CN110737525B - Task processing method and device, electronic equipment and storage medium - Google Patents

Task processing method and device, electronic equipment and storage medium Download PDF

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Publication number
CN110737525B
CN110737525B CN201910995530.7A CN201910995530A CN110737525B CN 110737525 B CN110737525 B CN 110737525B CN 201910995530 A CN201910995530 A CN 201910995530A CN 110737525 B CN110737525 B CN 110737525B
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delivery
processor
current
calculation
task
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CN110737525A (en
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叶长隆
张彬
孔垂建
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Rajax Network Technology Co Ltd
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Rajax Network Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/485—Task life-cycle, e.g. stopping, restarting, resuming execution
    • 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
    • G06Q10/083—Shipping

Abstract

The embodiment of the disclosure discloses a task processing method and device, electronic equipment and a storage medium. The method comprises the following steps: in response to a preset trigger event, acquiring current distribution data of a target distribution task through at least one processor; updating the closing time of the target distribution task through at least one processor according to preset configuration information and the current distribution data; the preset configuration information is used for configuring a mode of determining the closing time according to the current distribution data; and setting the target delivery task to be in a closed state through at least one processor in response to the current time reaching the updated closing time of the target delivery task. Through the embodiment of the disclosure, when the preset trigger event occurs, the closing time of the delivery task can be updated in time according to the current delivery condition, so that the updated closing time can be more reasonable, and the problems of low transport scheduling efficiency and the like caused by unreasonable closing time are avoided.

Description

Task processing method and device, electronic equipment and storage medium
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a task processing method and apparatus, an electronic device, and a storage medium.
Background
Current logistics can be divided into traditional express logistics and instant logistics, and the instant logistics is different from the traditional express logistics in distribution mode, timeliness requirement and logistics links. Since the demand of the instant logistics on the aging is very high, the management of the closing time of the timely delivery tasks is particularly important. If the closing time of the timely delivery tasks is unreasonable, and a large number of delivery tasks which are not closed due to overtime exist in the timely delivery system, the overall delivery efficiency of the timely delivery system is reduced.
Disclosure of Invention
The embodiment of the disclosure provides a task processing method and device, electronic equipment and a storage medium.
In a first aspect, an embodiment of the present disclosure provides a task processing method.
Specifically, the task processing method includes:
in response to a preset trigger event, acquiring current distribution data of a target distribution task through at least one processor;
updating the closing time of the target distribution task through at least one processor according to preset configuration information and the current distribution data; the preset configuration information is used for configuring a mode of determining the closing time according to the current distribution data;
and setting the target delivery task to be in a closed state through at least one processor in response to the current time reaching the updated closing time of the target delivery task.
With reference to the first aspect, in a first implementation manner of the first aspect, the preset trigger event includes a delivery status change event and/or an abnormal event of the target delivery task; and/or the presence of a gas in the gas,
the current delivery data includes delivery status, delivery time, line of fortune, weather data, and/or abnormal events of the target delivery task.
With reference to the first aspect and/or the first implementation manner of the first aspect, in a second implementation manner of the first aspect, the updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data includes:
when the preset trigger event is an abnormal event, determining the current abnormal event in the current distribution data through at least one processor;
determining a first calculation mode under the current abnormal event in the preset configuration information through at least one processor;
determining, by at least one processor, a first calculation factor in the first calculation mode based on the current delivery data;
determining, by at least one processor, the turn-off time based on the first calculation factor and the first calculation.
With reference to the first aspect, the first implementation manner of the first aspect, and/or the second implementation manner of the first aspect, in a third implementation manner of the first aspect, the updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data includes:
when the preset trigger event is a distribution state change event, determining the current distribution state of the target distribution task through at least one processor according to the current distribution data;
determining a second calculation mode in the preset configuration information under the current distribution state through at least one processor;
determining, by at least one processor, a second calculation factor in the second calculation mode based on the current delivery data;
determining, by at least one processor, the turn-off time based on the second calculation factor and the second calculation.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, and/or the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data includes:
and comparing the current distribution data with the matching conditions corresponding to the calculation branches in the preset configuration information through at least one processor, and determining the closing time according to the calculation modes corresponding to the calculation branches when the comparison is consistent.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, and/or the fourth implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the comparing, by at least one processor, the current delivery data with a matching condition corresponding to a calculation branch in the preset configuration information, and when the comparison is consistent, determining the closing time according to a calculation manner corresponding to the calculation branch includes:
determining, by at least one processor, a first computation branch in the preset configuration information that matches a current delivery status or a current abnormal event in the current delivery data;
determining, by at least one processor, a second of the first computational branches that matches a capacity line in the current delivery data;
determining, by at least one processor, a third one of the second calculation branches that matches weather data in the current delivery data;
determining, by at least one processor, a delivery time in the current delivery data that matches the configuration in the third computing branch;
determining, by at least one processor, the closing time based on the delivery time.
In a second aspect, an embodiment of the present disclosure provides a task processing device.
Specifically, the task processing device includes:
the system comprises a first response module, a first display module and a second display module, wherein the first response module is configured to respond to a preset trigger event and acquire current distribution data of a target distribution task through at least one processor;
the updating module is configured to update the closing time of the target delivery task according to preset configuration information and the current delivery data through at least one processor; the preset configuration information is used for configuring a mode of determining the closing time according to the current distribution data;
a second response module configured to set, by the at least one processor, the target delivery task to a closed state in response to the current time reaching the updated closing time of the target delivery task.
With reference to the second aspect, in a first implementation manner of the second aspect, the preset trigger event includes a delivery status change event and/or an abnormal event of the target delivery task; and/or the presence of a gas in the gas,
the current delivery data includes delivery status, delivery time, line of fortune, weather data, and/or abnormal events of the target delivery task.
