CN109685429B - Distribution capacity determining method and device, electronic equipment and storage medium - Google Patents

Distribution capacity determining method and device, electronic equipment and storage medium Download PDF

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CN109685429B
CN109685429B CN201811615651.6A CN201811615651A CN109685429B CN 109685429 B CN109685429 B CN 109685429B CN 201811615651 A CN201811615651 A CN 201811615651A CN 109685429 B CN109685429 B CN 109685429B
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order
target
resource
distribution
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CN109685429A (en
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杨考
伊兵
耿嘉亮
李元哲
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Lazas Network Technology Shanghai Co Ltd
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Abstract

The embodiment of the disclosure discloses a distribution capacity determining method and device, electronic equipment and a storage medium. The distribution capacity determining method comprises the following steps: acquiring the order receiving condition of the target distribution resource when the target distribution resource receives the distribution order; the order receiving condition at least comprises feedback data of the target distribution resource and corresponding preset factors; updating the portrait data of the target distribution resource according to the order receiving condition; and determining the distribution capacity of the target distribution resource according to the portrait data. By the method, the personalized portrait data can be obtained for different target distribution resources, the distribution capability really suitable for the different target distribution resources is determined based on the personalized portrait data, and the distribution quality and the distribution efficiency of distribution tasks can be improved.

Description

Distribution capacity determining 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 method and an apparatus for determining a distribution capability, an electronic device, and a storage medium.
Background
With the deep development of O2O, logistics distribution terminals have become the key point and survival dependence of each large Internet service of O2O, and accurate understanding and mastering of distribution resource information is crucial to improving distribution quality and distribution efficiency.
In a related art, a maximum waybill capability of a distributed resource is usually configured, and if the waybill of the distributed resource exceeds the maximum waybill capability value at any time, the distributed resource is not dispatched. In the scheme, the maximum waybill carrying capacity of the distributed resources is a pseudo proposition, the actual waybill carrying capacity of the distributed resources cannot be reflected in the practical application, and more than 50% of the distributed resources cannot reach the maximum waybill carrying capacity. Even if this maximum waybill capability is statistically derived over time for orders for delivered resources, it is not necessarily accurate.
In another related technique, the waybill capability of a delivery resource is guided by analyzing and summarizing historical waybill data of the delivery resource. In the technical scheme, the data of acquiring and analyzing the order-taking capability of the distribution resources are summarized by learning of historical data, and the original order-taking mode of the distribution resources cannot fully reflect the order-taking willingness of the distribution resources, namely, the most convenient mode for selecting the intended order is not provided for the distribution resources.
Disclosure of Invention
The embodiment of the disclosure provides a distribution capacity determining method and device, electronic equipment and a computer-readable storage medium.
In a first aspect, a delivery capability determining method is provided in the embodiments of the present disclosure.
Specifically, the method for determining the delivery capacity includes:
acquiring the order receiving condition of the target distribution resource when receiving the distribution order; the order receiving condition at least comprises feedback data of the target distribution resource and corresponding preset factors;
updating the portrait data of the target distribution resource according to the order receiving condition;
and determining the distribution capacity of the target distribution resource according to the portrait data.
With reference to the first aspect, in a first implementation manner of the first aspect, the delivery capability is a receipt capability.
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 obtaining an order taking situation of a delivery order pushed by a target delivery resource to a system includes:
acquiring the preset factors, the back order information of the target delivery resources and/or the attribute information of the delivery orders when the delivery orders are received; and/or the presence of a gas in the gas,
and acquiring the preset factor, the back order information of the target delivery resource, the attribute information of the delivery order and/or a rejection reason when the delivery order is rejected.
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 method further includes:
determining a plurality of candidate delivery resources with the number exceeding a preset threshold;
dividing the plurality of candidate dispatch resources into one or more groups according to the similarity of the portrait data;
determining at least one of the candidate delivery resources in each group as a target delivery resource.
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 method further includes:
and pushing the delivery order for the target delivery resource according to a preset scheduling strategy.
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 pushing the delivery order for the target delivery resource according to a preset scheduling policy includes:
And pushing the delivery orders screened out according to the scheduling strategy to the target delivery resources according to multiple dimensions.
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, the fourth implementation manner of the first aspect, and/or the fifth implementation manner of the first aspect, in a sixth implementation manner of the first aspect, the order receiving condition at least further includes dimension data used when the target delivery resource views the delivery order.
