conditions are that the occupied capacity value included in the occupied capacity information is less than the product of the total capacity value included in the store capacity information within the same unit time period information and the proportion of time period capacity included in the time period peak classification information. Furthermore, the occupied capacity value included in the occupied capacity information with the same unit time period information as the delivery unit time period information is updated to the sum of the occupied capacity value and a preset capacity value. The preset capacity value can be a pre-set unit capacity deduction value. For example, the preset capacity value can be 1.

[0074] Therefore, by performing a deduction operation on the delivery capacity within the time period information where there is sufficient capacity, the problem of a decrease in the order volume of other business types due to the crowding out of the delivery capacity during that delivery period is avoided.

[0075] Optionally, in response to determining that there is sufficient transportation capacity for the aforementioned business type within the aforementioned delivery time period information, the aforementioned executing entity determines the delivery unit time period information for the orders corresponding to the aforementioned business type based on the aforementioned peak time period classification information set, the aforementioned store transportation capacity information set, and the aforementioned occupied transportation capacity information set. This may include the following steps:

[0076] The first step is to select, from the above set of store capacity information, the store capacity information whose time period represented by the unit time period information falls within the time period represented by the above delivery time period information as the target store capacity information, thus obtaining the target store capacity information set.

[0077] As an example, the above set of store delivery capacity information can be {08:00-08:30 / / 100 / / High, 08:30-09:00 / / 100 / / Medium, 09:00-09:30 / / 100 / / Low, 09:30-10:00 / / 100 / / High}. The above delivery time period information can be 9:00-10:00. The resulting set of target store delivery capacity information is {09:00-09:30 / / 100 / / Low, 09:30-10:00 / / 100 / / High}.

[0078] The second step is to sort the above set of target store capacity information to obtain a sequence of target store capacity information.

[0079] First, the target store capacity information set can be grouped and arranged according to the unit peak level of high, medium, and low, resulting in a sequence of store capacity information groups. Then, in response to determining that the preset capacity deduction method is sequential deduction, the capacity information of each store in each store capacity information group sequence is sorted according to the chronological order of the unit time periods included in the store capacity information, resulting in a target store capacity information sequence. Alternatively, in response to determining that the preset capacity deduction method is random deduction, the capacity information of each store in each store capacity information group sequence is randomly sorted, resulting in a target store capacity information sequence. For example, the target store capacity information set is {09:00-09:30 / / 100 / / Low / / 10, 09:30-10:00 / / 100 / / High / / 70}. The preset capacity deduction method is sequential deduction. After sorting the above target store capacity information set according to the unit peak level of high, medium and low, the target store capacity information sequence is obtained as "09:30-10:00 / / 100 / / high, 09:00-09:30 / / 100 / / low".

[0080] The third step involves verifying the occupied capacity value corresponding to each target store's capacity information in the above-mentioned target store capacity information sequence based on the above-mentioned peak time period classification information set and the above-mentioned target store capacity information sequence, and obtaining the verification results.

[0081] Based on the above-mentioned peak time period classification information set and the above-mentioned target store capacity information sequence, the occupied capacity value included in the occupied capacity information corresponding to each target store capacity information in the above-mentioned target store capacity information sequence can be verified to obtain the verification result.

[0082] Fourth, in response to the determination that the above test results indicate that the capacity of the above business type is sufficient within the above delivery time period information, the unit time period information included in the capacity occupancy information that meets the second preset condition is determined as the delivery unit time period information.

[0083] The second preset condition is that the occupied capacity value included in the occupied capacity information is less than the test value.

[0084] The above steps and related content, as an inventive point of this disclosure, solve the second technical problem mentioned in the background art: "The inability to consolidate orders, thus preventing the centralized packaging of items in orders of the same business type, reduces packaging efficiency." The factors leading to low packaging efficiency are as follows: the inability to consolidate orders, thus preventing the centralized packaging of items in orders of the same business type. Solving these factors can improve packaging efficiency. To achieve this effect, this disclosure, by sorting and then deducting the target store's delivery capacity information, can consolidate orders, thereby enabling the items in an order to be packaged centrally within a time period, improving packaging efficiency.

[0085] Optionally, the aforementioned executing entity verifies the occupied capacity value corresponding to each target store's capacity information in the aforementioned target store capacity information sequence based on the aforementioned peak time period classification information set and the aforementioned target store capacity information sequence, and obtains the verification result, which may include the following steps:

[0086] The first step is to determine the above-mentioned test value by multiplying the total capacity value included in the target store's capacity information by the corresponding peak time period classification information for the time period's capacity percentage.