With reference to the second aspect and/or the first implementation manner of the second aspect, in a second implementation manner of the second aspect, the update module includes:
a first determining submodule configured to determine, by at least one processor, a current abnormal event in the current delivery data when the preset trigger event is an abnormal event;
the second determining submodule is configured to determine, through at least one processor, a first calculation mode under the current abnormal event in the preset configuration information;
a third determining submodule configured to determine, by at least one processor, a first calculation factor in the first calculation manner according to the current delivery data;
a fourth determination submodule configured to determine, by at least one processor, the closing time based on the first calculation factor and the first calculation means.
With reference to the second aspect, the first implementation manner of the second aspect, and/or the second implementation manner of the second aspect, in a third implementation manner of the second aspect, the update module includes:
a fifth determining submodule configured to determine, by at least one processor, a current delivery status of the target delivery task according to the current delivery data when the preset trigger event is a delivery status change event;
a sixth determining submodule configured to determine, by at least one processor, a second calculation manner in the preset configuration information in the current delivery state;
a seventh determining submodule configured to determine, by at least one processor, a second calculation factor in the second calculation manner according to the current delivery data;
an eighth determination submodule configured to determine, by at least one processor, the closing time based on the second calculation factor and the second calculation manner.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, and/or the third implementation manner of the second aspect, in a fourth implementation manner of the second aspect, the update module includes:
and the comparison submodule is configured to compare the current distribution data with matching conditions corresponding to the calculation branches in the preset configuration information through at least one processor, and determine the closing time according to the calculation modes corresponding to the calculation branches when the comparison is consistent.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, and/or the fourth implementation manner of the second aspect, in a fifth implementation manner of the second aspect, the comparing sub-module includes:
a ninth determining sub-module configured to determine, by at least one processor, a first calculation branch in the preset configuration information that matches a current delivery status or a current abnormal event in the current delivery data;
a tenth determination submodule configured to determine, by at least one processor, a second one of the first calculation branches that matches a capacity line in the current delivery data;
an eleventh determining sub-module configured to determine, by at least one processor, a third one of the second computing branches that matches weather data in the current delivery data;
a twelfth determining sub-module configured to determine, by at least one processor, a delivery time in the current delivery data that matches the configuration in the third computing branch;
a thirteenth determination submodule configured to determine, by at least one processor, the closing time based on the delivery time.
The functions can be realized by hardware, and the functions can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the above-described functions.
In one possible design, the task processing device includes a memory and a processor, the memory is used for storing one or more computer instructions for supporting the task processing device to execute the task processing method in the first aspect, and the processor is configured to execute the computer instructions stored in the memory. The task processing device may further comprise a communication interface for the task processing device to communicate with other devices or a communication network.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including a memory and a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method of the first aspect.
In a fourth aspect, the disclosed embodiments provide a computer-readable storage medium for storing computer instructions for a task processing apparatus, which includes computer instructions for performing any of the methods described above.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
the method includes the steps that for a delivery task, under the trigger of a preset trigger event, current delivery data of the delivery task are obtained through at least one processor, closing time of the delivery task is updated through the at least one processor according to preset configuration information and the current delivery data, and when the current time reaches the updated closing time, the delivery task is set to be in a closing state. Through the above mode disclosed by the disclosure, when the preset trigger event occurs, the closing time of the delivery task can be updated in time according to the current delivery condition, so that the updated closing time can be more reasonable, and the problems of low transport scheduling efficiency and the like caused by unreasonable closing time are avoided.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 illustrates a flow diagram of a task processing method according to an embodiment of the present disclosure;
FIG. 2 shows a flow chart of step S102 according to the embodiment shown in FIG. 1;
FIG. 3 shows a further flowchart of step S102 according to the embodiment shown in FIG. 1;
FIG. 4 illustrates a flow chart for determining a turn-off time portion via configuration information in accordance with an embodiment of the present disclosure;
fig. 5 is a block diagram showing a structure of a task processing device according to an embodiment of the present disclosure;
FIG. 6 illustrates a block diagram of the update module 502 according to the embodiment shown in FIG. 5;
FIG. 7 illustrates yet another block diagram of the update module 502 according to the embodiment shown in FIG. 5;
FIG. 8 is a block diagram illustrating a structure of a part for determining a turn-off time by configuration information according to an embodiment of the present disclosure;
fig. 9 is a schematic structural diagram of an electronic device suitable for implementing a task processing method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.
In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.
It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
In the related art, the order time is generated according to the generation time of the delivery tasks or the delivery time expected by the user plus a fixed time length, and all the delivery tasks are divided into an instant order of 'immediate delivery' and a predetermined order of 'scheduled delivery time' according to the delivery types. For the instant order, the order closing time is the sum of the generation time of the freight order and the fixed duration; for the reservation order, the order closing time is the user's desired delivery time plus a fixed duration. For example, setting the fixed duration to 3 hours, then one morning 11: 00 the order time for the delivery task created is 2 pm: 00, if at 2 pm: 00 without completing the fulfillment process, the delivery task will be closed and no further fulfillment will be possible. The order closing time in this example is not affected by other information.
The technical scheme adopts the fixed time length which is completely specified artificially and lacks credible basis. The fixed time makes it inapplicable to some instant delivery services, such as the order time of the ultra-long distance delivery order (more than 10KM) and the order time of the short distance delivery order are the same for two delivery tasks generated at the same time, which may make the ultra-long distance delivery order unable to continue to perform in the delivery due to the order.
Therefore, the embodiment of the present disclosure provides a method for processing a delivery task, in which when a preset trigger event occurs, a closing time of the delivery task is updated according to current delivery data of the delivery task and preset configuration information, so that the closing time of the delivery task is different according to the occurrence of different preset trigger events and different delivery data.
