CN107563572B - Order allocation method and device, computer equipment and storage medium - Google Patents
Order allocation method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses an order allocation method, an order allocation device, computer equipment and a storage medium, wherein the order allocation method comprises the following steps: screening candidate order distributors meeting preset conditions according to the real-time order information; if the number of the candidate order distributors is larger than a preset threshold value, calculating a distribution recommended value of the candidate order distributors; and determining target order distributors according to the distribution recommended value sequence, and pushing order distribution information to the target order distributors. The embodiment of the invention solves the problem of low delivery quality caused by failure in consideration of historical delivery records, credit and order completion rate of deliverers in the prior art, realizes reasonable distribution of orders, and improves user experience and order delivery efficiency.
Description
Technical Field
The embodiment of the invention relates to the technical field of internet, in particular to an order allocation method, an order allocation device, computer equipment and a storage medium.
Background
With the rapid development of economy and the popularization of the internet, especially the gradual maturity of electronic commerce, more and more users tend to place orders for shopping in the internet, fast food restaurants, supermarkets and the like, and the distribution of the orders of logistics after the orders are placed by the users plays a crucial role.
At present, when logistics distribution is performed after a user places an order, a distributor is selected mainly according to a nearby principle, namely, a picking distance of the distributor is judged, and an order is distributed to the distributor close to the distance according to a judgment result. However, in the above prior art scheme, the historical delivery records, the personal credit and the order completion rate of the deliverer are not considered, so that the overall delivery quality is low, and the user experience and the order delivery efficiency are reduced. In order to improve the user experience and the order dispatching efficiency, the orders need to be reasonably distributed.
Disclosure of Invention
The embodiment of the invention provides an order distribution method, an order distribution device, computer equipment and a storage medium, which are used for realizing reasonable distribution of orders and improving user experience and order dispatching efficiency.
In a first aspect, an embodiment of the present invention provides an order allocation method, where the method includes:
screening candidate order distributors meeting preset conditions according to the real-time order information;
if the number of the candidate order distributors is larger than a preset threshold value, calculating a distribution recommended value of the candidate order distributors;
and determining target order distributors according to the distribution recommended value sequence, and pushing order distribution information to the target order distributors.
In a second aspect, an embodiment of the present invention further provides an order distribution apparatus, where the apparatus includes:
the candidate order distributor screening module is used for screening candidate order distributors meeting preset conditions according to the real-time order information;
the delivery recommendation value calculation module is used for calculating the delivery recommendation values of the candidate order distributors if the number of the candidate order distributors is greater than a preset threshold value;
and the order distribution information pushing module is used for determining a target order distributor according to the distribution recommended value sequence and pushing order distribution information to the target order distributor.
In a third aspect, an embodiment of the present invention further provides a computer device, where the computer device includes:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the order allocation method as described above.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the order allocation method described above.
The embodiment of the invention provides an order distribution method, an order distribution device, computer equipment and a storage medium, wherein target order distributors are determined according to the distributor distribution recommended value sequence of real-time orders, and order distribution information is pushed to the target order distributors, so that the problem of low distribution quality caused by the fact that historical distributor distribution records, credit and order completion rate are not considered in the prior art is solved, the order is reasonably distributed, and the user experience and the order distribution efficiency are improved.
Drawings
FIG. 1 is a flow chart illustrating an order allocation method according to a first embodiment of the present invention;
FIG. 2 is a flowchart illustrating an order allocation method according to a second embodiment of the present invention;
FIG. 3 is a flow chart illustrating an order allocation method according to a third embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an order allocation apparatus according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer device in the fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart illustrating an order allocation method according to an embodiment of the present invention, where the order allocation method according to the embodiment of the present invention may be executed by an order allocation apparatus, and the order allocation apparatus may be implemented by software and/or hardware and may be disposed in a computer device. As shown in fig. 1, the order allocation method includes:
and 110, screening candidate order distributors meeting preset conditions according to the real-time order information.
In this embodiment, the real-time order information may be order allocation configuration item data generated when the user issues an order message, for example, the configuration item data may include an order name and number information; type and parameter information of the order may also be included, such as: the order parameter information may be order location, quantity, size, valuables, logistics preferences, and the like. The preset conditions may be whether the order configuration item data is satisfied, for example, to verify whether the order type matches the order type or the preference type that the delivery person can deliver, to verify whether the order location is within the delivery range of the delivery person, to verify whether the destination that the order needs to be delivered is in the list of destinations that the order delivery person can deliver, etc. The preset conditions among different orders are not limited to be consistent, and adjustment and selection can be performed according to the order configuration item data of the real-time orders and the delivery information of the deliverer. The candidate order dispatchers may be order dispatchers that meet preset conditions screened from dispatchers registered with the order distribution system account based on the order distribution profile data for the real-time order. It is noted that the candidate order dispatchers only initially select a qualified set of order dispatchers, and that further screening against the candidate order dispatchers is subsequently required.