[0087] The product of the total capacity value included in the above target store capacity information and the proportion of time period capacity included in the peak level information that is the same as the unit peak level included in the above target store capacity information can be determined as the above test value.

[0088] As an example, the peak time period classification information mentioned above can be "High: 20%". The target store capacity information mentioned above can be "09:30-10:00 / / 100 / / High". The total capacity value included in the target store capacity information mentioned above is 100. The product of the total capacity value "100" included in the target store capacity information "09:30-10:00 / / 100 / / High" and the time period capacity percentage "20%" included in the peak time period classification information "High: 20%" which has the same peak level as the target store capacity information mentioned above is 20, can be determined as the above verification value.

[0089] The second step is to update the test result to a value indicating that the above test value is greater than the corresponding occupied capacity value, and then end the test process.

[0090] In response to determining that the above test value is greater than the occupied capacity value included in the occupied capacity information within the same unit time period, the above test result can be updated to a value indicating that the above business type has sufficient capacity within the above delivery time period information, and the test process can be terminated.

[0091] As an example, the target store's delivery capacity information could be "09:00-09:30 / / 100 / / Low". The peak time grading information could be "Low: 60%". The check value could be 60. The occupied delivery capacity information could be "09:00-09:30 / / 10". In response to determining that the check value 60 is greater than the occupied delivery capacity value of 10 included in the occupied delivery capacity information "09:00-09:30 / / 10" within the same unit time period "09:00-09:30", the check result could be updated to a value indicating sufficient delivery capacity for the aforementioned delivery time period, and the check process could end.

[0092] This allows us to determine the delivery timeframes when there is sufficient capacity.

[0093] Third, in response to determining that the above test value is less than or equal to the corresponding occupied capacity value, the above test result is updated to a value indicating insufficient capacity for the above business type within the above delivery time period information, and the test processing continues.

[0094] In response to determining that the above test value is less than or equal to the occupied capacity value included in the occupied capacity information within the same unit time period, the above test result can be updated to a value indicating insufficient capacity for the above business type within the above delivery time period information, and the test processing can continue.

[0095] As an example, the target store's delivery capacity information could be "09:30-10:00 / / 100 / / High". The peak time grading information could be "High: 20%". The check value could be 20. The occupied delivery capacity information could be "09:30-10:00 / / 70". In response to determining that the check value 20 is less than or equal to the occupied delivery capacity value of 70 included in the occupied delivery capacity information "09:30-10:00 / / 70" within the same unit time period "09:30-10:00", the check result could be updated to a value indicating insufficient delivery capacity for the aforementioned delivery time period, and the check process could continue.

[0096] The above steps and related content, as an inventive point of this disclosure, solve the third technical problem mentioned in the background art: "When orders of a certain business type are in a peak ordering period during a certain delivery time, the delivery capacity during that delivery time period will be squeezed, making it difficult to meet the delivery needs of other business types." The factors that cause the delivery needs of other business types to be difficult to meet are as follows: orders of a certain business type squeeze the delivery capacity during that delivery time period. If the above factors are resolved, the delivery needs of other business types can be met. To achieve this effect, this disclosure does not deduct delivery capacity within a unit time period when the delivery capacity of the aforementioned business type is insufficient, thus avoiding the situation where orders of the aforementioned business type squeeze the delivery capacity during that delivery time period and meeting the delivery needs of other business types.

[0097] Step 205: Send the delivery unit time period information to the target terminal.

[0098] In some embodiments, the aforementioned executing entity may send the aforementioned delivery unit time period information to the target terminal.

[0099] This can remind delivery personnel to deliver items in a timely manner within a given delivery time, thereby improving the user experience.

[0100] Optionally, the aforementioned implementing entity may also perform the following steps:

[0101] The first step is to send information indicating insufficient capacity to the user terminal in response to the determination that there is insufficient capacity for the above-mentioned business type within the above-mentioned delivery time period.

[0102] In response to determining that there is insufficient capacity for the above-mentioned business type within the aforementioned delivery time period, information indicating insufficient capacity can be sent to the user terminal so that the user can reselect the delivery time period information.

[0103] Therefore, when the delivery capacity within the time slot selected by the user is insufficient, the user is prompted that the order has failed. This can prevent this type of order from crowding out the delivery capacity within that time slot, thereby increasing the order volume of other business types.

[0104] Optionally, before the aforementioned executing entity detects the user's order operation information and determines the business type of the item corresponding to the order operation information, it may also perform the following steps:

[0105] The first step is to determine the user's delivery address in response to the detected browsing activity information of the aforementioned delivery time period.

