CN110737525A - Task processing method and device, electronic equipment and storage medium - Google Patents
Task processing method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The method comprises the steps of responding to a preset trigger event, obtaining current distribution data of a target distribution task through at least processors, updating closing time of the target distribution task through at least processors according to preset configuration information and the current distribution data, wherein the preset configuration information is used for configuring a mode of determining the closing time according to the current distribution data, and responding to the fact that the current time reaches the updated closing time of the target distribution task, and setting the target distribution task to be in a closing state through at least processors.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to task processing methods and apparatuses, 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 task processing methods and devices, electronic equipment and storage media.
, task processing methods are provided in the disclosed embodiments.
Specifically, the task processing method includes:
in response to a preset trigger event, acquiring current distribution data of the target distribution task through at least processors;
updating the closing time of the target distribution task through at least processors according to preset configuration information and the current distribution data, wherein 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 processors in response to the current time reaching the updated closing time of the target delivery task.
With reference to , in an implementation manner of the present disclosure of , the preset trigger event includes a delivery status change event and/or an abnormal event of the target delivery task, and/or,
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 th aspect and/or th implementation manner of the th aspect, in a second implementation manner of the of the present disclosure, the updating, by at least processors, the closing time of the target distribution task according to preset configuration information and the current distribution data includes:
when the preset trigger event is an abnormal event, determining the current abnormal event in the current distribution data through at least processors;
determining, by at least processors, a th calculation mode under the current abnormal event in the preset configuration information;
determining, by at least processors, a th calculation factor in the th calculation mode based on the current distribution data;
determining, by at least processors, the closing time based on the th calculation factor and the th calculation.
With reference to the aspect, the implementation manner of the aspect, and/or the second implementation manner of the aspect, in a third implementation manner of the aspect, the updating, by at least processors, 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 according to the current distribution data through at least processors;
determining a second calculation mode in the current distribution state in the preset configuration information through at least processors;
determining, by at least processors, a second calculation factor in the second calculation from the current delivery data;
determining, by at least processors, the closing time based on the second calculation factor and the second calculation.
With reference to the aspect, the implementation manner of the aspect, the second implementation manner of the aspect, and/or the third implementation manner of the aspect, in a fourth implementation manner of the aspect, the updating, by at least processors, a closing time of the target delivery task according to preset configuration information and the current delivery data includes:
comparing the current distribution data with matching conditions corresponding to the calculation branches in the preset configuration information through at least processors, and determining the closing time according to the calculation mode corresponding to the calculation branches when comparison results.
With reference to , the implementation manner of the aspect, the second implementation manner of the aspect, the third implementation manner of the aspect, and/or the fourth implementation manner of the aspect, in a fifth implementation manner of the aspect of the present disclosure, comparing, by at least processors, the current delivery data with a matching condition corresponding to a calculation branch in the preset configuration information, and when the comparison is , determining the closing time according to a calculation manner corresponding to the calculation branch, includes:
determining, by at least processors, a th calculation 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 processors, a second of the computational branches that matches a line of capacity in the current distribution data;
determining, by at least processors, a third calculation branch of the second calculation branches that matches weather data in the current distribution data;
determining, by at least processors, a delivery time in the current delivery data that matches the configuration in the third calculation branch;
determining, by at least processors, the closing time based on the delivery time.
In a second aspect, task processing devices are provided in embodiments of the present disclosure.
Specifically, the task processing device includes:
an response module configured to obtain current distribution data of the target distribution task through at least processors in response to a preset trigger event;
the updating module is configured to update the closing time of the target distribution task according to preset configuration information and the current distribution data through at least processors, wherein 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 at least processors, the target delivery task to an off state in response to the current time reaching the updated off time of the target delivery task.