Optionally, the step of screening candidate order distributors meeting the preset conditions according to the real-time order information may specifically be: and judging whether the deliverers in the preset position range meet preset conditions or not by taking the real-time order positions as centers according to the real-time order information, and counting the order deliverers to generate a candidate order deliverer set if the deliverers meet the preset conditions. Illustratively, assume that the order information includes: the order position is at point A, and the order distribution destination is at point B in the area B; four distributors of A, B, C and T are distributed at the positions 1km, 1.5km, 1.8km and 3km away from the A point respectively, the order destination range of the A distribution can be a, B, c and d, the order destination range of the B distribution can be a, B and c, the order destination range of the C distribution can be a, c and d, the order destination range of the D distribution can be a, B, c and d, the three distributors of A, B and C are searched within 2km with the A point of the real-time order position as the center according to the information of the user order, and only two distributors of A and B are found according with the condition of the A point of the order distribution destination range at the B point in the area, so that the two distributors of A and B can be used as candidate order distributors.
Optionally, before the step of screening candidate order distributors meeting the preset conditions according to the real-time order information, the method further includes: and obtaining order user information and order distributor information.
In this embodiment, a user ordering system may be registered before ordering, and the user may set the user's own requirements in the requirement items in the user ordering system when ordering, for example, which users pay attention and which do not pay attention in the order distribution process. The user can be quickly allocated with the appropriate deliverer through the intuitive demands of the user in the order delivery process. The order user information comprises user requirements and can be directly obtained from the server. Correspondingly, the order distributor information can also be directly pulled from the basic information entered when the distributor registers the account. The order distributor information may include distributor names, distribution ranges, distribution types, historical order data, and the like.
And 120, if the number of the candidate order distributors is larger than a preset threshold value, calculating a distribution recommended value of the candidate order distributors.
In this embodiment, after the candidate order distributors are screened out, it may be determined whether the number of the candidate order distributors reaches a preset number threshold, and if the number of the candidate order distributors reaches the preset number threshold, the recommended value of the candidate order distributors may be continuously calculated. The recommended value of the order distributor can be calculated according to factors influencing user experience and order dispatching efficiency in the order distribution process to obtain the order distribution recommended value of the order distributor. In general, the higher the delivery recommended value of the order distributor, the easier it is to assign the order, and the specific calculation manner is explained in detail in the following embodiments.
Optionally, if the number of candidate order dispatchers does not reach the preset number threshold, the order grabbing mode may be started to allow all the dispatchers to grab orders for delivery.
And step 130, determining target order distributors according to the distribution recommended value sequence, and pushing order distribution information to the target order distributors.
In this embodiment, the candidate order distributors may be ranked according to the calculated delivery recommended values of the candidate order distributors, the candidate order distributors in the previous order may be determined as target order distributors according to the ranking order, and the order distribution information may be pushed to the target order distributors. The order allocation information may be part of the order information, not all of the order information. Optionally, the order distribution information may be the position of the order, which has an advantage that after the order distribution information is pushed to the target order distributor, the target order distributor may select whether to take the order according to some information in the order distribution information; meanwhile, only the order distribution information is pushed to the target order distributor, so that the fairness of order distribution can be ensured, and the problem that the target order distributor intentionally refuses orders due to the problems that the orders are difficult or the orders do not accord with own interests and the like after the target order distributor knows all the order information is avoided.
According to the order distribution method provided by the embodiment of the invention, the target order distributor is determined according to the distributor distribution recommended value sequence of the real-time orders, and the order distribution information is pushed to the target order distributor, so that the problem of low distribution quality caused by no consideration of historical distributor distribution records, credit and order completion rate in the prior art is solved, the reasonable distribution of the orders is realized, and the user experience and the order distribution efficiency are improved.
Example two
Fig. 2 is a flowchart illustrating an order allocation method according to a second embodiment of the present invention, where the step of calculating the delivery recommendation value of the candidate order deliverer is further optimized based on the first embodiment. As shown in fig. 2, the order allocation method includes:
and step 210, screening candidate order distributors meeting preset conditions according to the real-time order information.