[0106] It can obtain the delivery address selected by the user in response to the detection of the user's browsing operation information of the above delivery time period.

[0107] The second step, in response to determining that the above delivery address is within the order delivery range, is to determine whether the capacity of the above business type is sufficient within each unit time period information in each preset display time period information set.

[0108] The aforementioned order delivery range refers to the pre-set delivery address range for the order.

[0109] The third step is to send the preset display time period information that meets the display conditions from the above preset display time period information set to the above user terminal.

[0110] The preset display time slots that meet the display conditions from the aforementioned set of preset display time slot information can be sent to the aforementioned user terminal so that the user can select delivery time slot information. The aforementioned display conditions are that within at least one unit of time slot information, the capacity for the aforementioned service type is sufficient.

[0111] Therefore, by sending the preset display time period information of sufficient transportation capacity to the user terminal, orders can be diverted to the unit time period with sufficient transportation capacity for delivery, thereby realizing the diversion of orders and improving the delivery efficiency of orders.

[0112] The above embodiments of this disclosure have the following beneficial effects: By using the time information sending method of some embodiments of this disclosure, different types of transportation capacity are set in each delivery time period. Only when the transportation capacity of a certain type of order is sufficient in the delivery time period selected by the user can the user successfully place an order. When the transportation capacity is insufficient, it is necessary to select other delivery time periods with sufficient transportation capacity to place an order. Thus, it is possible to achieve staggered allocation of orders, thereby improving the delivery efficiency of orders. Specifically, the reason for the low delivery efficiency of orders is that orders cannot be staggered, which easily leads to too many delivery tasks during peak hours and too few delivery tasks during off-peak hours. Based on this, the time information sending method of some embodiments of this disclosure. First, in response to detecting the user's order operation information, the business type of the item corresponding to the order operation information is determined, wherein the order operation information includes the delivery time period information pre-selected by the user. Thus, the business type of the order can be determined. Then, in response to determining that the business type requires transportation capacity verification, the time period transportation capacity ratio corresponding to each peak level of the business type is determined, and a time period peak level classification information set is obtained, wherein the time period peak level classification information in the time period peak level classification information set includes peak level and time period transportation capacity ratio. Therefore, by determining the proportion of orders for the aforementioned business types within each peak level, order distribution can be achieved, thereby realizing staggered order allocation and improving delivery efficiency. Next, a set of store capacity information and a set of occupied capacity information for the aforementioned business types are obtained. The store capacity information in the store capacity information set includes: unit time period information, total capacity value, and unit peak level; the occupied capacity information in the occupied capacity information set includes unit time period information and occupied capacity value. Thus, by obtaining the store capacity information for orders of the aforementioned business types, delivery time management for these orders can be achieved, making delivery personnel's delivery times more aligned with store staff scheduling, further improving delivery efficiency. Subsequently, in response to determining that there is sufficient capacity for the aforementioned business types within the aforementioned delivery time period information, the delivery unit time period information for the orders corresponding to the aforementioned business types is determined based on the aforementioned peak time period classification information set, the aforementioned store capacity information set, and the aforementioned occupied capacity information set, and the delivery unit time period information is updated accordingly. Therefore, by deducting delivery capacity within the available delivery time slots, the problem of reduced order volume for other service types due to orders of this service type crowding out delivery capacity during that time slot is avoided. Finally, the aforementioned delivery unit time slot information is sent to the target terminal. This reminds delivery personnel to deliver items within the specified delivery time slot in a timely manner, thereby improving the user experience.Because different types of delivery capacity are set for different delivery time periods, users can only place an order successfully when there is sufficient capacity for a certain type of order within the delivery time period selected by the user. When there is insufficient capacity, users need to choose other delivery time periods with sufficient capacity to place an order. This can achieve staggered allocation of orders and thus improve the delivery efficiency of orders.

[0113] Further reference Figure 3 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of a time information transmission device, which are similar to... Figure 2 Corresponding to the method embodiments shown, the device can be specifically applied to various electronic devices.

