CN113657879A - Resource scheduling method and device - Google Patents
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Abstract
One or more embodiments of the present specification provide a method and apparatus for resource scheduling. The method comprises the following steps: responding to a resource scheduling request of a user, and determining the initial priority of each resource scheduling channel; acquiring a priority adjustment strategy of each resource scheduling channel, wherein the priority adjustment strategy is determined based on an optimization model, and the maximum success rate of resource scheduling is a target under the condition that the optimization model meets a preset constraint condition; determining the comprehensive priority of each resource scheduling channel based on the initial priority and a priority adjustment strategy; sequencing the resource scheduling channels based on the comprehensive priority, and displaying the sequencing result in a visual interface; and responding to a call request of a user for the target resource scheduling channel, and executing resource scheduling based on the target resource scheduling channel.
Description
Technical Field
One or more embodiments of the present disclosure relate to the field of computer technologies, and in particular, to a method and an apparatus for resource scheduling.
Background
The resource scheduling is the resource circulation between the resource scheduling initiator and the resource scheduling receiver, and the resource can be electronic currency equivalent to the actual currency or virtual resource such as game assets and mobile phone traffic. Generally, the resource scheduling is completed based on a resource scheduling channel, and a resource scheduling initiator initiates a call request for a target resource scheduling channel to complete resource scheduling between the resource scheduling initiator and a resource scheduling receiver based on the target resource scheduling channel.
Disclosure of Invention
In view of this, one or more embodiments of the present disclosure provide a method and apparatus for resource scheduling.
In order to achieve the above purpose, one or more embodiments of the present disclosure provide the following technical solutions:
according to a first aspect of one or more embodiments of the present specification, there is provided a method for resource scheduling, including:
responding to a resource scheduling request of a user, and determining the initial priority of each resource scheduling channel;
acquiring a priority adjustment strategy of each resource scheduling channel, wherein the priority adjustment strategy is determined based on an optimization model, and the maximum success rate of resource scheduling is a target under the condition that the optimization model meets a preset constraint condition;
for each resource scheduling channel, determining the comprehensive priority of the resource scheduling channel based on the initial priority and the priority adjustment strategy;
sequencing the resource scheduling channels based on the comprehensive priority, and displaying the sequencing result in a visual interface;
and responding to a call request of a user for a target resource scheduling channel, and executing resource scheduling based on the target resource scheduling channel.
According to a second aspect of one or more embodiments of the present specification, there is provided an apparatus for resource scheduling, including an initial priority determining unit, a priority policy obtaining unit, a comprehensive priority determining unit, a ranking recommending unit, and a resource scheduling unit:
the initial priority determining unit is used for responding to the resource scheduling request of the user and determining the initial priority of each resource scheduling channel;
the priority strategy acquisition unit is used for acquiring a priority adjustment strategy of each resource scheduling channel, wherein the priority adjustment strategy is determined based on a tuning model, and the maximum success rate of resource scheduling is a target under the condition that the tuning model meets a preset constraint condition;
the comprehensive priority determining unit is used for determining the comprehensive priority of the resource scheduling channels according to the initial priority and the priority adjusting strategy aiming at each resource scheduling channel;
the sequencing recommendation unit sequences the resource scheduling channels based on the comprehensive priority and displays the sequencing result in a visual interface;
and the resource scheduling unit responds to a call request of a user for a target resource scheduling channel and executes resource scheduling based on the target resource scheduling channel.
According to a third aspect of one or more embodiments of the present specification, there is provided an electronic apparatus including: a processor and a memory for storing processor-executable instructions;
wherein the processor implements the steps of the method of the first aspect by executing the executable instructions.
According to a fourth aspect of one or more embodiments of the present description, a computer-readable storage medium is proposed, on which computer instructions are stored, which computer instructions, when executed by a processor, implement the steps of the method of the first aspect described above.