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, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, and/or the sixth implementation manner of the first aspect, in a seventh implementation manner of the first aspect, the determining, according to the portrait data, a distribution capability of the target distribution resource includes:
and determining the distribution capacity of the target distribution resources under different preset factors according to the portrait data.
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, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, the sixth implementation manner of the first aspect, and/or the seventh implementation manner of the first aspect, in an eighth implementation manner of the first aspect, the feedback data is feedback data when the target distribution resource accepts or rejects.
In a second aspect, a delivery capability determining apparatus is provided in the disclosed embodiments.
Specifically, the distribution capability determining apparatus includes: the acquisition module is configured to acquire the order receiving condition of the target distribution resource when the distribution order is received; the order receiving condition at least comprises feedback data of the target distribution resource and corresponding preset factors;
an update module configured to update the portrait data of the target delivery resource according to the order taking situation;
a first determination module configured to determine a dispatch capability of the target dispatch resource based on the representation data.
With reference to the second aspect, in a first implementation manner of the second aspect, the delivery capability is a receipt capability.
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 obtaining module includes:
the first obtaining sub-module is configured to obtain the preset factor when the delivery order is received, the back order information of the target delivery resource and/or the attribute information of the delivery order; and/or the presence of a gas in the gas,
and the second obtaining sub-module is configured to obtain the preset factor when the delivery order is rejected, the back order information of the target delivery resource, the attribute information of the delivery order and/or a rejection reason.
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 apparatus further includes:
a second determining module configured to determine a plurality of candidate delivery resources that have been backed up by an amount exceeding a preset threshold;
a partitioning module configured to partition the plurality of candidate delivery resources into one or more groups according to a similarity of the portrait data;
a third determination module configured to determine at least one of the candidate delivery resources in each grouping as a target delivery resource.
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 first aspect, the present disclosure further includes:
the pushing module is configured to push the delivery order for the target delivery resource according to a preset scheduling policy.
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 pushing module includes:
And the pushing submodule is configured to push the delivery orders screened out according to the scheduling strategy to the target delivery resources according to multiple dimensions.
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, the fourth implementation manner of the second aspect, and/or the fifth implementation manner of the second aspect, in a sixth implementation manner of the second aspect, the order taking condition at least further includes dimension data used when the target delivery resource views the delivery order.
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, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, and/or the sixth implementation manner of the second aspect, in a seventh implementation manner of the second aspect, the first determining module includes:
a determination submodule configured to determine delivery capabilities of the target delivery resources under different preset factors according to the representation data. 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.
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, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, the sixth implementation manner of the second aspect, and/or the seventh implementation manner of the second aspect, in an eighth implementation manner of the second aspect, the feedback data is feedback data when the target distribution resource accepts or rejects.
In one possible design, the distribution capability determining apparatus includes a memory and a processor, the memory is used for storing one or more computer instructions for supporting the distribution capability determining apparatus to execute the distribution capability determining method in the first aspect, and the processor is configured to execute the computer instructions stored in the memory. The delivery capability determining apparatus may further include a communication interface for the delivery capability determining apparatus 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 steps of the first aspect.
In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium for storing computer instructions for a distribution capability determining apparatus, where the computer instructions include computer instructions for executing the distribution capability determining method in the first aspect.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
according to the method and the device, the delivery order is continuously pushed to the target delivery resource under the condition that the maximum order taking capability of the target delivery resource is not limited, the order taking condition of the delivery resource to the pushed delivery order is obtained, mainly feedback data of the delivery resource under preset factors is obtained, image data of the target delivery resource is determined according to the order taking condition, and the delivery capability of the delivery resource is determined through the image data. By the method, the personalized portrait data can be obtained for different target distribution resources, the distribution capability really suitable for the different target distribution resources is determined based on the personalized portrait data, and the distribution quality and the distribution efficiency of distribution tasks can be improved.
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.
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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 delivery capability determination method according to an embodiment of the present disclosure;
FIG. 2 illustrates a flow diagram for determining a target dispatch resource component in a dispatch capacity determination method in accordance with one embodiment of the present disclosure;
fig. 3 is a block diagram showing the configuration of a distribution capability determining apparatus according to an embodiment of the present disclosure;
FIG. 4 illustrates a block diagram of a portion of a dispatch capacity determination apparatus for determining target dispatch resources in accordance with one embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device suitable for implementing a delivery capability determination 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, numerals, steps, actions, components, parts, or combinations thereof in the specification, and are not intended to preclude the possibility that one or more other features, numerals, steps, actions, components, parts, or combinations thereof are 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.