[0114] like Figure 3 As shown, the time information sending device 300 in some embodiments includes: a first determining unit 301, a second determining unit 302, an acquiring unit 303, a determining and updating unit 304, and a sending unit 305. The first determining unit 301 is configured to, in response to detecting a user's order operation information, determine the service type of the item corresponding to the order operation information, wherein the order operation information includes delivery time period information pre-selected by the user. The second determining unit 302 is configured to, in response to determining that the service type requires capacity verification, determine the time period capacity ratio corresponding to each peak level of the service type, obtaining a time period peak level classification information set, wherein the time period peak level classification information in the time period peak level classification information set includes peak level and time period capacity ratio. The acquiring unit 303 is configured to acquire a store capacity information set and a service type occupied capacity information set, wherein the store capacity information in the store capacity information set includes: unit time period information, total capacity value, and unit peak level, and the occupied capacity information in the occupied capacity information set includes unit time period information and occupied capacity value. The determination and update unit 304 is configured to, in response to determining that there is sufficient capacity for the aforementioned business type within the aforementioned delivery time period information, determine the delivery unit time period information for the order corresponding to the aforementioned business type based on the aforementioned peak time period classification information set, the aforementioned store capacity information set, and the aforementioned occupied capacity information set, and update the occupied capacity value corresponding to the aforementioned delivery unit time period information. The sending unit 305 is configured to send the aforementioned delivery unit time period information to the target terminal.

[0115] It is understandable that the units described in the device 300 are related to the reference. Figure 2 The steps in the described method correspond accordingly. Therefore, the operations, features, and beneficial effects described above for the method also apply to the device 300 and the units contained therein, and will not be repeated here.

[0116] The following is for reference. Figure 4It illustrates electronic devices suitable for implementing some embodiments of the present disclosure (such as...). Figure 1 The diagram shows the structure of the computing device 101)400. Figure 4 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0117] like Figure 4 As shown, electronic device 400 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 401, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 402 or a program loaded from storage device 408 into random access memory (RAM) 403. RAM 403 also stores various programs and data required for the operation of electronic device 400. Processing device 401, ROM 402, and RAM 403 are interconnected via bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0118] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows electronic device 400 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 An electronic device 400 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 4 Each box shown can represent a device or multiple devices as needed.

[0119] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 409, or installed from storage device 408, or installed from ROM 402. When the computer program is executed by processing device 401, it performs the functions defined above in the methods of some embodiments of this disclosure.

[0120] It should be noted that, in some embodiments of this disclosure, the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, 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 thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0121] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0122] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: In response to detecting user order operation information, determine the business type of the item corresponding to the order operation information, wherein the order operation information includes the user's pre-selected delivery time period information; In response to determining that the business type requires capacity verification, determine the time-period capacity ratio corresponding to each peak level of the business type, obtaining a time-period peak level classification information set, wherein the time-period peak level classification information in the time-period peak level classification information set includes peak level and time-period capacity ratio; Obtain a store capacity information set and a time-occupied capacity information set for the aforementioned business type, wherein the store capacity information in the store capacity information set includes: unit time period information, total capacity value, and unit peak level, and the time-occupied capacity information in the time-occupied capacity information set includes unit time period information and time-occupied capacity value. In response to the determination that there is sufficient transportation capacity for the aforementioned business type within the aforementioned delivery time period, the delivery unit time period information for the orders corresponding to the aforementioned business type is determined based on the aforementioned peak time period classification information set, the aforementioned store transportation capacity information set, and the aforementioned occupied transportation capacity information set. The occupied transportation capacity value corresponding to the aforementioned delivery unit time period information is then updated. The aforementioned delivery unit time period information is then sent to the target terminal.

[0123] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0124] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0125] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including a first determining unit, a second determining unit, an acquiring unit, a determining and updating unit, and a sending unit. The names of these units do not necessarily limit the specific unit; for example, the sending unit may also be described as "a unit that sends delivery unit time period information to a target terminal."

[0126] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0127] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for sending time information, comprising: In response to detecting user order information, the service type of the item corresponding to the order information is determined, wherein the order information includes the delivery time period information pre-selected by the user; In response to the determination that the service type requires capacity verification, the time-period capacity proportion corresponding to each peak level of the service type is determined, resulting in a time-period peak level classification information set. The time-period peak level classification information set includes peak level and time-period capacity proportion, including: The updated peak classification information of each unit time period is obtained to obtain an updated peak classification information set, wherein the updated peak classification information in the updated peak classification information set includes unit time period information and peak level; Based on the peak level, the updated peak level information in the updated peak level information set is grouped to obtain an updated peak level information group set, wherein each updated peak level information in each updated peak level information group in the updated peak level information group set includes the same peak level. Based on the updated peak classification information group set, the historical peak classification information group within each time unit of the preset time period is determined to obtain the historical peak classification information group set, wherein the historical peak classification information in the historical peak classification information group set includes peak level and historical capacity ratio; The weighted average of the historical capacity proportions of historical peak classification information with the same peak level in the historical peak classification information group set is determined as the time period capacity proportion, thus obtaining the time period peak classification information set. Obtain a set of store capacity information and a set of occupancy capacity information for the business type. The store capacity information in the set of store capacity information includes: unit time period information, total capacity value, and unit peak level. The occupancy capacity information in the set of occupancy capacity information includes unit time period information and occupancy capacity value. In response to determining that there is sufficient transportation capacity for the business type within the delivery time period information, the delivery unit time period information for the order corresponding to the business type is determined based on the time period peak level information set, the store transportation capacity information set, and the occupied transportation capacity information set, and the occupied transportation capacity value corresponding to the delivery unit time period information is updated; The delivery unit time period information is sent to the target terminal.