And step 220, if the number of the candidate order distributors is larger than a preset threshold value, determining an influence factor of the distribution recommended value of the candidate order distributors and a weight proportion of the influence factor.
Specifically, after the candidate order distributors are screened out, whether the number of the candidate order distributors reaches a preset number threshold value or not can be judged, and if the number of the candidate order distributors reaches the preset number threshold value, the influence factors of the distribution recommended values of the candidate order distributors and the weight ratios corresponding to the influence factors are determined. Optionally, the impact factor includes at least one of an expected pickup time, an expected delivery time, a credit score, or an order taking rate.
The impact factors and respective impact factor weight ratios for the delivery recommendations of candidate order dispatchers are described in detail below.
In this embodiment, the predicted pickup time may be the time that the order distributor needs to take from the order receiving determination to the pick-up at the home after the order issued by the user, or may be calculated by multiplying the predicted pickup distance by the pickup time. The predicted pickup distance may be a distance between the order position and a starting position when the order distributor prepares to pick up the piece, and the pickup time limit may be a time required for the order distributor to move a unit distance during the pickup process, for example, the pickup time limit may be s/m or h/km.
In order to more clearly show the role played by the pickup time in the delivery recommended value of the candidate order distributor, according to the central limit theorem and a large number of sample experimental verifications, it can be obtained that the role played by the pickup time in the delivery recommended value of the candidate order distributor follows normal distribution, that is: f (t)1):N(u,2) The calculated corresponding distribution function is:
because the calculation complexity of the integral function is higher, the following piecewise function is established by using the piece taking time as a variable, and the piece taking time can be converted into a corresponding piece taking time recommendation value score by the piecewise function, wherein the piecewise function is specifically:
wherein f isT(t1) A function for calculating recommended values of the pickup time in sections, which is used for reflecting the scores of the pickup time influence factors corresponding to the pickup time when calculating the distribution recommended values of the candidate order distributors, t1For taking piece time, the unit is 'second', n is a time conversion coefficient, and the time t can be converted1The unit is converted from second to minute, and n can be specifically: n-1/60, T1First picking time segment threshold, T, for a segment picking time function2Second pickup time segment threshold, T, for a segment pickup time function1And T2Can be preset, and optional, T1And T2May be set to 600 seconds and 1200 seconds, respectively. It should be noted that, in the above-mentioned piece-by-piece taking time function, T1And T2The value of (A) can be set according to the actual order distribution operation conditions, for example, in the first-line city, the traffic is developed, the logistics industry develops rapidly, and the T is set1And T2Two thresholds may be set to 600 seconds and 1200 seconds, respectively; and in the second-line city logistics industry, the development is slower than that of the first-line city, the pickup location is possibly far away, the pickup time threshold is properly prolonged, and T is set1And T2Two thresholds may be set to 1200 seconds and 1800 seconds, respectively.
In this embodiment, the estimated delivery time may be the time from the start of the pick-up to the end of the delivery of the order to the destination after the order distributor has picked up the order, or may be calculated by multiplying the estimated delivery distance by the delivery time. The predicted delivery distance can be the distance between the order position and the destination position to which the order needs to be delivered, and the delivery time can be the time required for moving the distance of a unit in the delivery process of the order distributor, for example, the delivery time can be s/m or h/km.
Accordingly, in order to more clearly show the role of delivery time in the delivery recommendation of candidate order distributors, the embodiment of the present invention establishes a continuous function using delivery time as a variable, and the continuous function can convert the expected delivery time into a recommendation score of a corresponding delivery time, where the piecewise function is specifically:
fS＝max[0,100-n·t2]
wherein f isS(t2) A function for calculating a recommendation value for a continuous delivery time for reflecting a scoring value of a delivery time impact factor corresponding to the delivery time when calculating a delivery recommendation value for a candidate order distributor, t2To send piecesThe unit of time is 'second', n is a time conversion coefficient, and the time t can be converted2The unit of (a) is converted from second to minute, and n is specifically: and n is 1/60.