Fig. 1 shows a flow chart of a delivery capability determination method according to an embodiment of the present disclosure. As shown in fig. 1, the delivery capability determining method includes the following steps S101 to S103:
in step S101, acquiring an order receiving situation of the target delivery resource when receiving the delivery order; the order receiving condition at least comprises feedback data of the target distribution resource and corresponding preset factors;
in step S102, updating the image data of the target distribution resource according to the order receiving condition;
in step S103, the distribution capability of the target distribution resource is determined based on the image data.
In this embodiment, the target delivery resource may be a human resource and/or a machine resource (such as a vehicle) that is delivered by the system according to a delivery address on the delivery order. When the system schedules the delivery resources, the system can continuously push appropriate delivery orders for the target delivery resources (for example, the delivery address is on the delivery path of the target delivery resources, the pick-up address is closer to the target delivery resources, and the like). After the delivery order is pushed to the target delivery resource, the order taking condition of the target delivery resource for the pushed delivery order can be obtained. The order taking situation at least comprises but is not limited to feedback data of the target distribution resource under preset factors. The preset factors may include, but are not limited to, environmental factors such as weather factors when the pushed delivery order is received, time factors, the target delivery resources themselves (e.g., the number of orders already being placed, the duration of continuous delivery, the number of orders to be picked up, etc.), location factors, etc. The preset factors may be factors which are obtained through data and empirical analysis in advance and can influence the willingness of receiving or rejecting the order of the target distribution resources, and may be specifically set according to the actual situation, which is not limited herein.
In some embodiments, the feedback data is feedback data when the target delivery resource accepts or rejects orders. The feedback data may be active feedback data of the target delivery resource, or may be passive feedback data obtained according to the order taking condition of the target delivery resource, the selection of the target delivery resource, and the like, for example, result data of the order taking or rejection of the target delivery resource, dimension data for screening a push order before the order taking, and the like, and may further include a reason for the order rejection of the target delivery resource (which may be inferred by the system through other data and factors, or may be actively provided by the target delivery resource).
The image data of the target distribution resource may include, but is not limited to, fixed image data and image data that is continuously updated, and in this embodiment, the image data that is continuously updated is updated by a single event. Fixed portrait data includes, but is not limited to, the age, gender, length of order delivery (long order delivery, short order delivery), delivery tools (electric, bicycle, walking, drive, motorcycle), delivery range (within 1KM, within 3KM, long distance); the updatable image data includes, but is not limited to, distribution paths of distribution resources (e.g., like to move on a certain path), attendance periods (Monday, Sunday, day, night, work hours), and some summarized data, such as the number of bills of lading, how far the distribution paths of bills of lading are from, the distribution resources are more conservative (the next bill is received after picking up the goods; the next bill is received after the delivery is completed soon), the shutdown is performed after the distribution of 1 and 2 bills of lading, the distribution resources are more active in bad weather, and so on. The image data of the distribution resource is only an example, and the image data in practical use is not limited to the image data.
According to the method and the device for pushing the orders, the image data of the target distribution resources can be continuously updated according to the order receiving conditions of the target distribution resources on the pushed orders, such as feedback data under different preset factors, and the distribution capacity of the target distribution resources can be determined according to the updated image data.
According to the method and the device, the delivery order is continuously pushed to the target delivery resource under the condition that the maximum order taking capability of the target delivery resource is not limited, the order taking condition of the delivery resource to the pushed delivery order is obtained, mainly feedback data of the delivery resource under preset factors is obtained, image data of the target delivery resource is determined according to the order taking condition, and the delivery capability of the delivery resource is determined through the image data. By the method, the personalized portrait data can be obtained for different target distribution resources, the distribution capacity really suitable for the different target distribution resources is determined based on the personalized portrait data, and the distribution quality and the distribution efficiency of the distribution tasks can be improved.
In an optional implementation manner of this embodiment, the delivery capability is a receipt capability.
In this optional implementation manner, the delivery capacity of the target delivery resource may also be measured by the receipt capability, and the greater the maximum delivery task number that can be received by the receipt capability in a time period, the stronger the delivery capacity of the target delivery resource. A back order refers to the number of dispatch tasks that have been allocated to the target dispatch resource but have not completed the dispatch. It should be noted that, in other embodiments, the delivery capacity may also be measured in combination with other factors, such as the delivery speed of the target delivery resource, the maximum delivery duration of a day, and the like.