With reference to the second aspect, in 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 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 th implementation manner of the second aspect, in a second implementation manner of the second aspect, the update module includes:
an determining submodule configured to determine, by at least processors, a current exceptional event in the current delivery data when the preset triggering event is an exceptional event;
the second determining submodule is configured to determine, through at least processors, the th calculation mode under the current abnormal event in the preset configuration information;
a third determining submodule configured to determine, by at least processors, a th calculation factor in the th calculation mode according to the current distribution data;
a fourth determination submodule configured to determine, by at least processors, the closing time based on the th calculation factor and the th calculation mode.
With reference to the second aspect, the th 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 processors, 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 processors, a second calculation manner in the preset configuration information in the current distribution state;
a seventh determining submodule configured to determine, by at least processors, a second calculation factor in the second calculation manner from the current distribution data;
an eighth determination submodule configured to determine, by at least processors, the closing time based on the second calculation factor and the second calculation mode.
With reference to the second aspect, the th 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 processors, and when the comparison is met, determine the closing time according to the calculation modes corresponding to the calculation branches.
With reference to the second aspect, the th 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, through at least processors, a th 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 processors, a second calculation branch of the calculation branches that matches a capacity line in the current distribution data;
a tenth determination submodule configured to determine, by at least processors, a third one of the second calculation branches that matches weather data in the current distribution data;
a twelfth determination submodule configured to determine, by at least processors, delivery times in the current delivery data that match the configuration in the third calculation branch;
a thirteenth determination submodule configured to determine, by at least processors, the closing time based on the delivery time.
The functions may be implemented by hardware, or by hardware executing corresponding software, which includes or more modules corresponding to the above functions.
In possible designs, the task processing device has a structure including a memory for storing pieces of computer instructions supporting the task processing device to perform the method of processing the task in above and a processor configured to execute the computer instructions stored in the memory.
In a third aspect, the disclosed embodiments provide electronic devices comprising a memory and a processor, wherein the memory is configured to store or more computer instructions, wherein the or more computer instructions are executed by the processor to implement the method of aspect .
In a fourth aspect, the disclosed embodiments provide computer-readable storage media for storing computer instructions for a task processing device, including computer instructions for performing the method of any of described above.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
according to the method, 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 efficiency of capacity scheduling and the like caused by unreasonable closing time are solved.
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 flow diagram according to step S102 of the embodiment shown in FIG. 1;
FIG. 4 illustrates a flow chart for determining the off-time portion via configuration information in an embodiment of the present disclosure ;
FIG. 5 illustrates a block diagram 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 a block diagram of yet another configuration of the update module 502 according to the embodiment shown in FIG. 5;
FIG. 8 illustrates a block diagram of a portion of the determination of the 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 in the specification, and are not intended to exclude the possibility that 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 user desired arrival time plus a fixed time length, and all the delivery tasks are divided into an instant order of "immediate arrival" and a predetermined order of "scheduled arrival time" according to the delivery types, the order time is the generation time of the waybill plus the fixed time length for the instant order, and the order time is the user desired arrival time plus the fixed time length for the predetermined order, for example, the fixed time length is set to be 3 hours, then the order time of delivery tasks created 11:00 am is 2:00 pm, and if the fulfillment process is not completed 2:00 pm, the delivery tasks are closed and cannot be continued.
The fixed time cannot be applied to some instant delivery services, for example, for two delivery tasks generated at the same time of , the order time of an ultra-long distance delivery order (more than 10KM) and the order time of a short distance delivery order are , which may cause that the ultra-long distance delivery order cannot continue to perform in the delivery process due to the order.
Therefore, the present disclosure provides methods for processing delivery tasks, in which when a preset trigger event occurs, the closing time of the delivery tasks is updated according to the current delivery data of the delivery tasks and preset configuration information, so that the closing time of the delivery tasks is different according to the occurrence of different preset trigger events and different delivery data.