Fig. 1 illustrates a flowchart of a task processing method according to an embodiment of the present disclosure. As shown in fig. 1, the task processing method includes the following steps:
in step S101, in response to a preset trigger event, obtaining, by at least one processor, current delivery data of a target delivery task;
in step S102, updating, by at least one processor, a closing time of the target delivery task according to preset configuration information and the current delivery data; the preset configuration information is used for configuring a mode of determining the closing time according to the current distribution data;
in step S103, in response to the current time reaching the updated closing time of the target delivery task, the target delivery task is set to a closing state by at least one processor.
In this embodiment, the preset trigger event may be an update trigger event of the closing time of the target delivery task, and the preset trigger event may be preset, and when the trigger condition of the preset starting time is reached, the preset trigger time is generated by the at least one processor. The target delivery task may be any delivery task that has been generated. The delivery system closes the delivery task after a prescribed closing time is exceeded due to the delivery of the delivery task failing to complete for a long time from the creation, and refuses to continue to perform.
If the delivery system does not set the shutdown time, a delivery task will have some adverse effects if it is not shut down for a long time; for example, if the delivery resources do not deliver the delivery tasks assigned to the delivery resources for a long time, and the delivery system does not close the delivery tasks, the delivery tasks are delayed indefinitely and cannot be solved; for another example, after a delivery resource is delivered to a delivery task, the delivery resource is in a state of being delivered in the delivery system because the client forgets to perform the operation of delivering the delivery task, which affects various settlements related to the delivery task. Therefore, in order to avoid the problems mentioned above, the delivery system may allocate a reasonable closing time to the delivery task, and after the current time reaches the closing time, the at least one processor sets the status of the delivery task to the closing status, so that the delivery task does not affect the subsequent order taking capability of the corresponding delivery resource, and if the delivery task is closed due to the exception, the delivery task may enter the next stage, such as the exception handling stage.
There are many factors that affect the overall delivery process of the delivery task, which may include, but are not limited to, the delivery status of the delivery task, exceptional events, various delivery times, lines of transportation, weather data, and the like.
The delivery state is an abstract expression of the life cycle of the delivery task, and the delivery task can be divided into a plurality of delivery states corresponding to the stages of the delivery task in the delivery process, for example, taking the instant delivery task as an example, the delivery state can be divided into the following 6 states:
Figure BDA0002239592690000081
the line of transportation can be understood as a team where the distribution resources responsible for the distribution tasks are located, and the operation modes of different lines of transportation are different, for example, there are a team dedicated to distribution and a crowd-sourced resource for part-time distribution, and the distribution resources dedicated to distribution may have higher efficiency and faster distribution speed in the process of undertaking the distribution tasks, while the crowd-sourced resource may have relatively lower efficiency and slower distribution speed, so that the difference in the line of transportation also affects the reasonable closing time of the distribution tasks.
The various delivery times of the delivery tasks in the delivery process can be understood as the time points of the delivery tasks when entering the various delivery states, and the delivery times can be the initial calculation times of the closing times of the delivery tasks, and can include but are not limited to the creation times of the delivery tasks, the time allocated to the delivery resources, the payment time of users, the delivery time required by users, and the like;
the distribution process of the distribution tasks is also influenced by the weather condition, and the distribution speed, the distribution efficiency and the like are influenced in severe weather; weather data may include, but is not limited to, the severity of the weather during the distribution of the distribution mission, e.g., the weather may be classified into 5 categories, normal, mildly severe, extreme, and rarely severe, respectively.
The distribution process of the distribution tasks is also affected by some exceptional events. The exception event may assign various emergencies in the delivery process, such as the user failing to contact, the goods being damaged, the merchant being out of stock too late, etc. The occurrence of exceptional events often requires extended order-taking time for the delivery tasks, thereby allowing more time for the delivery resources to perform.
The foregoing is merely an illustration of various factors affecting the distribution process of the distribution tasks, but it is understood that the factors affecting the distribution process of the distribution tasks are not limited to the above, and may be determined according to practical situations, and are not limited herein.
The above factors affect the distribution process of the distribution tasks, and further may affect the reasonable closing time of the distribution tasks. Therefore, the triggering time causing the change of the closing time of the distribution tasks can be determined by analyzing the distribution process affecting the distribution tasks, and after the triggering events are preset, the technical scheme provided by the embodiment of the disclosure can be executed after the at least one processor generates the preset triggering events according to the triggering conditions, so that the closing time of the distribution tasks is updated by the at least one processor. For example, as can be seen from analysis of various factors influencing the delivery process of the delivery tasks by the at least one processor, reasonable closing times of the delivery tasks in different delivery states are different, and therefore, in some embodiments, the delivery state change event may be set as a preset trigger event; in addition, the reasonable closing time of the dispatching task under the abnormal event is different from that under the normal state, so in other embodiments, the abnormal event can also be set as a preset triggering event.
The preset trigger event is a preset event which can cause the closing time of the delivery tasks to change, and the current delivery data is a factor of how the closing time of the delivery tasks is influenced after the preset trigger event is generated. For example, when the delivery status of a delivery task changes, factors that affect the closing time of the delivery task differ based on the different delivery status entered. For example, based on the various factors that affect the delivery process of the delivery tasks listed above, the delivery status of the delivery tasks, the delivery time, the route, weather data, and/or abnormal events may affect the morning and evening of the closing time of the delivery tasks. Thus, the current delivery data is data in multiple dimensions, and may include, but is not limited to, the delivery status, the delivery time, the line of transportation, weather data, and/or abnormal events, etc. in which the delivery task is currently located.
The preset configuration information may be configured in advance, and includes, but is not limited to, a determination manner of determining a current closing time of the delivery task according to the current delivery data, and the preset configuration information may include a calculation manner of how to determine the closing time according to the current delivery data of the delivery task in what delivery state or in an abnormal event. For example, the preset configuration information may configure information that the target delivery task determines the closing time of the target delivery task according to a certain delivery time point of the target delivery task under the current delivery state or abnormal event, under the capacity line that bears the target delivery task, and under the current weather condition. The preset configuration information may be configured according to actual conditions, and is not limited herein.