In this embodiment, the credit score reflects an evaluation value of the user to the order distributor in the order distribution process, after the order distributor completes the order distribution each time, the user may evaluate and score the order distribution of the order distributor this time, a result of the evaluation and scoring of the user may be stored in the order distribution system database, and the server may process a historical evaluation result in the database to obtain a more intuitive credit score, for example, an average value obtained by averaging the historical evaluation results in the database is recorded as the credit score. In order to more clearly represent the role of the reputation score in the distribution recommendation value of the candidate order distributor, the embodiment of the invention can be represented by a reputation score recommendation value piecewise function, and the reputation score can be converted into a corresponding reputation score recommendation value score by the piecewise function, wherein the piecewise function specifically comprises the following steps:
wherein f isC(t3) Calculating a piecewise function for the reputation score recommendation value for reflecting the scoring value of the reputation score impact factor corresponding to the reputation score when calculating the delivery recommendation value of the candidate order distributor, t3Is the magnitude of the credit score, T3For the reputation score standard threshold, a and B are weighted proportional values whose reputation scores are greater than the standard threshold and whose reputation scores are less than the standard threshold, respectively, it should be noted that the values of a and B are not the same, to a certain extent, a may represent a reputation score reward coefficient for an order distributor when the reputation score of the order distributor is greater than the standard threshold, and B may represent a reputation score penalty coefficient for the order distributor when the reputation score of the order distributor is less than the standard threshold, for example, a is set to 1.2, B is set to 0.8, and specific setting values of a and B are not limited herein and may be set according to actual conditions. Optionally, the reputation score can be calculated according to the specific reputation score of the order distributor in a recent period of timeThe price condition is adaptively adjusted, so that the condition that the user intentionally evaluates the low credit score to cause follow-up calculation or always calculate according to historical data is avoided, and the accuracy and the fairness of the credit score recommendation value are improved.
In this embodiment, the order taking rate may be defined as: the order receiving rate is 1-order reject rate, correspondingly, in the case of (the finished order amount + the cancelled order amount + the order reject amount is 0), the order reject rate is 0, and in the case of (the finished order amount + the cancelled order amount + the order reject amount is not equal to 0), the order reject rate is the order reject amount/(the finished order amount + the cancelled order amount + the order reject amount), wherein the finished order amount may be the number of orders which the order distributor successfully completes order distribution after order receiving or order grabbing; the order canceling amount can be the amount of the order which the order distributor agrees to cancel the order after negotiation due to other problems of the order distributor or the user after order taking or order grabbing; the amount of refusal may be the number of orders that the order distributor refuses to deliver without negotiation with the user after order taking or order grabbing.
In order to more clearly show the role of the order taking rate in the delivery recommendation values of the candidate order distributors, the embodiment of the present invention may use a piecewise function of the order taking rate recommendation value to represent, and the order taking rate may be converted into a corresponding score of the order taking rate recommendation value through the piecewise function, where the piecewise function specifically is:
wherein f isR(t4) Calculating a piecewise function for the order taking rate recommendation value for reflecting the scoring value of the corresponding order taking rate impact factor of the order taking rate when calculating the delivery recommendation value of the candidate order distributor, t4To measure the order rate, T3And T4Two standard thresholds for picking rate, R1The order rate is greater than T3% time penalty award coefficient, R2The order rate is greater than T4% and less than T3% penalty award coefficient and R3The order rate is less than T4% penalty award coefficient, where R1、R2And R3The value of (a) can be set appropriately according to the actual reward and punishment system, for example, R is set1、R2And R3Are 1.2, 1 and 0.8 respectively, in which case R1May represent the reward factor, R, for higher rates of orders2The order rate is at a medium level with neither reward nor penalty, R3Can represent the penalty coefficient when the bill receiving rate is lower, by pair R1、R2And R3The parameter setting is beneficial to prompting the order distributor to receive orders, and the order distribution efficiency is improved.
It should be noted that, because no limitation on the number of times of rejection is made before the order allocation method adopted in the embodiment of the present invention is implemented, in order to avoid influence of historical data on order dispatching fairness, when the rate of rejection or the rate of order pickup is calculated, data 5 month and 15 days before 2017 is filtered and two bits after the data is accurate to the percentage, the rate of order pickup is not calculated in real time, and 00 times per day can be selected: 00, the order receiving rate of the order distributor is updated, and server overload operation caused by real-time calculation of the order receiving rate is avoided.