Fig. 1 illustrates a flow diagram of a task processing method according to an embodiment of the present disclosure , as illustrated in fig. 1, the task processing method includes the steps of:
in step S101, in response to a preset trigger event, current distribution data of the target distribution tasks are obtained through at least processors;
in step S102, updating, by at least processors, the closing time of the target distribution task according to preset configuration information and the current distribution data, wherein the preset configuration information is used for configuring a manner 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 closed state by at least processors.
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 generated by at least processors when the trigger condition of the preset starting time is reached.
If the distribution system does not set the closing time, distribution tasks are not closed after a long time, some adverse effects may be generated , for example, a distribution resource does not distribute the distribution tasks allocated to the distribution resource for a long time, and the distribution system does not close the distribution tasks, which may result in the distribution tasks being delayed indefinitely and not being solved, and for example, after a distribution resource reaches a distribution task, the distribution resource is in a state of being distributed in the distribution system due to forgetting to perform the operation that the distribution task has reached at the client, which may affect various settlements related to the distribution task, and therefore, in order to avoid various problems as mentioned above, the distribution system may allocate a reasonable closing time to the distribution task, and after the current time reaches the closing time, set the state of the distribution task in a closing state through at least processors, so that the distribution task no longer affects the subsequent order taking capability of the corresponding distribution resource, and if the distribution task is closed due to an abnormality, may enter a next stage , such as an abnormality processing stage 82.
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:
the line of transportation can be understood as a team where the distribution resources for the distribution tasks are located, and the operation modes of different lines of transportation are different, for example, a team where special is dedicated for distribution and crowd-sourced resources for part-time distribution, the distribution resources dedicated for distribution may have higher efficiency and faster distribution speed in the process of being dedicated for distribution tasks, and the crowd-sourced resources may have relatively lower efficiency and slower distribution speed, so that the difference of the lines 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 delivery process of the delivery task is also affected by exceptions, which may be associated with various emergencies in the delivery process, such as user unavailability, damage to goods, too late merchant delivery time, etc. the occurrence of exceptions often requires an extended schedule time for the delivery task, thereby allowing more time for 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 method includes the steps of analyzing distribution processes of distribution tasks to determine trigger time causing change of the closing time of the distribution tasks, presetting the trigger events, executing the technical scheme provided by the embodiment of the disclosure after at least processors generate preset trigger events according to trigger conditions, and updating the closing time of the distribution tasks through at least processors, wherein the reasonable closing time of the distribution tasks in different distribution states is different through analysis of various factors in the distribution processes of the distribution tasks through at least processors, so that the distribution state change events can be set as the preset trigger events in embodiments, and the reasonable closing time of the distribution tasks in abnormal events is different from that in normal states, so the abnormal events can be set as the preset trigger events in other embodiments.
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, 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 efficiency of capacity scheduling and the like caused by unreasonable closing time are solved.
In optional implementation manners of the embodiment, as shown in fig. 2, the step S102, that is, the step of updating the closing time of the target distribution task by at least processors according to preset configuration information and the current distribution data, further includes the following steps:
in step S201, when the preset trigger event is an abnormal event, determining, by at least processors, a current abnormal event in the current distribution data;
in step S202, determining, by at least processors, a th calculation manner of the preset configuration information at the current abnormal event;
in step S203, determining a calculation factor in the calculation mode according to the current distribution data through at least processors;
in step S204, the closing time is determined by at least processors based on the th calculation factor and the th calculation.
When the preset trigger event is an abnormal event, determining an abnormal event currently occurring to the target delivery task according to the current delivery data through at least processors, determining a th calculation mode under the current abnormal event from the preset configuration information, determining a th calculation factor used in the th calculation mode from the preset configuration information through at least processors, and determining the th calculation factor according to the current delivery data of the target delivery task.