In an optional implementation manner of this embodiment, the step S101, that is, the step of obtaining the order receiving condition of the target delivery resource when receiving the delivery order, further includes the following steps:
acquiring the preset factors, the back order information of the target delivery resources and/or the attribute information of the delivery orders when the delivery orders are received; and/or the presence of a gas in the gas,
and acquiring the preset factor, the back order information of the target delivery resource, the attribute information of the delivery order and/or a rejection reason when the delivery order is rejected.
In this optional implementation manner, the order receiving condition of the target delivery resource when receiving the pushed delivery order may be continuously obtained, where the order receiving condition includes result data of receiving the pushed delivery order, preset factors when receiving the delivery order, order backing information of the target delivery resource when receiving the delivery order, and attribute information of the received delivery order itself. For example, the target delivery resource receives a delivery order pushed by the system to the user terminal on the APP of the user terminal, and after checking the property of the delivery order, the target delivery resource accepts the delivery order according to its own condition, and at this time, the system may record preset factors (including current time, current location of the target delivery resource, weather conditions, and the like), receipt information (number of received receipts, number of to-be-received receipts, and the like) of the target delivery resource, and attribute information (including pickup address, delivery path, pickup time, latest delivery time, and the like) of the delivery order at that time.
In this optional implementation manner, preset factors, back order information of the target delivery resource, attribute information of the delivery order, and/or a rejection reason when the target delivery resource rejects the delivery order pushed by the system may also be continuously obtained. For example, if the target delivery resource refuses to accept the delivery order after checking details of the delivery order, the system may record preset factors (including current time, current location of the target delivery resource, weather conditions, and the like), receipt information (quantity of received receipts, and the like) of the target delivery resource, attribute information (including pickup address, delivery route, pickup time, latest delivery time, and the like) of the delivery order, and provide a reason option or an input information field for the target delivery resource to reject the receipt, so that the target delivery resource may actively increase a reason for the rejection, and the system may preliminarily guess the reason for the target delivery resource rejecting the receipt according to various situations at that time.
For example, if the resource is delivered, the number of the rider's back orders under the current environmental factors at the moment of the resource delivery refusal can be calculated in real time; if the rider does not take the order any more, the rider ignores the order by regularly inquiring the condition of the order after the order is assigned, and calculates the number of the rider back orders under the current environmental factors of the rider in real time according to each time inquiry moment. If the distribution resources do not accept the assigned orders, the distribution resources select proper orders by themselves, which indicates that the distribution resources have the willingness to receive orders, but indicates that the distribution orders pushed by the system are not the orders desired by the distribution resources, namely the system does not hold the demands of the distribution resources; the distribution resource order rejection can also indicate the reason of order rejection, and the general conventional reasons comprise factors such as overtime of orders, long order dispatching distance, insufficient electric quantity of riding electric vehicles of riders and the like; and may be the reason for dispatching the resources itself if the dispatching resources are down.
In an optional implementation manner of this embodiment, as shown in fig. 2, the method further includes the following steps S201 to S203:
in step S201, a plurality of candidate delivery resources whose back number exceeds a preset threshold are determined;
in step S202, dividing the candidate distribution resources into one or more groups according to the similarity of the portrait data;
in step S203, at least one of the candidate delivery resources in each group is determined as a target delivery resource.
In the optional implementation mode, the distribution orders are continuously pushed to the target distribution resources, the portrait data of the distribution resources of different types are analyzed based on the statistics of the order taking conditions of the target distribution resources, and the portrait data of the distribution resources are obtained by continuously detecting the initiative order taking willingness data of the distribution resources. Then in some embodiments, to reduce the number of target distribution resources for detection and further improve the image data acquisition efficiency, multiple more similar distribution resources may be merged and one of them may be selected as the target distribution resource. In this case, in order to ensure that the delivery resources that have not been selected after merging can also receive the pushed delivery orders normally, a preset threshold may be set, a plurality of candidate delivery resources that have a quantity exceeding the preset threshold are grouped according to the similarity, and at least one of the candidate delivery resources is selected from each group as the target delivery resource. In this case, the obtained representation data can be used as the representation data of all the distributed resources in the group in which the target distributed resource is located.
In an optional implementation manner of this embodiment, the method further includes the following steps:
and pushing the delivery order for the target delivery resource according to a preset scheduling strategy.