According to the method and the device, for the delivery tasks, under the triggering of a preset triggering event, the current delivery data of the delivery tasks are obtained through at least one processor, the closing time of the delivery tasks is updated through the at least one processor according to preset configuration information and the current delivery data, and when the current time reaches the updated closing time, the delivery tasks are set to be in a closing state. Through the above mode disclosed by the disclosure, when the preset trigger event occurs, the closing time of the delivery task can be updated in time according to the current delivery condition, so that the updated closing time can be more reasonable, and the problems of low transport scheduling efficiency and the like caused by unreasonable closing time are avoided.
In an optional implementation manner of this embodiment, as shown in fig. 2, the step S102 of updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data further includes the following steps:
in step S201, when the preset trigger event is an abnormal event, determining, by at least one processor, a current abnormal event in the current delivery data;
in step S202, determining, by at least one processor, a first calculation manner in the preset configuration information under the current abnormal event;
in step S203, determining, by at least one processor, a first calculation factor in the first calculation manner according to the current distribution data;
in step S204, the closing time is determined by at least one processor according to the first calculation factor and the first calculation manner.
In this optional implementation manner, the preset configuration information may configure a calculation manner of the closing time of the target delivery task under different preset trigger events. When the preset trigger event is an abnormal event, the abnormal event currently occurring in the target delivery task can be determined according to the current delivery data through at least one processor, the first calculation mode under the current abnormal event is determined from the preset configuration information, and a first calculation factor used in the first calculation mode can be determined from the preset configuration information through at least one processor, and the first calculation factor is determined according to the current delivery data of the target delivery task.
For example, if the configuration in the preset configuration information is "when { a certain abnormal event }, if the line of motion of the delivery task is { a certain line of motion }, and the weather level is { a certain weather level }, the closing time of the delivery task is updated to { a time point in a certain delivery process } plus { a certain time period } ", it can be seen that the first calculation factor in the first calculation mode includes an abnormal event, a power line, a weather level, a time point in the delivery process, and a time period, and the first calculation mode is that in the case that the calculation condition matching the current abnormal event, the power line, and the weather level in the current delivery data of the target delivery task is satisfied, and calculating the closing time of the target distribution task according to the 'time point in the certain distribution process' in the current distribution data of the target distribution task and the fixed time period configured in the preset configuration information.
In an optional implementation manner of this embodiment, as shown in fig. 3, the step S102 of updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data further includes the following steps:
in step S301, when the preset trigger event is a delivery status change event, determining, by at least one processor, a current delivery status of the target delivery task according to the current delivery data;
in step S302, determining, by at least one processor, a second calculation manner in the preset configuration information in the current distribution state;
in step S303, determining, by at least one processor, a second calculation factor in the second calculation manner according to the current distribution data;
in step S304, the closing time is determined by at least one processor according to the second calculation factor and the second calculation manner.
In this optional implementation manner, the preset configuration information may configure a calculation manner of the closing time of the target delivery task under different preset trigger events. When the preset trigger event is a delivery state change event, the current delivery state of the target delivery task can be determined according to the current delivery data through at least one processor, the second calculation mode in the current delivery state is determined from the preset configuration information, a second calculation factor used in the second calculation mode can be determined from the preset configuration information through at least one processor, and the first calculation factor is determined according to the current delivery data of the target delivery task.
For example, if the preset configuration information is configured with "in the current { certain delivery status }, if the line of motion of the delivery task is { certain line of motion }, and the weather level is { a certain weather level }, the closing time of the delivery task is updated to { a time point in a certain delivery process } plus { a certain time period } ", it can be seen that the second calculation factor in the second calculation mode includes the current delivery status, the power line, the weather level, the time point in the delivery process, and the time period, and the second calculation mode is that in the case that the calculation condition that the current delivery status, the power line, and the weather level match in the current delivery data of the target delivery task is satisfied, and calculating the closing time of the target distribution task according to the 'time point in the certain distribution process' in the current distribution data of the target distribution task and the fixed time period configured in the preset configuration information.
In an optional implementation manner of this embodiment, in the step S102, that is, the step of updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data further includes the following steps:
and comparing the current distribution data with the matching conditions corresponding to the calculation branches in the preset configuration information through at least one processor, and determining the closing time according to the calculation modes corresponding to the calculation branches when the comparison is consistent.
In this optional implementation manner, matching conditions corresponding to different calculation branches may be configured in the preset configuration information, and different calculation manners under different matching conditions may be configured, where the matching conditions may include, but are not limited to, a distribution state, an abnormal event, a traffic line, a weather level, and the like; the manner of calculation may include, but is not limited to, the manner of how the closing time is determined according to the delivery time under the above matching condition.
In an optional implementation manner of this embodiment, as shown in fig. 4, the step of comparing, by at least one processor, the current delivery data with the matching condition corresponding to the calculation branch in the preset configuration information, and determining the closing time according to the calculation manner corresponding to the calculation branch when the comparison is consistent, further includes the following steps:
in step S401, determining, by at least one processor, a first calculation branch in the preset configuration information, where the first calculation branch matches a current distribution state or a current abnormal event in the current distribution data;
in step S402, determining, by at least one processor, a second calculation branch of the first calculation branches that matches a capacity line in the current delivery data;
in step S403, determining, by at least one processor, a third calculation branch of the second calculation branches that matches weather data in the current distribution data;
determining, by at least one processor, a delivery time in the current delivery data that matches the configuration in the third calculation branch in step S404;
in step S405, the closing time is determined by at least one processor from the delivery time.