In this embodiment, the weight ratio of the estimated pickup time, the estimated delivery time, the credit score or the order receiving rate may be set according to the actual operation environment when the order allocation method according to the embodiment of the present invention is adopted. Optionally, the weight proportion of the predicted pickup time, the predicted delivery time, the credit score or the order receiving rate is specifically set according to different regions, for example, due to the fast rhythm of the first-line city, the user cannot wait for pickup all the time after placing an order, so that the user is more interested in the predicted pickup time but less interested in the delivery time, and thus when the order distribution method of the embodiment of the invention is adopted in the first-line city, the weight proportion of the predicted time can be distributed to a larger amount, and the delivery time can be distributed to a smaller amount. In two-wire cities, where the order location may be remote, the user is more on delivery time, and the weight of the projected time may be assigned less in proportion to the delivery time and greater in configuration. For example, in the first-line city, the weight ratio of the estimated pickup time, the estimated delivery time, the credit score or the pick-up rate can be set to 6:4:4:2, while in the second-line city, the weight ratio can be set to 3:4:4:5, which is only given as an example and is not limited, and the specific set ratio can be used for obtaining the aspects to which the user prefers according to the user evaluation content or information gathering and then carrying out reasonable weight setting.
And step 230, determining a delivery recommendation value of the candidate order deliverer according to the influence factor and the weight proportion.
Specifically, the delivery recommendation value of the candidate order distributor may be calculated according to a weighted sum between the influence factor and the weight ratio.
Optionally, calculating a delivery recommended value of the candidate order deliverer according to a weighted sum of the influence factor and the weight ratio, specifically:
according to the formula w ═ a · fT+b·fS+c·fC+d·fRCalculating a delivery recommended value of the candidate order deliverer; wherein W is the delivery recommendation of the candidate order deliverer, fTFor the predicted pickup time of the candidate order distributor to correspond to the recommended value, fSFor the predicted delivery time of the candidate order distributor to correspond to the recommended value, fCAssigning a recommendation value to the candidate order distributor's reputation score, fRThe method comprises the steps of obtaining a recommended value corresponding to the order taking rate of the candidate order distributor, a being the weight proportion of the predicted order taking time of the candidate order distributor corresponding to the recommended value, b being the weight proportion of the predicted delivery time of the candidate order distributor corresponding to the recommended value, c being the weight proportion of the credit score of the candidate order distributor corresponding to the recommended value, and d being the weight proportion of the recommended value corresponding to the order taking rate of the candidate order distributor.
For example, when the determined target order distributor is a distributor of three, i.e., a first distributor, a second distributor and a third distributor, the specific information of the order distributor is as follows:
the order receiving rate of the first order distributor is 90.9%, the credit score is 5 minutes, the pickup distance is 2740 meters, and the distribution time effectiveness is 0.315 s/m;
the order receiving rate of the order B distributor is 90.1%, the credit score is 4.9 minutes, the pickup distance is 1816 meters, and the distribution timeliness is 0.374 s/m;
the order receiving rate of the third order distributor is 75.1%, the credit score is 5 minutes, the pickup distance is 2673 meters, and the distribution timeliness is 0.155 s/m;
according to actual conditions, after the weights of all factors are distributed, the scores of the first order distributor 470.67, the scores of the second order distributor 462.54 and the scores of the third order distributor 461.61 are calculated, and the calculation results of the recommended values of the order distributors can show that: although the third order distributor is closer to the pickup position, the first order distributor and the real-time order are judged to have higher order matching degree by calculating the recommended value, and the order is distributed to the first order distributor.
And 240, determining a target order distributor according to the distribution recommended value sequence, and pushing order distribution information to the target order distributor.
According to the order distribution method provided by the embodiment of the invention, the distribution recommended value of the candidate order distributor is calculated according to the weighting sum between the influence factor and the weight proportion of the recommended value of the order distributor, and the order distribution message is pushed to the order distributor with the priority of the distribution recommended value ahead, so that the problem of unreasonable distribution caused by the fact that the distribution records, credit and order completion rate of historical distributors are not considered in the prior art is solved, the reasonable distribution of orders is realized, and the user experience and the order distribution efficiency are improved.
EXAMPLE III
Fig. 3 is a flowchart of an order allocation method according to a third embodiment of the present invention, and this embodiment further optimizes the steps of determining target order distributors according to the distribution recommendation value sequence and pushing order allocation information to the target order distributors based on the first and second embodiments. As shown in fig. 3, the order allocation method includes:
and 310, screening candidate order distributors meeting preset conditions according to the real-time order information.
If the number of candidate order dispatchers is greater than the predetermined threshold, go to step 330: and calculating the delivery recommended value of the candidate order deliverer.
If the number of candidate order dispatchers is less than or equal to the predetermined threshold, go to step 380: and starting a list grabbing mode to carry out list grabbing distribution on the real-time orders.