For example, in the preset configuration information, "if the line of power of the delivery task is { certain line of power } and the weather level is { certain weather level }, the closing time of the delivery task is updated to { a point of time in a delivery process } plus { certain time period }" in the current { certain abnormal event } configuration information, it is seen that the -th calculation factor in the -th calculation method includes the abnormal event, the line of power, the weather level, the point of time in the delivery process, and the time period, and the -th calculation method is to calculate the closing time of the target delivery task according to "the point of time in the delivery process" in the current delivery data of the target delivery task and the fixed time period configured in the preset configuration information, when the calculation condition that the current abnormal event, the line of power, the weather level in the current delivery data of the target delivery task matches is satisfied.
In optional implementation manners of the embodiment, as shown in fig. 3, the step S102, that is, the step of updating the closing time of the target distribution task by at least processors according to preset configuration information and the current distribution data, further includes the following steps:
in step S301, when the preset trigger event is a distribution status change event, determining, by at least processors, a current distribution status of the target distribution task according to the current distribution data;
in step S302, determining, by at least processors, a second calculation manner in the preset configuration information under the current distribution state;
in step S303, determining, by at least processors, 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 processors according to the second calculation factor and the second calculation manner.
When the preset trigger event is a distribution state change event, the current distribution state of the target distribution task can be determined according to the current distribution data through at least processors, a second calculation mode in the current distribution state can be 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 processors, and the th calculation factor is determined according to the current distribution data of the target distribution 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 optional implementation manners of the embodiment, the step S102, namely the step of updating the closing time of the target distribution task according to preset configuration information and the current distribution data through at least processors, further includes the following steps:
comparing the current distribution data with matching conditions corresponding to the calculation branches in the preset configuration information through at least processors, and determining the closing time according to the calculation mode corresponding to the calculation branches when comparison results.
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 optional implementation manners of the embodiment, as shown in fig. 4, the step of comparing, by at least processors, the current distribution data with the matching conditions corresponding to the calculation branches in the preset configuration information, and when the comparison result is , determining the closing time according to the calculation manner corresponding to the calculation branches, further includes the steps of:
in step S401, determining, by at least processors, a th calculation branch in the preset configuration information that matches a current distribution status or a current abnormal event in the current distribution data;
in step S402, determining, by at least processors, a second calculation branch of the th calculation branches that matches a capacity line in the current distribution data;
in step S403, determining, by at least processors, a third calculation branch of the second calculation branches that matches the weather data in the current distribution data;
in step S404, determining, by at least processors, delivery times in the current delivery data that match the configuration in the third calculation branch;
in step S405, the closing time is determined by at least processors based on the delivery time.
For example, the matching condition corresponding to the -th calculation branch at the topmost level is delivery status or abnormal event, the second calculation branch is located under the -th calculation branch, the matching condition is capacity line, the third calculation branch is located under the second calculation branch, the matching condition is weather data, and the third calculation branch is configured with a calculation method for calculating closing time according to delivery time and time period.
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:
an response module 501, configured to respond to a preset trigger event, obtain current delivery data of a target delivery task through at least processors;
an updating module 502 configured to update, by at least processors, the closing time of the target delivery task according to preset configuration information and the current delivery data, wherein the preset configuration information is used for configuring a manner of determining the closing time according to the current delivery data;
a second response module 503 configured to set, by at least processors, the target delivery task to an off state in response to the current time reaching the updated off 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 generated by at least processors when the trigger condition of the preset starting time is reached.
If the distribution system does not set the closing time, distribution tasks are not closed after a long time, some adverse effects may be generated , for example, a distribution resource does not distribute the distribution tasks allocated to the distribution resource for a long time, and the distribution system does not close the distribution tasks, which may result in the distribution tasks being delayed indefinitely and not being solved, and for example, after a distribution resource reaches a distribution task, the distribution resource is in a state of being distributed in the distribution system due to forgetting to perform the operation that the distribution task has reached at the client, which may affect various settlements related to the distribution task, and therefore, in order to avoid various problems as mentioned above, the distribution system may allocate a reasonable closing time to the distribution task, and after the current time reaches the closing time, set the state of the distribution task in a closing state through at least processors, so that the distribution task no longer affects the subsequent order taking capability of the corresponding distribution resource, and if the distribution task is closed due to an abnormality, may enter a next stage , such as an abnormality processing stage 82.