In this optional implementation manner, a plurality of calculation branches may be configured in the preset configuration information, and different calculation branches correspond to different matching conditions. For example, the matching condition corresponding to the first calculation branch at the top layer is a distribution state or an abnormal event, the second calculation branch is located under the first calculation branch, the matching condition is a power line, the third calculation branch is located under the second calculation branch, the matching condition is weather data, and a calculation mode for calculating closing time according to distribution time and a time period is configured under the third calculation branch. When the closing time is determined, comparing the current distribution state or the abnormal event in the current distribution data (when the preset trigger event is a distribution state change event, comparing the current distribution state with the matching condition corresponding to the first calculation branch, when the preset trigger event is an abnormal event, comparing the current abnormal event with the matching condition corresponding to the first calculation branch through at least one processor) with the matching condition corresponding to the first calculation branch in the preset configuration information, further comparing the matching condition corresponding to the second calculation branch under the consistent first calculation branch with the power line in the current distribution data, then comparing the matching condition corresponding to the third calculation branch under the consistent second calculation branch with the weather data in the current distribution data, and finally determining the closing time by using the calculation mode configured under the third calculation branch, in this calculation method, the closing time is calculated by specifying which delivery time and time slot in the current delivery data are used.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.
Fig. 5 shows a block diagram of a task processing device according to an embodiment of the present disclosure, which may be implemented as part or all of an electronic device by software, hardware, or a combination of both. As shown in fig. 5, the task processing device includes:
a first response module 501, configured to, in response to a preset trigger event, acquire, by at least one processor, current delivery data of a target delivery task;
an updating module 502 configured to update, by at least one processor, a closing time of the target delivery task according to preset configuration information and the current delivery data; the preset configuration information is used for configuring a mode of determining the closing time according to the current distribution data;
a second response module 503 configured to set, by the at least one processor, the target delivery task in a closed state in response to the current time reaching the updated closing time of the target delivery task.
In this embodiment, the preset trigger event may be an update trigger event of the closing time of the target delivery task, and the preset trigger event may be preset, and when the trigger condition of the preset starting time is reached, the preset trigger time is generated by the at least one processor. The target delivery task may be any delivery task that has been generated. The delivery system closes the delivery task after a prescribed closing time is exceeded due to the delivery of the delivery task failing to complete for a long time from the creation, and refuses to continue to perform.
If the delivery system does not set the shutdown time, a delivery task will have some adverse effects if it is not shut down for a long time; for example, if the delivery resources do not deliver the delivery tasks assigned to the delivery resources for a long time, and the delivery system does not close the delivery tasks, the delivery tasks are delayed indefinitely and cannot be solved; for another example, after a delivery task is delivered by a delivery resource, the delivery task is forgotten to be executed by a client, so that the delivery resource is in a delivery state in a delivery system, and various settlements related to the delivery task are affected. Therefore, in order to avoid the problems mentioned above, the delivery system may allocate a reasonable closing time to the delivery task, and after the current time reaches the closing time, the at least one processor sets the status of the delivery task to the closing status, so that the delivery task does not affect the subsequent order taking capability of the corresponding delivery resource, and if the delivery task is closed due to the exception, the delivery task may enter the next stage, such as the exception handling stage.
There are many factors that affect the overall delivery process of the delivery task, which may include, but are not limited to, the delivery status of the delivery task, exceptional events, various delivery times, lines of transportation, weather data, and the like.
The delivery state is an abstract expression of the life cycle of the delivery task, and the delivery task can be divided into a plurality of delivery states corresponding to the stages of the delivery task in the delivery process, for example, taking the instant delivery task as an example, the delivery state can be divided into the following 6 states:
Figure BDA0002239592690000151
the line of transportation can be understood as a team where the distribution resources responsible for the distribution tasks are located, and the operation modes of different lines of transportation are different, for example, there are a team dedicated to distribution and a crowd-sourced resource for part-time distribution, and the distribution resources dedicated to distribution may have higher efficiency and faster distribution speed in the process of undertaking the distribution tasks, while the crowd-sourced resource may have relatively lower efficiency and slower distribution speed, so that the difference in the line of transportation also affects the reasonable closing time of the distribution tasks.
The various delivery times of the delivery tasks in the delivery process can be understood as the time points of the delivery tasks when entering the various delivery states, and the delivery times can be the initial calculation times of the closing times of the delivery tasks, and can include but are not limited to the creation times of the delivery tasks, the time allocated to the delivery resources, the payment time of users, the delivery time required by users, and the like;
the distribution process of the distribution tasks is also influenced by the weather condition, and the distribution speed, the distribution efficiency and the like are influenced in severe weather; weather data may include, but is not limited to, the severity of the weather during the distribution of the distribution mission, e.g., the weather may be classified into 5 categories, normal, mildly severe, extreme, and rarely severe, respectively.
The distribution process of the distribution tasks is also affected by some exceptional events. The exception event may assign various emergencies in the delivery process, such as the user failing to contact, the goods being damaged, the merchant being out of stock too late, etc. The occurrence of exceptional events often requires extended order-taking time for the delivery tasks, thereby allowing more time for the delivery resources to perform.
The foregoing is merely an illustration of various factors affecting the distribution process of the distribution tasks, but it is understood that the factors affecting the distribution process of the distribution tasks are not limited to the above, and may be determined according to practical situations, and are not limited herein.
The above factors affect the distribution process of the distribution tasks, and further may affect the reasonable closing time of the distribution tasks. Therefore, the triggering time causing the change of the closing time of the distribution tasks can be determined by analyzing the distribution process affecting the distribution tasks, and after the triggering events are preset, the technical scheme provided by the embodiment of the disclosure can be executed after the at least one processor generates the preset triggering events according to the triggering conditions, so that the closing time of the distribution tasks is updated by the at least one processor. For example, as can be seen from the analysis of the various factors influencing the delivery process of the delivery tasks by the at least one processor, the reasonable closing time of the delivery tasks in different delivery states is different, so in some embodiments, the delivery state change event may be set as a preset trigger event; in addition, the reasonable closing time of the dispatching task under the abnormal event is different from that under the normal state, so in other embodiments, the abnormal event can also be set as a preset triggering event.