Specifically, if the number of candidate order distributors does not reach a preset threshold value, an order grabbing mode is started to carry out order grabbing distribution on the real-time order. Wherein, starting the order grabbing mode to carry out order grabbing and delivery on the real-time order may specifically include: pushing order distribution information to all order distributors who start to receive orders and are in an idle state; if the order distributor takes the order within the preset interval time, screening the order distributor meeting the conditions according to the credit score of the order distributor; and determining the order distributor with the front priority as the order distributor for carrying out order distribution from the order distributors with the screening conforming conditions according to the credit priority ranking, and pushing all order information to the mobile terminal of the order distributor.
And 340, carrying out priority ranking on the candidate order distributors according to the distribution recommended values.
And step 350, selecting the candidate order distributor with high priority as the target order distributor according to the priority sequence.
And step 350, judging whether the target order distributor starts order receiving and is in an idle state.
If the target order distributor starts order taking and is in an idle state, go to step 370: and pushing the real-time order distribution information to a target order distributor.
If the target order distributor does not start order taking or is not in an idle state, the method returns to execute step 310: and screening candidate order distributors meeting preset conditions according to the real-time order information.
In this embodiment, if the target order distributor does not start order taking and/or is not in an idle state, the order distribution information is continuously pushed to other candidate order distributors, except the target order distributor, which meet the preset conditions until the order distribution information is pushed successfully. Specifically, in the pushing process, the determined target order distributor may not open the order and/or be in the idle state, and at this time, the target order distributor that has not opened the order and/or is not in the idle state may be deleted, and the process continues to return to step 310: and screening candidate order distributors meeting preset conditions according to the real-time order information.
Optionally, if the number of candidate order distributors does not reach a preset threshold or the order is rejected after the pushing of the real-time order distribution information is successful, the order grabbing mode is started to carry out order grabbing distribution on the real-time order.
Specifically, after the order distribution information is successfully pushed to the order distributor, the order distributor may reject the order. And after the order pusher refuses the order, the order grabbing mode can be continuously started to carry out order grabbing and distribution on the real-time order. And meanwhile, recording the rejection amount of the order distributor, optionally recording the day-time rejection amount of the order distributor, and performing corresponding punishment on the order distributor according to the rejection amount, for example, after the day-time rejection amount reaches three, a certain bonus can be punished or credit score can be reduced, and the like.
According to the order distribution method provided by the embodiment of the invention, after the order distributor is selected to push the order distribution information according to the recommended value of the order distributor, an order grabbing mode is added to grab orders, so that the problem that the order distribution is not timely due to the fact that the order distributor can not receive orders when the order distributor is busy and the order distribution method meets the conditions caused by the fact that the order distribution method is singly adopted is solved, and the user experience and the order distribution efficiency are improved.
Example four
Fig. 4 is a schematic structural diagram of an order allocation apparatus according to a fourth embodiment of the present invention, where the order allocation apparatus according to the fourth embodiment of the present invention executes the order allocation method according to any one of the embodiments described above, and the apparatus may be implemented in a software and/or hardware manner. As shown in fig. 4, the order distribution apparatus includes:
and a candidate order distributor screening module 410, configured to screen candidate order distributors meeting the preset conditions according to the real-time order information.
And a delivery recommendation value calculation module 420, configured to calculate a delivery recommendation value of the candidate order distributor if the number of candidate order distributors is greater than a preset threshold.
Optionally, the delivery recommendation value calculating module includes:
the distribution recommendation value influence factor determining unit is used for determining the influence factor of the distribution recommendation value of the candidate order distributor and the weight proportion of the influence factor;
and the delivery recommendation value calculation unit is used for determining the delivery recommendation values of the candidate order distributors according to the influence factors and the weight proportion.
Wherein the influencing factor comprises at least one of: predicting pick-up time, predicted delivery time, credit score or order receiving rate; correspondingly, the delivery recommendation value calculating unit comprises: and the distribution recommended value weighting and calculating subunit is used for calculating the distribution recommended values of the candidate order distributors according to the weighted sum between the influence factors and the weight proportion.
And the order distribution information pushing module 430 is configured to determine a target order distributor according to the distribution recommended value sequence, and push order distribution information to the target order distributor.
Optionally, the order distribution information pushing module includes:
the candidate order distributor sorting unit is used for carrying out priority sorting on the candidate order distributors according to the distribution recommended values;
the candidate order distributor determining unit is used for selecting the candidate order distributor with high priority as the target order distributor according to the priority sequence;
correspondingly, the order distribution information pushing module further comprises:
and the order distribution information pushing unit is used for judging the order receiving state of the target order distributor, and pushing the real-time order distribution information to the target order distributor if the target order distributor starts the order receiving and is in an idle state.