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:
the line of transportation can be understood as a team where the distribution resources for the distribution tasks are located, and the operation modes of different lines of transportation are different, for example, a team where special is dedicated for distribution and crowd-sourced resources for part-time distribution, the distribution resources dedicated for distribution may have higher efficiency and faster distribution speed in the process of being dedicated for distribution tasks, and the crowd-sourced resources may have relatively lower efficiency and slower distribution speed, so that the difference of the lines 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 delivery process of the delivery task is also affected by exceptions, which may be associated with various emergencies in the delivery process, such as user unavailability, damage to goods, too late merchant delivery time, etc. the occurrence of exceptions often requires an extended schedule time for the delivery task, thereby allowing more time for 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 method includes the steps of analyzing distribution processes of distribution tasks to determine trigger time causing change of the closing time of the distribution tasks, presetting the trigger events, executing the technical scheme provided by the embodiment of the disclosure after at least processors generate preset trigger events according to trigger conditions, and updating the closing time of the distribution tasks through at least processors, wherein the reasonable closing time of the distribution tasks in different distribution states is different through analysis of various factors in the distribution processes of the distribution tasks through at least processors, so that the distribution state change events can be set as the preset trigger events in embodiments, and the reasonable closing time of the distribution tasks in abnormal events is different from that in normal states, so the abnormal events can be set as the preset trigger events in other embodiments.
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, 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 efficiency of capacity scheduling and the like caused by unreasonable closing time are solved.
In optional implementations of the present embodiment, as shown in fig. 6, the update module 502 includes:
an determining sub-module 601 configured to determine, by at least processors, a current abnormal event in the current distribution data when the preset triggering event is an abnormal event;
a second determining submodule 602 configured to determine, by at least processors, a th calculation manner in the preset configuration information at the current abnormal event;
a third determining submodule 603 configured to determine, by at least processors, a th calculation factor in the th calculation mode according to the current distribution data;
a fourth determination submodule 604 configured to determine the closing time by at least processors based on the th calculation factor and the th calculation mode.
When the preset trigger event is an abnormal event, determining an abnormal event currently occurring to the target delivery task according to the current delivery data through at least processors, determining a th calculation mode under the current abnormal event from the preset configuration information, determining a th calculation factor used in the th calculation mode from the preset configuration information through at least processors, and determining the th calculation factor according to the current delivery data of the target delivery task.
For example, in the preset configuration information, "if the line of power of the delivery task is { certain line of power } and the weather level is { certain weather level }, the closing time of the delivery task is updated to { a point of time in a delivery process } plus { certain time period }" in the current { certain abnormal event } configuration information, it is seen that the -th calculation factor in the -th calculation method includes the abnormal event, the line of power, the weather level, the point of time in the delivery process, and the time period, and the -th calculation method is to calculate the closing time of the target delivery task according to "the point of time in the delivery process" in the current delivery data of the target delivery task and the fixed time period configured in the preset configuration information, when the calculation condition that the current abnormal event, the line of power, the weather level in the current delivery data of the target delivery task matches is satisfied.
In optional implementations of the present embodiment, as shown in fig. 7, the update module 502 includes:
a fifth determining submodule 701, configured to determine, by at least processors, 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 702 configured to determine, by at least processors, a second calculation manner in the preset configuration information in the current distribution state;
a seventh determining submodule 703 configured to determine, by at least processors, a second calculation factor in the second calculation manner from the current distribution data;
an eighth determining submodule 704 configured to determine, by at least processors, the closing time based on the second calculation factor and the second calculation mode.