The preset trigger event is a preset event which can cause the closing time of the delivery tasks to change, and the current delivery data is a factor of how the closing time of the delivery tasks is influenced after the preset trigger event is generated. For example, when the delivery status of a delivery task changes, factors that affect the closing time of the delivery task differ based on the different delivery status entered. For example, based on the various factors that affect the delivery process of the delivery tasks listed above, the delivery status of the delivery tasks, the delivery time, the line of force, weather data, and/or abnormal events may affect the morning and evening of the closing time of the delivery tasks. Thus, the current delivery data is data in multiple dimensions, and may include, but is not limited to, the delivery status, the delivery time, the line of transportation, weather data, and/or abnormal events, etc. in which the delivery task is currently located.
The preset configuration information may be configured in advance, and includes, but is not limited to, a determination manner of determining a current closing time of the delivery task according to the current delivery data, and the preset configuration information may include a calculation manner of how to determine the closing time according to the current delivery data of the delivery task in what delivery state or in an abnormal event. For example, the preset configuration information may configure information that the target delivery task determines the closing time of the target delivery task according to a certain delivery time point of the target delivery task under the current delivery state or abnormal event, under the capacity line that bears the target delivery task, and under the current weather condition. The preset configuration information may be configured according to actual conditions, and is not limited herein.
The method includes the steps that for a delivery task, under the trigger of a preset trigger event, current delivery data of the delivery task are obtained through at least one processor, closing time of the delivery task is updated through the at least one processor according to preset configuration information and the current delivery data, and when the current time reaches the updated closing time, the delivery task is set to be in a closing state. Through the above mode disclosed by the disclosure, when the preset trigger event occurs, the closing time of the delivery task can be updated in time according to the current delivery condition, so that the updated closing time can be more reasonable, and the problems of low transport scheduling efficiency and the like caused by unreasonable closing time are avoided.
In an optional implementation manner of this embodiment, as shown in fig. 6, the updating module 502 includes:
a first determining submodule 601, configured to determine, by at least one processor, a current abnormal event in the current delivery data when the preset trigger event is an abnormal event;
a second determining submodule 602, configured to determine, by at least one processor, a first calculation manner in the preset configuration information under the current abnormal event;
a third determining submodule 603 configured to determine, by at least one processor, a first calculation factor in the first calculation manner according to the current delivery data;
a fourth determining submodule 604 configured to determine, by the at least one processor, the closing time based on the first calculation factor and the first calculation mode.
In this optional implementation manner, the preset configuration information may configure a calculation manner of the closing time of the target delivery task under different preset trigger events. When the preset trigger event is an abnormal event, the abnormal event currently occurring in the target delivery task can be determined according to the current delivery data through at least one processor, the first calculation mode under the current abnormal event is determined from the preset configuration information, and a first calculation factor used in the first calculation mode can be determined from the preset configuration information through at least one processor, and the first calculation factor is determined according to the current delivery data of the target delivery task.
For example, if the configuration in the preset configuration information is "when { a certain abnormal event }, if the line of motion of the delivery task is { a certain line of motion }, and the weather level is { a certain weather level }, the closing time of the delivery task is updated to { a time point in a certain delivery process } plus { a certain time period } ", it can be seen that the first calculation factor in the first calculation mode includes an abnormal event, a power line, a weather level, a time point in the delivery process, and a time period, and the first calculation mode is that in the case that the calculation condition matching the current abnormal event, the power line, and the weather level in the current delivery data of the target delivery task is satisfied, and calculating the closing time of the target distribution task according to the 'time point in the certain distribution process' in the current distribution data of the target distribution task and the fixed time period configured in the preset configuration information.
In an optional implementation manner of this embodiment, as shown in fig. 7, the updating module 502 includes:
a fifth determining submodule 701, configured to determine, by at least one processor, a current delivery state of the target delivery task according to the current delivery data when the preset trigger event is a delivery state change event;
a sixth determining sub-module 702, configured to determine, by at least one processor, a second calculation manner in the preset configuration information in the current delivery state;
a seventh determining sub-module 703 configured to determine, by at least one processor, a second calculation factor in the second calculation manner according to the current distribution data;
an eighth determining submodule 704 configured to determine, by at least one processor, the closing time based on the second calculation factor and the second calculation manner.
In this optional implementation manner, the preset configuration information may configure a calculation manner of the closing time of the target delivery task under different preset trigger events. When the preset trigger event is a delivery state change event, the current delivery state of the target delivery task can be determined according to the current delivery data through at least one processor, the second calculation mode in the current delivery state is determined from the preset configuration information, a second calculation factor used in the second calculation mode can be determined from the preset configuration information through at least one processor, and the first calculation factor is determined according to the current delivery data of the target delivery task.
For example, if the preset configuration information is configured with "in the current { certain delivery status }, if the line of motion of the delivery task is { certain line of motion }, and the weather level is { a certain weather level }, the closing time of the delivery task is updated to { a time point in a certain delivery process } plus { a certain time period } ", it can be seen that the second calculation factor in the second calculation mode includes the current delivery status, the power line, the weather level, the time point in the delivery process, and the time period, and the second calculation mode is that in the case that the calculation condition that the current delivery status, the power line, and the weather level match in the current delivery data of the target delivery task is satisfied, and calculating the closing time of the target distribution task according to the 'time point in the certain distribution process' in the current distribution data of the target distribution task and the fixed time period configured in the preset configuration information.
In an optional implementation manner of this embodiment, the updating module 502 includes:
and the comparison submodule is configured to compare the current distribution data with matching conditions corresponding to the calculation branches in the preset configuration information through at least one processor, and determine the closing time according to the calculation modes corresponding to the calculation branches when the comparison is consistent.
In this optional implementation manner, matching conditions corresponding to different calculation branches may be configured in the preset configuration information, and different calculation manners under different matching conditions may be configured, where the matching conditions may include, but are not limited to, a distribution state, an abnormal event, a traffic line, a weather level, and the like; the manner of calculation may include, but is not limited to, the manner of how the closing time is determined according to the delivery time under the above matching condition.