2. The method according to claim 1, wherein, The step of determining the historical peak classification information group for each time unit within a preset time period based on the updated peak classification information group set includes: Obtain the unit capacity value and the target capacity value corresponding to the business type within each unit time period information within the time unit to obtain a historical capacity information set, wherein the historical capacity information in the historical capacity information set includes unit time period information, unit capacity value and target capacity value; Using each updated peak classification information group in the updated peak classification information group set, the sum of the unit capacity values ​​in each historical capacity information that meets the first preset condition in the historical capacity information set is determined as the historical total capacity value, wherein the first preset condition is that the unit time period information included in the historical capacity information is the same as the unit time period information included in any updated peak classification information in the updated peak classification information group. Using each updated peak classification information group in the updated peak classification information group set, the sum of the target capacity values ​​in each historical capacity information that meets the first preset condition in the historical capacity information set is determined as the historical target total capacity value; The historical capacity ratio is determined by the ratio of the historical target total capacity value and the historical total capacity value corresponding to the same updated peak level information group among the obtained historical total capacity values, thus obtaining the historical capacity ratio set. Each historical capacity share in the historical capacity share set and its corresponding peak level are determined as historical peak level information, thus obtaining a historical peak level information group.

3. The method according to claim 1, wherein, The method further includes: In response to determining that there is insufficient capacity for the service type within the delivery time period information, information indicating insufficient capacity is sent to the user terminal.

4. The method according to claim 1, wherein, Before determining the business type of the item corresponding to the order operation information in response to detecting the user's order operation information, the method further includes: In response to detecting user browsing activity information related to the delivery time period, the user's delivery address is determined; In response to determining that the delivery address is within the order delivery range, determine whether the transportation capacity of the business type is sufficient within each unit time period information in each preset display time period information set; The preset display time period information that meets the display conditions from the preset display time period information set is sent to the user terminal, wherein the display conditions are that the service type has sufficient capacity within at least one unit time period information within the preset display time period information.

5. A time information transmission device, comprising: The first determining unit is configured to determine the business type of the item corresponding to the order operation information in response to detecting the user's order operation information, wherein the order operation information includes the delivery time period information pre-selected by the user; The second determining unit is configured to, in response to determining that the service type requires capacity verification, determine the time-period capacity proportion corresponding to each peak level of the service type, and obtain a time-period peak level classification information set, wherein the time-period peak level classification information set includes peak level and time-period capacity proportion, including: obtaining updated peak level classification information for each unit time period, obtaining an updated peak level classification information set, wherein the updated peak level classification information set includes unit time period information and peak level; and grouping the updated peak level classification information in the updated peak level classification information set according to the peak level, to obtain updated peak level classification information. A set of updated peak level information groups is defined, wherein each updated peak level information group in the updated peak level information group includes the same peak level; based on the updated peak level information group set, historical peak level information groups are determined for each time unit within a preset time period, resulting in a set of historical peak level information groups, wherein the historical peak level information in the set of historical peak level information groups includes peak level and historical capacity share; the weighted average of the historical capacity shares included in the historical peak level information groups with the same peak level is determined as the time period capacity share, resulting in a set of time period peak level information groups; The acquisition unit is configured to acquire a set of store capacity information and a set of occupancy capacity information for the business type. The store capacity information in the set of store capacity information includes: unit time period information, total capacity value, and unit peak level. The occupancy capacity information in the set of occupancy capacity information includes unit time period information and occupancy capacity value. The determination and update unit is configured to, in response to determining that there is sufficient capacity for the business type within the delivery time period information, determine the delivery unit time period information of the order corresponding to the business type based on the time period peak classification information set, the store capacity information set, and the occupied capacity information set, and update the occupied capacity value corresponding to the delivery unit time period information; The sending unit is configured to send the delivery unit time period information to the target terminal.

6. An electronic device, comprising: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1 to 4.

7. A computer-readable medium having a computer program stored thereon, wherein, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 4.

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