When the preset trigger event is a distribution state change event, the current distribution state of the target distribution task can be determined according to the current distribution data through at least processors, a second calculation mode in the current distribution state can be 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 processors, and the th calculation factor is determined according to the current distribution data of the target distribution 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 optional implementation manners of the present embodiment, the update 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 processors, and when the comparison is met, determine the closing time according to the calculation modes corresponding to the calculation branches.
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 optional implementations of the present embodiment, as shown in fig. 8, the comparing sub-module includes:
a ninth determining sub-module 801 configured to determine, through at least processors, a th calculation branch in the preset configuration information that matches the current delivery status or the current abnormal event in the current delivery data;
a tenth determination submodule 802 configured to determine, by at least processors, a second calculation branch of the calculation branches that matches a capacity line in the current distribution data;
a tenth determining sub-module 803 configured to determine, by at least processors, a third calculation branch of the second calculation branches that matches weather data in the current distribution data;
a twelfth determining sub-module 804 configured to determine, by at least processors, a delivery time in the current delivery data that matches the configuration in the third calculation branch;
a thirteenth determination submodule 805 configured to determine the closing time from the delivery time by at least processors.
For example, the matching condition corresponding to the -th calculation branch at the topmost level is delivery status or abnormal event, the second calculation branch is located under the -th calculation branch, the matching condition is capacity line, the third calculation branch is located under the second calculation branch, the matching condition is weather data, and the third calculation branch is configured with a calculation method for calculating closing time according to delivery time and time period.
The disclosed embodiment also provides electronic devices, as shown in fig. 9, comprising at least processors 901, and a memory 902 communicatively connected to at least processors 901, wherein the memory 902 stores instructions executable by at least processors 901, the instructions being executed by at least processors 901 to implement:
in response to a preset trigger event, acquiring current distribution data of the target distribution task through at least processors;
updating the closing time of the target distribution task through at least processors according to preset configuration information and the current distribution data, wherein 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 processors 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 processors comprises:
when the preset trigger event is an abnormal event, determining the current abnormal event in the current distribution data through at least processors;
determining, by at least processors, a th calculation mode under the current abnormal event in the preset configuration information;
determining, by at least processors, a th calculation factor in the th calculation mode based on the current distribution data;
determining, by at least processors, the closing time based on the th calculation factor and the th calculation.
Wherein, updating the closing time of the target distribution task according to preset configuration information and the current distribution data through at least processors comprises:
when the preset trigger event is a distribution state change event, determining the current distribution state of the target distribution task according to the current distribution data through at least processors;
determining a second calculation mode in the current distribution state in the preset configuration information through at least processors;
determining, by at least processors, a second calculation factor in the second calculation from the current delivery data;
determining, by at least processors, the closing time based on the second calculation factor and the second calculation.
Wherein, updating the closing time of the target distribution task according to preset configuration information and the current distribution data through at least processors comprises:
comparing the current distribution data with matching conditions corresponding to the calculation branches in the preset configuration information through at least processors, and determining the closing time according to the calculation mode corresponding to the calculation branches when comparison results.
Comparing the current distribution data with matching conditions corresponding to the calculation branches in the preset configuration information through at least processors, and determining the closing time according to the calculation mode corresponding to the calculation branches when comparison results, wherein the method comprises the following steps:
determining, by at least processors, a th calculation 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 processors, a second of the computational branches that matches a line of capacity in the current distribution data;
determining, by at least processors, a third calculation branch of the second calculation branches that matches weather data in the current distribution data;
determining, by at least processors, a delivery time in the current delivery data that matches the configuration in the third calculation branch;
determining, by at least processors, the closing time based on the delivery time.
Specifically, the processor 901 and the memory 902 may be connected by a bus or other means, and fig. 9 illustrates the connection by the bus, the memory 902 is nonvolatile computer readable storage media which can be used for storing nonvolatile software programs, nonvolatile computer executable programs and modules, the processor 901 executes various functional applications and data processing of the device by running the nonvolatile software programs, instructions and modules stored in the memory 902, so as to implement the above method in the embodiment of the present disclosure.