In this optional implementation, a delivery order may be pushed to a target delivery resource based on a preset scheduling policy, and both the portrait data obtained in the embodiment of the present disclosure and the delivery capability obtained based on the portrait data may be fed back to a designer of the scheduling policy, so as to be used by the designer to update the scheduling policy.
In an optional implementation manner of this embodiment, the step of pushing the delivery order for the target delivery resource according to a preset scheduling policy further includes the following steps:
and pushing the delivery orders screened out according to the scheduling strategy to the target delivery resources according to multiple dimensions.
In this optional implementation manner, the preset scheduling policy may screen out a delivery order suitable for the target delivery resource to deliver according to the portrait data, the delivery capability, and the like of the target delivery resource, and push the delivery order to the target delivery resource. In some embodiments, after being pushed to the APP of the target delivery resource, the target delivery resource may be viewed in multiple dimensions, for example, through a delivery path length dimension, a time dimension, a merchant dimension, a price dimension, and the like of the delivery order, and the target delivery resource may be viewed in an ordered manner based on the dimensions and may select to accept an order that is most willing to be delivered by the target delivery resource.
In an optional implementation manner of this embodiment, the order taking condition at least further includes dimension data used when the target delivery resource views the delivery order.
In this optional implementation, after the delivery order is pushed, the system may further obtain dimension data selected when the target delivery resource views the delivery order, and may preliminarily presume data that is more concerned with the target delivery resource based on the dimension data. For example, the target delivery resources generally rank the received delivery orders by path dimension, and select the order receiving with shorter path; the target delivery resource is most often tied to a delivery order from a particular merchant, and so on. These data may be used as image data for describing the target delivery resource as order receiving data of the target delivery resource.
In an optional implementation manner of this embodiment, in step S103, the step of determining a distribution capability of the target distribution resource according to the representation data further includes the following steps:
and determining the distribution capacity of the target distribution resources under different preset factors according to the portrait data.
In the optional implementation manner, after the portrait data of the target delivery resource is determined, since the portrait data is described based on the order taking condition of the target delivery resource corresponding to different preset factors, different delivery capacities can be determined based on different preset factors when the delivery capacity of the target delivery resource is determined, so that the personalized delivery capacity of the target delivery resource can be better embodied.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.
Fig. 3 is a block diagram illustrating a configuration of a distribution capability determining apparatus 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. 3, the delivery capability determining apparatus includes:
an obtaining module 301, configured to obtain an order receiving situation of a target delivery resource when receiving a delivery order; the order receiving condition at least comprises feedback data of the target distribution resource and corresponding preset factors;
an update module 302 configured to update the portrait data of the target delivery resource according to the order taking situation;
a first determination module 303 configured to determine a delivery capability of the target delivery resource based on the representation data.
In this embodiment, the target delivery resource may be a human resource and/or a machine resource (such as a vehicle) that is delivered by the system according to a delivery address on the delivery order. When the system schedules the delivery resources, the system can continuously push appropriate delivery orders for the target delivery resources (for example, the delivery address is on the delivery path of the target delivery resources, the pick-up address is closer to the target delivery resources, and the like). After the delivery order is pushed to the target delivery resource, the obtaining module 301 may obtain the order taking condition of the target delivery resource for the pushed delivery order. The order taking situation at least comprises but is not limited to feedback data of the target distribution resource under preset factors. The preset factors may include, but are not limited to, environmental factors such as weather factors when the pushed delivery order is received, time factors, the target delivery resources themselves (e.g., the number of orders already being placed, the duration of continuous delivery, the number of orders to be picked up, etc.), location factors, etc. The preset factors may be factors which are obtained through data and empirical analysis in advance and can influence the willingness of receiving or rejecting the order of the target distribution resources, and may be specifically set according to the actual situation, which is not limited herein.
In some embodiments, the feedback data is feedback data when the target delivery resource accepts or rejects orders. The feedback data may be active feedback data of the target delivery resource, or may be passive feedback data obtained according to the order taking condition of the target delivery resource, the selection of the target delivery resource, and the like, for example, result data of the order taking or rejection of the target delivery resource, dimension data of the filtered push order before the order taking, and the like, and may further include a reason for the order rejection of the target delivery resource (which may be inferred by the system through other data and factors, or may be actively provided by the target delivery resource).