On the basis of the embodiment of the present invention, optionally, the order distribution apparatus further includes:
the order allocation information circular pushing module 440 is configured to, if the target order distributor does not start order taking and/or is not in an idle state, continue to push order allocation information to other candidate order distributors meeting the preset condition except the target order distributor until the order allocation information is pushed successfully.
On the basis of the embodiment of the present invention, optionally, the order distribution apparatus further includes:
and the order grabbing module 450 is configured to, if the number of candidate order distributors does not reach a preset threshold or the order is rejected after the real-time order distribution information is successfully pushed, start an order grabbing mode to carry out order grabbing and distribution on the real-time order.
The order distribution device provided by the embodiment of the invention can execute the order distribution method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects for executing the method.
EXAMPLE five
Fig. 5 is a schematic structural diagram of a computer device according to a fifth embodiment of the present invention. FIG. 5 illustrates a block diagram of an exemplary computer device 512 suitable for use in implementing embodiments of the present invention. The computer device 512 shown in FIG. 5 is only an example and should not bring any limitations to the functionality or scope of use of embodiments of the present invention.
As shown in FIG. 5, computer device 512 is in the form of a general purpose computing device. Components of computer device 512 may include, but are not limited to: one or more processors 516, a system memory 528, and a bus 518 that couples the various system components including the system memory 528 and the processors 516.
Computer device 512 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by computer device 512 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 528 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)530 and/or cache memory 532. The computer device 512 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 534 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 518 through one or more data media interfaces. Memory 528 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 540 having a set (at least one) of program modules 542, including but not limited to an operating system, one or more application programs, other program modules, and program data, may be stored in, for example, the memory 528, each of which examples or some combination may include an implementation of a network environment. The program modules 542 generally perform the functions and/or methods of the described embodiments of the invention.
The computer device 512 may also communicate with one or more external devices 514 (e.g., keyboard, pointing device, display 524, etc.), with one or more devices that enable a user to interact with the computer device 512, and/or with any devices (e.g., network card, modem, etc.) that enable the computer device 512 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 522. Also, computer device 512 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via network adapter 520. As shown, the network adapter 520 communicates with the other modules of the computer device 512 via the bus 518. It should be appreciated that although not shown in FIG. 5, other hardware and/or software modules may be used in conjunction with computer device 512, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processor 516 executes various functional applications and data processing by running programs stored in the system memory 528, for example, implementing the order allocation method provided by the embodiment of the present invention, including:
screening candidate order distributors meeting preset conditions according to the real-time order information;
if the number of the candidate order distributors is larger than a preset threshold value, calculating a distribution recommended value of the candidate order distributors;
and determining target order distributors according to the distribution recommended value sequence, and pushing order distribution information to the target order distributors.
EXAMPLE six
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements an order allocation method provided in an embodiment of the present invention, where the computer program includes:
screening candidate order distributors meeting preset conditions according to the real-time order information;
if the number of the candidate order distributors is larger than a preset threshold value, calculating a distribution recommended value of the candidate order distributors;
and determining target order distributors according to the distribution recommended value sequence, and pushing order distribution information to the target order distributors.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (12)
1. An order allocation method, characterized in that the method comprises:
screening candidate order distributors meeting preset conditions in a preset position range by taking the real-time order positions as centers according to the real-time order information; the preset conditions comprise whether the order distribution configuration item data of the real-time order meet order dispatchers; whether the order allocation configuration item data satisfies the order distributor includes: checking whether the order type is matched with the order type or the preference type delivered by a delivery person, checking whether the order position is within the delivery range of the delivery person, and checking whether the destination to be delivered by the order is in a destination list delivered by the order delivery person;
if the number of the candidate order distributors is larger than a preset threshold value, calculating a distribution recommended value of the candidate order distributors; the delivery recommendation value is determined according to influence factors influencing user experience and delivery efficiency in the order delivery process; the impact factors include at least one of: predicting pick-up time, predicted delivery time, credit score or order receiving rate;
determining target order distributors according to the distribution recommended value sequence, and pushing order distribution information to the target order distributors; the order distribution information only comprises partial information of the real-time order information;
if the number of the candidate order distributors does not reach a preset threshold value or orders are rejected after the order distribution information is pushed successfully, starting an order grabbing mode to carry out order grabbing distribution on the real-time orders; wherein, the implementation of the order grabbing and distribution to the real-time order comprises the following steps: and if the order distributor robs the order within the preset interval time, screening the order distributor meeting the conditions according to the credit score of the order distributor so as to push order distribution information.