In an optional implementation manner of this embodiment, as shown in fig. 8, the comparing sub-module includes:
a ninth determining sub-module 801 configured to determine, by at least one processor, a first calculation branch in the preset configuration information that matches a current delivery status or a current abnormal event in the current delivery data;
a tenth determination submodule 802 configured to determine, by the at least one processor, a second calculation branch of the first calculation branches that matches the capacity line in the current delivery data;
an eleventh determining sub-module 803 configured to determine, by the at least one processor, a third one of the second calculation branches that matches the weather data in the current delivery data;
a twelfth determining sub-module 804 configured to determine, by the at least one processor, a delivery time in the current delivery data that matches the configuration in the third computing branch;
a thirteenth determination submodule 805 configured to determine, by the at least one processor, the closing time based on the delivery time.
In this optional implementation manner, a plurality of calculation branches may be configured in the preset configuration information, and different calculation branches correspond to different matching conditions. For example, the matching condition corresponding to the first calculation branch at the top layer is a distribution state or an abnormal event, the second calculation branch is located under the first calculation branch, the matching condition is a power line, the third calculation branch is located under the second calculation branch, the matching condition is weather data, and a calculation mode for calculating closing time according to distribution time and a time period is configured under the third calculation branch. When the closing time is determined, comparing the current distribution state or the abnormal event in the current distribution data (when the preset trigger event is a distribution state change event, comparing the current distribution state with the matching condition corresponding to the first calculation branch, when the preset trigger event is an abnormal event, comparing the current abnormal event with the matching condition corresponding to the first calculation branch through at least one processor) with the matching condition corresponding to the first calculation branch in the preset configuration information, further comparing the matching condition corresponding to the second calculation branch under the consistent first calculation branch with the power line in the current distribution data, then comparing the matching condition corresponding to the third calculation branch under the consistent second calculation branch with the weather data in the current distribution data, and finally determining the closing time by using the calculation mode configured under the third calculation branch, in this calculation method, the closing time is calculated by specifying which delivery time and time slot in the current delivery data are used.
The disclosed embodiment also provides an electronic device, as shown in fig. 9, including at least one processor 901; and memory 902 communicatively connected to the at least one processor 901; wherein the memory 902 stores instructions executable by the at least one processor 901, the instructions being executable by the at least one processor 901 to implement:
in response to a preset trigger event, acquiring current distribution data of a target distribution task through at least one processor;
updating the closing time of the target distribution task through at least one processor according to preset configuration information and the current distribution data; the preset configuration information is used for configuring a mode of determining the closing time according to the current distribution data;
and setting the target delivery task to be in a closed state through at least one processor in response to the current time reaching the updated closing time of the target delivery task.
The preset trigger event comprises a delivery state change event and/or an abnormal event of the target delivery task; and/or the presence of a gas in the gas,
the current delivery data includes delivery status, delivery time, line of fortune, weather data, and/or abnormal events of the target delivery task.
Wherein, updating the closing time of the target distribution task according to preset configuration information and the current distribution data through at least one processor comprises:
when the preset trigger event is an abnormal event, determining the current abnormal event in the current distribution data through at least one processor;
determining a first calculation mode under the current abnormal event in the preset configuration information through at least one processor;
determining, by at least one processor, a first calculation factor in the first calculation mode based on the current delivery data;
determining, by at least one processor, the turn-off time based on the first calculation factor and the first calculation.
Wherein updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data includes:
when the preset trigger event is a distribution state change event, determining the current distribution state of the target distribution task through at least one processor according to the current distribution data;
determining a second calculation mode in the preset configuration information under the current distribution state through at least one processor;
determining, by at least one processor, a second calculation factor in the second calculation mode based on the current delivery data;
determining, by at least one processor, the turn-off time based on the second calculation factor and the second calculation.
Wherein updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data includes:
and comparing the current distribution data with the matching conditions corresponding to the calculation branches in the preset configuration information through at least one processor, and determining the closing time according to the calculation modes corresponding to the calculation branches when the comparison is consistent.
Comparing the current distribution data with matching conditions corresponding to the calculation branches in the preset configuration information through at least one processor, and determining the closing time according to the calculation modes corresponding to the calculation branches when the comparison is consistent, wherein the method comprises the following steps:
determining, by at least one processor, a first computation branch in the preset configuration information that matches a current delivery status or a current abnormal event in the current delivery data;
determining, by at least one processor, a second of the first computational branches that matches a capacity line in the current delivery data;
determining, by at least one processor, a third one of the second calculation branches that matches weather data in the current delivery data;
determining, by at least one processor, a delivery time in the current delivery data that matches the configuration in the third computing branch;
determining, by at least one processor, the closing time based on the delivery time.
Specifically, the processor 901 and the memory 902 may be connected by a bus or by other means, and fig. 9 illustrates the connection by the bus as an example. Memory 902, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The processor 901 executes various functional applications of the device and data processing by executing nonvolatile software programs, instructions, and modules stored in the memory 902, that is, implements the above-described method in the embodiments of the present disclosure.
The memory 902 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store historical data of shipping network traffic, and the like. Further, the memory 902 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the electronic device optionally includes a communications component 903, and the memory 902 optionally includes memory remotely located from the processor 901, which may be connected to an external device through the communications component 903. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more modules are stored in the memory 902, and when executed by the one or more processors 901 perform the methods described above in the embodiments of the present disclosure.
The product can execute the method provided by the embodiment of the disclosure, has corresponding functional modules and beneficial effects of the execution method, and reference can be made to the method provided by the embodiment of the disclosure for technical details which are not described in detail in the embodiment.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.
As another aspect, the present disclosure also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the above embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.