The image data of the target distribution resource may include, but is not limited to, fixed image data and continuously updated image data, and in this embodiment, the image data that can be continuously updated is updated by a single-on-demand method. Fixed portrait data includes, but is not limited to, the age, gender, duration of delivery (long time, short time), delivery tools (electric, bicycle, walking, drive, motorcycle), delivery range (within 1KM, within 3KM, long distance); the updatable image data includes, but is not limited to, distribution paths of distribution resources (e.g., like to move on a certain path), attendance periods (Monday, Sunday, day, night, work hours), and some summarized data, such as the number of bills of lading, how far the distribution paths of bills of lading are from, the distribution resources are more conservative (the next bill is received after picking up the goods; the next bill is received after the delivery is completed soon), the shutdown is performed after the distribution of 1 and 2 bills of lading, the distribution resources are more active in bad weather, and so on. The image data of the distribution resource is only an example, and the image data in practical use is not limited to the image data.
According to the embodiment of the present disclosure, after the order is pushed each time, the updating module 302 continuously updates the image data of the target distribution resource according to the order receiving condition of the target distribution resource for the pushed order, for example, feedback data under different preset factors, and the first determining module 303 determines the distribution capability of the target distribution resource according to the updated image data.
According to the method and the device, the delivery order is continuously pushed to the target delivery resource under the condition that the maximum order taking capability of the target delivery resource is not limited, the order taking condition of the delivery resource to the pushed delivery order is obtained, mainly feedback data of the delivery resource under preset factors is obtained, image data of the target delivery resource is determined according to the order taking condition, and the delivery capability of the delivery resource is determined through the image data. By the method, the personalized portrait data can be obtained for different target distribution resources, the distribution capability really suitable for the different target distribution resources is determined based on the personalized portrait data, and the distribution quality and the distribution efficiency of distribution tasks can be improved.
In an optional implementation manner of this embodiment, the delivery capability is a receipt capability.
In this optional implementation manner, the delivery capacity of the target delivery resource may also be measured by the receipt capability, and the greater the maximum delivery task number that can be received by the receipt capability in a time period, the stronger the delivery capacity of the target delivery resource. A back order refers to the number of dispatch tasks that have been allocated to the target dispatch resource but have not completed dispatching. It should be understood that in other embodiments, the delivery capacity may be measured in combination with other factors, such as the delivery speed of the target delivery resource, the maximum delivery duration of a day, and the like.
In an optional implementation manner of this embodiment, the obtaining module 301 includes:
the first obtaining sub-module is configured to obtain the preset factor when the delivery order is received, the back order information of the target delivery resource and/or the attribute information of the delivery order; and/or the presence of a gas in the gas,
and the second obtaining sub-module is configured to obtain the preset factor when the delivery order is rejected, the back order information of the target delivery resource, the attribute information of the delivery order and/or a rejection reason.
In this optional implementation manner, the order receiving condition of the target delivery resource when receiving the pushed delivery order may be continuously obtained, where the order receiving condition includes result data of receiving the pushed delivery order, preset factors when receiving the delivery order, order backing information of the target delivery resource when receiving the delivery order, and attribute information of the received delivery order itself. For example, the target delivery resource receives a delivery order pushed by the system to the user terminal on the APP of the user terminal, and after checking the property of the delivery order, the target delivery resource accepts the delivery order according to its own condition, and at this time, the system may record preset factors (including current time, current location of the target delivery resource, weather conditions, and the like), receipt information (number of received receipts, number of to-be-received receipts, and the like) of the target delivery resource, and attribute information (including pickup address, delivery path, pickup time, latest delivery time, and the like) of the delivery order at that time.
In this optional implementation manner, preset factors, back order information of the target delivery resource, attribute information of the delivery order, and/or a rejection reason when the target delivery resource rejects the delivery order pushed by the system may also be continuously obtained. For example, if the target delivery resource refuses to accept the delivery order after checking details of the delivery order, the system may record preset factors (including current time, current location of the target delivery resource, weather conditions, and the like), receipt information (quantity of received receipts, and the like) of the target delivery resource, attribute information (including pickup address, delivery route, pickup time, latest delivery time, and the like) of the delivery order, and provide a reason option or an input information field for the target delivery resource to reject the receipt, so that the target delivery resource may actively increase a reason for the rejection, and the system may preliminarily guess the reason for the target delivery resource rejecting the receipt according to various situations at that time.