As can be seen from the above description, in this specification, after a user initiates a resource scheduling request, in response to the request, first determining an initial priority of each resource scheduling channel, then obtaining a priority adjustment policy of each resource scheduling channel that has been determined by an optimization model, determining a comprehensive priority of all resource scheduling channels in combination with the initial priority and the priority adjustment policy, and then recommending each resource scheduling channel ranked based on the comprehensive priority to the user in a visual manner, and in response to a call request of the user for a target resource scheduling channel, completing resource scheduling based on the target resource scheduling channel. In the scheme, the priority adjustment strategy of each resource scheduling channel is determined in advance by the optimization model based on the preset constraint condition under the goal of the maximum resource scheduling success rate, the initial priority of each resource scheduling channel is adjusted by combining the priority adjustment strategy determined by the optimization model, and the comprehensive priority obtained after adjustment is used for sequencing and recommending, so that the recommended resource scheduling channel can take the resource scheduling success rate and the preset constraint into account, the method is more accurate and effective, the success rate of resource scheduling is improved, and the use experience of a user is also improved.
Drawings
Fig. 1 is a flowchart of a method for scheduling resources according to an exemplary embodiment.
FIG. 2 is a flow diagram illustrating a method for determining an initial priority of a resource scheduling channel in an exemplary embodiment.
FIG. 3 is a flowchart illustrating a method for determining a priority adjustment policy for each resource scheduling channel using an optimization model in an exemplary embodiment.
Fig. 4 is a schematic structural diagram of an electronic device in which an apparatus for resource scheduling is located according to an exemplary embodiment.
Fig. 5 is a block diagram of an apparatus for resource scheduling according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with one or more embodiments of the present specification. Rather, they are merely examples of apparatus and methods consistent with certain aspects of one or more embodiments of the specification, as detailed in the claims which follow.
It should be noted that: in other embodiments, the steps of the corresponding methods are not necessarily performed in the order shown and described herein. In some other embodiments, the method may include more or fewer steps than those described herein. Moreover, a single step described in this specification may be broken down into multiple steps for description in other embodiments; multiple steps described in this specification may be combined into a single step in other embodiments.
The present specification provides a resource scheduling scheme.
The resources in this specification may include: electronic money, game assets, cell phone traffic, etc. resources that can be circulated between multiple parties.
Resource scheduling is typically the circulation of resources between several owners. For example, a resource scheduling initiator may initiate a resource scheduling request to transfer a specified resource flow to a resource recipient.
For example, the resource schedule may be a transfer of funds between the user and the merchant, or a transfer of game assets between two game players.
The resource scheduling channel is generally a channel for realizing resource circulation. Generally, there may be multiple resource scheduling channels for implementing the same resource flow. After receiving a resource scheduling request initiated by a resource scheduling initiator, a plurality of available resource calling channels can be displayed to the resource initiator, and then resource scheduling is executed for the resource initiator based on the resource calling channel selected by the resource initiator.
For example, taking the example that the resource scheduling request is a payment request, after the user initiates the payment request, several payment channels, such as different banks or payment institutions, may be shown to the user, and then the payment operation may be performed based on the payment channel selected by the user.
In the process of displaying the resource calling channels, if there are a plurality of available resource calling channels, the resource calling channels are usually displayed after being sorted. The sequencing and displaying accuracy of the resource calling channels can influence the probability of successful completion of resource scheduling, the use experience of a user in resource scheduling and the like.
The present specification proposes a resource scheduling method, which can be applied to a resource scheduling platform, where the resource scheduling platform can be deployed by a resource scheduling service provider, and can provide a resource scheduling service such as a recommended resource scheduling channel, and its physical carrier is usually a server or a server cluster.
For example, when the resource is electronic money, the resource scheduling platform may be a payment platform, and the resource scheduling channel is a payment channel, and may include various large banks and payment institutions. When the resource is the mobile phone traffic, the resource scheduling platform may be deployed by a certain operator, and the resource scheduling channel may include each large operator.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for scheduling resources according to an exemplary embodiment.
The method for scheduling resources can comprise the following specific steps:
and 102, responding to the resource scheduling request of the user, and determining the initial priority of each resource scheduling channel.
In this embodiment, after receiving a resource scheduling request of a user, a resource scheduling platform may first determine an initial priority of each resource scheduling channel, where the initial priority is an initial prediction of the priority of each resource scheduling channel.
Specifically, in a more convenient implementation manner, the resource scheduling platform may obtain the preset initial priority of each resource scheduling channel, that is, the initial priority of each resource scheduling channel may be the same for different resource scheduling.
In a more accurate implementation manner, the resource scheduling platform may determine the initial priority of each resource scheduling channel in the current resource scheduling by using a trained initial priority prediction model and combining specific parameters of the current resource scheduling, that is, the initial priority of each resource scheduling channel may be different for different times of resource scheduling.