The memory 902 may include a program storage area that may store an operating system, applications needed for at least functions, and a data storage area that may store historical data for shipping network traffic, etc. additionally, the memory 902 may include high speed random access memory and may include non-volatile memory such as at least disk storage devices, flash memory devices, or other non-volatile solid state storage devices in embodiments, the electronic device may optionally include a communications component 903, the memory 902 may optionally include memory located remotely from the processor 901, which may be connected to an external device via the communications component 903.
or more modules are stored in memory 902 that, when executed by or more processors 901, perform the methods described above in embodiments of the 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.
It should also be noted that, in some alternative implementations, the functions noted in the blocks 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, and it may also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, may be implemented by special purpose hardware-based systems that 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.
In another aspect, the present disclosure also provides computer-readable storage media, which may be the computer-readable storage media included in the apparatuses described in the above embodiments, or may be the computer-readable storage media that exists separately and is not assembled into the apparatuses, the computer-readable storage media stores or or more programs, and the programs are used by or or more processors to execute 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 (10)
1, A task processing method, comprising:
in response to a preset trigger event, acquiring current distribution data of the target distribution task through at least processors;
updating the closing time of the target distribution task through at least processors according to preset configuration information and the current distribution data, wherein 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 processors in response to the current time reaching the updated closing time of the target delivery task.
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 according to claim 1 or 2, wherein updating the closing time of the target delivery task according to preset configuration information and the current delivery data through at least processors comprises:
when the preset trigger event is an abnormal event, determining the current abnormal event in the current distribution data through at least processors;
determining, by at least processors, a th calculation mode under the current abnormal event in the preset configuration information;
determining, by at least processors, a th calculation factor in the th calculation mode based on the current distribution data;
determining, by at least processors, the closing time based on the th calculation factor and the th calculation.
4. The method according to claim 1 or 2, wherein updating the closing time of the target delivery task according to preset configuration information and the current delivery data through at least processors comprises:
when the preset trigger event is a distribution state change event, determining the current distribution state of the target distribution task according to the current distribution data through at least processors;
determining a second calculation mode in the current distribution state in the preset configuration information through at least processors;
determining, by at least processors, a second calculation factor in the second calculation from the current delivery data;
determining, by at least processors, the closing time based on the second calculation factor and the second calculation.
5. The method according to claim 1 or 2, wherein updating the closing time of the target delivery task according to preset configuration information and the current delivery data through at least processors comprises:
comparing the current distribution data with matching conditions corresponding to the calculation branches in the preset configuration information through at least processors, and determining the closing time according to the calculation mode corresponding to the calculation branches when comparison results.
6. The method of claim 5, wherein comparing, by at least processors, the current distribution data with matching conditions corresponding to calculation branches in the preset configuration information, and when results, determining the closing time according to a calculation manner corresponding to the calculation branches comprises:
determining, by at least processors, a th calculation 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 processors, a second of the computational branches that matches a line of capacity in the current distribution data;
determining, by at least processors, a third calculation branch of the second calculation branches that matches weather data in the current distribution data;
determining, by at least processors, a delivery time in the current delivery data that matches the configuration in the third calculation branch;
determining, by at least processors, the closing time based on the delivery time.
7, A task processing device, comprising:
an response module configured to obtain current distribution data of the target distribution task through at least processors in response to a preset trigger event;
the updating module is configured to update the closing time of the target distribution task according to preset configuration information and the current distribution data through at least processors, wherein 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 at least processors, the target delivery task to an off state in response to the current time reaching the updated off time of the target delivery task.
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.
An electronic device of 9, comprising a memory and at least processors, wherein,
the memory to store or more computer instructions, wherein the or more computer instructions are executable by the at least processors to implement the method of any of claims 1-6 to .
10, computer readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, implement the method of any of claims 1-6 to .
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