For example, if the resource is delivered, the number of the rider's back orders under the current environmental factors at the moment of the resource delivery refusal can be calculated in real time; if the rider does not take the order any more, the rider ignores the order by regularly inquiring the condition of the order after the order is assigned, and calculates the number of the rider back orders under the current environmental factors of the rider in real time according to each time inquiry moment. If the distribution resources do not accept the assigned orders, the distribution resources select proper orders by themselves, which indicates that the distribution resources have the willingness to receive orders, but indicates that the distribution orders pushed by the system are not the orders desired by the distribution resources, namely the system does not hold the demands of the distribution resources; the distribution resource order rejection can also indicate the reason of order rejection, and the general conventional reasons comprise factors such as overtime of orders, long order dispatching distance, insufficient electric quantity of riding electric vehicles of riders and the like; and may be the reason for dispatching the resources itself if the dispatching resources are down.
In an optional implementation manner of this embodiment, as shown in fig. 4, the apparatus further includes:
a second determining module 401 configured to determine a plurality of candidate delivery resources that have been backed up by an amount exceeding a preset threshold;
a partitioning module 402 configured to partition the plurality of candidate delivery resources into one or more groups according to a similarity of the portrait data;
a third determining module 403 configured to determine at least one of the candidate delivery resources in each group as a target delivery resource.
In the optional implementation mode, the distribution orders are continuously pushed to the target distribution resources, the portrait data of the distribution resources of different types are analyzed based on the statistics of the order taking conditions of the target distribution resources, and the portrait data of the distribution resources are obtained by continuously detecting the initiative order taking willingness data of the distribution resources. Then in some embodiments, to reduce the number of target distribution resources for detection and further improve the image data acquisition efficiency, multiple more similar distribution resources may be merged and one of them may be selected as the target distribution resource. In this case, in order to ensure that the delivery resources that have not been selected after merging can also receive the pushed delivery orders normally, a preset threshold may be set, a plurality of candidate delivery resources that have a quantity exceeding the preset threshold are grouped according to the similarity, and at least one of the candidate delivery resources is selected from each group as the target delivery resource. In this case, the obtained representation data can be used as the representation data of all the distributed resources in the group in which the target distributed resource is located.
In an optional implementation manner of this embodiment, the apparatus further includes:
the pushing module is configured to push the delivery order for the target delivery resource according to a preset scheduling policy.
In this optional implementation, a delivery order may be pushed to a target delivery resource based on a preset scheduling policy, and both the portrait data obtained in the embodiment of the present disclosure and the delivery capability obtained based on the portrait data may be fed back to a designer of the scheduling policy, so as to be used by the designer to update the scheduling policy.
In an optional implementation manner of this embodiment, the pushing module includes:
and the pushing submodule is configured to push the delivery orders screened out according to the scheduling strategy to the target delivery resources according to multiple dimensions.
In this optional implementation manner, the preset scheduling policy may screen out a delivery order suitable for the target delivery resource to deliver according to the portrait data, the delivery capability, and the like of the target delivery resource, and push the delivery order to the target delivery resource. In some embodiments, after being pushed to the APP of the target delivery resource, the target delivery resource may be viewed in multiple dimensions, for example, through a delivery path length dimension, a time dimension, a merchant dimension, a price dimension, and the like of the delivery order, and the target delivery resource may be viewed in an ordered manner based on the dimensions and may select to accept an order that is most willing to be delivered by the target delivery resource.
In an optional implementation manner of this embodiment, the order taking condition at least further includes dimension data used when the target delivery resource views the delivery order.
In this optional implementation, after the delivery order is pushed, the system may further obtain dimension data selected when the target delivery resource views the delivery order, and may preliminarily presume data that is more concerned with the target delivery resource based on the dimension data. For example, the target delivery resources generally rank the received delivery orders by path dimension, and select the order receiving with shorter path; the target delivery resource is most often tied to a delivery order from a particular merchant, and so on. These data may be used as image data for describing the target delivery resource as order receiving data of the target delivery resource.
In an optional implementation manner of this embodiment, the first determining module 303 includes:
a determination submodule configured to determine delivery capabilities of the target delivery resources under different preset factors according to the representation data.
In the optional implementation manner, after the portrait data of the target delivery resource is determined, since the portrait data is described based on the order taking condition of the target delivery resource corresponding to different preset factors, different delivery capacities can be determined based on different preset factors when the delivery capacity of the target delivery resource is determined, so that the personalized delivery capacity of the target delivery resource can be better embodied.