Claims (14)

1. A method for processing a task, comprising:
in response to a preset trigger event, acquiring current distribution data of a target distribution task through at least one processor;
updating the closing time of the target distribution task through at least one processor according to preset configuration information and the current distribution data; the preset configuration information is used for configuring a mode of determining the closing time according to the current distribution data;
and in response to the current time reaching the updated closing time of the target delivery task, setting the target delivery task to be in a closing state through at least one processor, so that the delivery task does not influence the subsequent order taking capability of the corresponding delivery resource any more.
2. The method according to claim 1, wherein the preset trigger event comprises a delivery status change event and/or an abnormal event of the target delivery task; and/or the presence of a gas in the gas,
the current delivery data includes delivery status, delivery time, line of fortune, weather data, and/or abnormal events of the target delivery task.
3. The method of claim 1 or 2, wherein updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data comprises:
when the preset trigger event is an abnormal event, determining the current abnormal event in the current distribution data through at least one processor;
determining a first calculation mode under the current abnormal event in the preset configuration information through at least one processor;
determining, by at least one processor, a first calculation factor in the first calculation mode based on the current delivery data;
determining, by at least one processor, the turn-off time based on the first calculation factor and the first calculation.
4. The method of claim 1 or 2, wherein updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data comprises:
when the preset trigger event is a distribution state change event, determining the current distribution state of the target distribution task through at least one processor according to the current distribution data;
determining a second calculation mode in the preset configuration information under the current distribution state through at least one processor;
determining, by at least one processor, a second calculation factor in the second calculation mode based on the current delivery data;
determining, by at least one processor, the turn-off time based on the second calculation factor and the second calculation.
5. The method of claim 1 or 2, wherein updating, by at least one processor, the closing time of the target delivery task according to preset configuration information and the current delivery data comprises:
and comparing the current distribution data with the matching conditions corresponding to the calculation branches in the preset configuration information through at least one processor, and determining the closing time according to the calculation modes corresponding to the calculation branches when the comparison is consistent.
6. The method of claim 5, wherein comparing, by at least one processor, the current delivery data with matching conditions corresponding to calculation branches in the preset configuration information, and determining the closing time according to a calculation manner corresponding to the calculation branches when the comparison is consistent comprises:
determining, by at least one processor, a first computation branch in the preset configuration information that matches a current delivery status or a current abnormal event in the current delivery data;
determining, by at least one processor, a second calculation branch of the first calculation branches that matches a capacity line in the current delivery data;
determining, by at least one processor, a third one of the second calculation branches that matches weather data in the current delivery data;
determining, by at least one processor, a delivery time in the current delivery data that matches the configuration in the third computing branch;
determining, by at least one processor, the closing time based on the delivery time.
7. A task processing apparatus, comprising:
the system comprises a first response module, a first display module and a second display module, wherein the first response module is configured to respond to a preset trigger event and acquire current distribution data of a target distribution task through at least one processor;
the updating module is configured to update the closing time of the target delivery task according to preset configuration information and the current delivery data through at least one processor; the preset configuration information is used for configuring a mode of determining the closing time according to the current distribution data;
and the second response module is configured to set the target delivery task to a closed state through at least one processor in response to that the current time reaches the updated closing time of the target delivery task, so that the delivery task no longer affects subsequent order taking capability of the corresponding delivery resource.
8. The apparatus according to claim 7, wherein the preset trigger event comprises a delivery status change event and/or an abnormal event of the target delivery task; and/or the presence of a gas in the gas,
the current delivery data includes delivery status, delivery time, line of fortune, weather data and/or abnormal events of the target delivery task.
9. The apparatus of claim 7 or 8, wherein the update module comprises:
a first determining submodule configured to determine, by at least one processor, a current abnormal event in the current delivery data when the preset trigger event is an abnormal event;
the second determining submodule is configured to determine, through at least one processor, a first calculation mode under the current abnormal event in the preset configuration information;
a third determining submodule configured to determine, by at least one processor, a first calculation factor in the first calculation manner according to the current delivery data;
a fourth determination submodule configured to determine, by at least one processor, the closing time based on the first calculation factor and the first calculation means.
10. The apparatus of claim 7 or 8, wherein the update module comprises:
a fifth determining submodule configured to determine, by at least one processor, a current delivery status of the target delivery task according to the current delivery data when the preset trigger event is a delivery status change event;
a sixth determining submodule configured to determine, by at least one processor, a second calculation manner in the preset configuration information in the current delivery state;
a seventh determining submodule configured to determine, by at least one processor, a second calculation factor in the second calculation manner according to the current delivery data;
an eighth determination submodule configured to determine, by at least one processor, the closing time based on the second calculation factor and the second calculation manner.
11. The apparatus of claim 7 or 8, wherein the update module comprises:
and the comparison submodule is configured to compare the current distribution data with matching conditions corresponding to the calculation branches in the preset configuration information through at least one processor, and determine the closing time according to the calculation modes corresponding to the calculation branches when the comparison is consistent.
12. The apparatus of claim 11, wherein the comparison submodule comprises:
a ninth determining sub-module configured to determine, by at least one processor, a first calculation branch in the preset configuration information that matches a current delivery status or a current abnormal event in the current delivery data;
a tenth determination submodule configured to determine, by at least one processor, a second one of the first calculation branches that matches a capacity line in the current delivery data;
an eleventh determining sub-module configured to determine, by at least one processor, a third one of the second computing branches that matches weather data in the current delivery data;
a twelfth determining sub-module configured to determine, by at least one processor, a delivery time in the current delivery data that matches the configuration in the third computing branch;
a thirteenth determination submodule configured to determine, by at least one processor, the closing time based on the delivery time.
13. An electronic device comprising a memory and at least one processor; wherein the content of the first and second substances,
the memory is to store one or more computer instructions, wherein the one or more computer instructions are to be executed by the at least one processor to implement the method of any one of claims 1-6.
14. A computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, implement the method of any of claims 1-6.
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