2. The method of claim 1, wherein said calculating a delivery recommendation for the candidate order deliverer comprises:
determining an influence factor of the delivery recommendation value of the candidate order deliverer and a weight proportion of the influence factor;
and determining the delivery recommended value of the candidate order deliverer according to the influence factor and the weight proportion.
3. The method of claim 2, wherein said determining a delivery recommendation for said candidate order deliverer based on said impact factor and said weight ratio comprises:
and calculating the delivery recommendation value of the candidate order deliverer according to the weighted sum of the influence factor and the weight proportion.
4. The method of claim 1, wherein said ordering target order dispatchers according to the delivery recommendation value comprises:
carrying out priority ranking on the candidate order distributor according to the distribution recommended value;
selecting candidate order distributors with high priority as target order distributors according to the priority sequence;
correspondingly, the pushing order distribution information to the target order distributor further includes:
and judging the order receiving state of the target order distributor, and pushing the order distribution information to the target order distributor if the target order distributor starts the order receiving and is in an idle state.
5. The method of claim 4, further comprising:
and if the target order distributor does not start order taking and/or is not in an idle state, continuously pushing order distribution information to other candidate order distributors except the target order distributor, which meet the preset conditions, until the order distribution information is pushed successfully.
6. An order distribution apparatus, characterized in that the apparatus comprises:
the candidate order distributor screening module is used for screening candidate order distributors meeting preset conditions in a preset position range by taking the real-time order positions as centers according to the real-time order information; the preset conditions comprise whether the order distribution configuration item data of the real-time order meet order dispatchers; whether the order allocation configuration item data satisfies the order distributor includes: checking whether the order type is matched with the order type or the preference type delivered by a delivery person, checking whether the order position is within the delivery range of the delivery person, and checking whether the destination to be delivered by the order is in a destination list delivered by the order delivery person;
the delivery recommendation value calculation module is used for calculating the delivery recommendation values of the candidate order distributors if the number of the candidate order distributors is greater than a preset threshold value; the delivery recommendation value is determined according to influence factors influencing user experience and delivery efficiency in the order delivery process; the impact factors include at least one of: predicting pick-up time, predicted delivery time, credit score or order receiving rate;
the order distribution information pushing module is used for determining a target order distributor according to the distribution recommended value sequence and pushing order distribution information to the target order distributor; the order distribution information only comprises partial information of the real-time order information;
the order grabbing module is used for starting an order grabbing mode to carry out order grabbing and delivery on the real-time order if the number of the candidate order distributors does not reach a preset threshold value or the order distribution information is rejected after being successfully pushed; wherein, the implementation of the order grabbing and distribution to the real-time order comprises the following steps: and if the order distributor robs the order within the preset interval time, screening the order distributor meeting the conditions according to the credit score of the order distributor so as to push order distribution information.
7. The apparatus of claim 6, wherein the delivery recommendation calculation module comprises:
the distribution recommendation value influence factor determining unit is used for determining the influence factor of the distribution recommendation value of the candidate order distributor and the weight proportion of the influence factor;
and the delivery recommendation value calculating unit is used for determining the delivery recommendation value of the candidate order deliverer according to the influence factor and the weight proportion.
8. The apparatus of claim 7, wherein the delivery recommendation calculation unit comprises:
and the distribution recommended value weighting and calculating subunit is used for calculating the distribution recommended values of the candidate order distributors according to the weighted sum between the influence factors and the weight proportion.
9. The apparatus of claim 6, wherein the order allocation information pushing module comprises:
the candidate order distributor sorting unit is used for carrying out priority sorting on the candidate order distributors according to the distribution recommended values;
the candidate order distributor determining unit is used for selecting a candidate order distributor with a high priority as a target order distributor according to the priority sequence;
correspondingly, the order distribution information pushing module further includes:
and the order distribution information pushing unit is used for judging the order receiving state of the target order distributor, and pushing the order distribution information to the target order distributor if the target order distributor starts the order receiving and is in an idle state.
10. The apparatus of claim 9, further comprising:
and the order distribution information cyclic pushing module is used for continuously pushing order distribution information to other candidate order distributors except the target order distributor, which meet the preset conditions, until the order distribution information is pushed successfully if the target order distributor does not start order taking and/or is not in an idle state.
11. A computer device, characterized in that the computer device comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the order allocation method of any of claims 1-5.
12. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the order allocation method according to any one of claims 1-5.
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