Fig. 5 is a schematic structural diagram of an electronic device suitable for implementing a delivery capability determination method according to an embodiment of the present disclosure.
As shown in fig. 5, the electronic apparatus 500 includes a Central Processing Unit (CPU)501 that can execute various processes in the embodiment shown in fig. 1 described above according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The CPU501, ROM502, and RAM503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
In particular, according to embodiments of the present disclosure, the method described above with reference to fig. 1 may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the method illustrated in FIG. 1. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511.
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 on 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 (12)

1. A distribution capability determination method, comprising:
continuously pushing a delivery order for the target delivery resources under the condition of not limiting the maximum order taking capability of the target delivery resources, and acquiring the order receiving condition of the target delivery resources when receiving the delivery order; the order receiving condition at least comprises feedback data of the target distribution resources under preset factors; the profile data for the target delivery resource comprises: fixed image data and continuously updated image data; the feedback data is feedback data when the target distribution resource accepts or rejects;
updating the continuously updated image data according to the order receiving condition;
determining the distribution capacity of the target distribution resources under different preset factors according to the updated portrait data; wherein the delivery capacity is a receipt capacity;
wherein, obtaining the order taking condition of the delivery order pushed by the target delivery resource to the system comprises:
acquiring the preset factors, the back order information of the target delivery resources and/or the attribute information of the delivery orders when the delivery orders are received; and/or the presence of a gas in the gas,
and acquiring the preset factor, the back order information of the target delivery resource, the attribute information of the delivery order and/or a rejection reason when the delivery order is rejected.
2. The method of claim 1, further comprising:
determining a plurality of candidate delivery resources with the number exceeding a preset threshold;
dividing the plurality of candidate distribution resources into one or more groups according to the similarity of the portrait data;
determining at least one of the candidate delivery resources in each group as a target delivery resource.
3. The method according to any one of claims 1-2, further comprising:
and pushing the delivery order for the target delivery resource according to a preset scheduling strategy.
4. The method of claim 3, wherein pushing the delivery order for the target delivery resource according to a preset scheduling policy comprises:
and pushing the delivery orders screened out according to the scheduling strategy to the target delivery resources according to multiple dimensions.
5. The method of claim 4, wherein the order taking situation further comprises at least dimensional data used by the target delivery resource in reviewing the delivery order.
6. A delivery capability determining apparatus, comprising:
the acquisition module is configured to continuously push a delivery order for the target delivery resource without limiting the maximum order taking capability of the target delivery resource, and acquire an order receiving condition of the target delivery resource when receiving the delivery order; the order receiving condition at least comprises feedback data of the target distribution resources under preset factors; the representation data of the target delivery resource comprises: fixed image data and continuously updated image data; the feedback data is feedback data when the target distribution resource accepts or rejects;
An update module configured to update the continuously updated portrait data according to the order taking situation;
a first determining module configured to determine, according to the updated portrait data, a delivery capacity of the target delivery resource under different preset factors; wherein the delivery capacity is the receipt capacity;
wherein the acquisition module comprises:
the first obtaining sub-module is configured to obtain the preset factor when the delivery order is received, the back order information of the target delivery resource and/or the attribute information of the delivery order; and/or the presence of a gas in the atmosphere,
and the second obtaining sub-module is configured to obtain the preset factor when the delivery order is rejected, the back order information of the target delivery resource, the attribute information of the delivery order and/or a rejection reason.
7. The apparatus of claim 6, further comprising:
a second determining module configured to determine a plurality of candidate delivery resources that have been backed up by an amount exceeding a preset threshold;
a partitioning module configured to partition the plurality of candidate delivery resources into one or more groups according to a similarity of the portrait data;
a third determination module configured to determine at least one of the candidate delivery resources in each grouping as a target delivery resource.
8. The apparatus of any of claims 6-7, further comprising:
the pushing module is configured to push the delivery order for the target delivery resource according to a preset scheduling policy.
9. The apparatus of claim 8, wherein the pushing module comprises:
and the pushing submodule is configured to push the delivery orders screened out according to the scheduling strategy to the target delivery resources according to multiple dimensions.
10. The apparatus of claim 9, wherein the order taking situation further comprises at least dimensional data used by the target delivery resource in reviewing the delivery order.
11. An electronic device comprising 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 steps of any of claims 1-5.
12. A computer-readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, carry out the method steps of any of claims 1-5.
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