In one example, the resource is electronic money, the resource scheduling request is a payment request, and the resource scheduling channel is a payment channel for interfacing different banks and payment institutions; after receiving the payment request, the payment platform can acquire specific parameters of the payment amount, currency and the like of the payment, and determines the initial priority of each payment channel in the payment by adopting a trained initial priority prediction model.
The initial priority prediction model can be a classification model, the resource scheduling platform can adopt the trained initial priority prediction model to predict the confidence coefficient of successful payment of the current payment on each payment channel as the initial priority, and the training process of the model can be completed in a supervision mode by using multiple historical payment records of successful payment and unsuccessful payment on each payment channel.
The initial priority of each resource scheduling channel may be the initial priority of all resource scheduling channels that the resource scheduling platform can provide, or the initial priority of a part of resource scheduling channels in all resource scheduling channels that the resource scheduling platform can provide.
Referring to fig. 2, in an alternative implementation, step 102 may include:
The resource scheduling types may be distinguished based on one or more of a service scenario of resource scheduling, a resource type of the scheduled resource, characteristics of a resource scheduling initiator and a resource scheduling receiver.
The resource scheduling platform is used for presetting a mapping relation between a resource scheduling type and a resource scheduling channel, searching the mapping relation after determining the resource scheduling type corresponding to the current resource scheduling, and determining the resource scheduling channel supporting the resource scheduling type, wherein the resource scheduling platform is used for determining the initial priority of each resource scheduling channel supporting the current resource scheduling corresponding type, and the initial priority of each resource scheduling channel not supporting the type is not required to be determined.
For example, taking the payment channel as an example, the payment platform may determine a specific part of the payment channels from the plurality of payment channels that can be provided by the payment platform according to the type of the commodity paid this time, and if the commodity type is overseas commodity, the payment platform may determine the initial priority of each payment channel that supports foreign currency exchange and payment accordingly, and does not determine the initial priority of each payment channel that does not support foreign currency exchange and payment.
It can be understood that the resource scheduling platform may also determine the initial priority of each resource scheduling channel that meets the user-defined setting based on the user-defined setting of the resource scheduling initiator and the resource scheduling receiver. Taking the payment channel as an example, if the merchant denies the credit card payment in the custom setting, the transaction platform may determine the initial priority of each payment channel for non-credit card payment accordingly.
In the implementation mode, the resource scheduling platform can pertinently determine the initial priorities of part of the resource scheduling channels instead of determining the initial priorities of all the resource scheduling channels, so that the processing capacity of the equipment can be reduced, and the working efficiency of the equipment can be improved.
And 104, acquiring a priority adjustment strategy of each resource scheduling channel, wherein the priority adjustment strategy is determined based on an adjustment model, and the maximum success rate of resource scheduling is the target under the condition that the adjustment model meets preset constraint conditions.
In this embodiment, the initial priority of each resource scheduling channel is only the initial prediction of the resource scheduling platform on the priority of each resource scheduling channel, and in order to further comprehensively consider each resource scheduling channel to provide a more accurate and effective channel for a user, after determining the initial priority of each resource scheduling channel, the resource scheduling platform further obtains a priority adjustment policy of each resource scheduling channel to adjust the initial priority of each resource scheduling channel.
When the initial priority is a numerical priority score, the priority adjustment policy may be a distribution weight under a preset distribution formula, and the initial priority may be adjusted based on the distribution formula and the distribution weight. In addition, the priority adjustment strategies of different resource scheduling channels can be different.
In this embodiment, the resource scheduling platform obtains the priority adjustment policy of each resource scheduling channel determined by the tuning model, and the tuning model determines the priority policy of each resource scheduling channel by using data in the multiple historical resource scheduling records with the maximum resource scheduling success rate as a target under the limitation of a preset constraint condition. Specifically, the tuning model solves the priority adjustment strategy of each resource scheduling channel under the limit of a preset constraint condition and with the maximum overall success rate of multiple times of historical resource scheduling as an objective.
The preset constraint condition may be set according to actual requirements, including but not limited to a constraint condition for resource scheduling cost and channel proportion.
Resource scheduling consumption corresponding to the resource scheduling channels exists when one-time resource scheduling is carried out on any resource scheduling channel, and the resource scheduling consumption corresponding to different resource scheduling channels can be different. In order to keep the resource scheduling consumption for resource scheduling within a controllable range, a resource scheduling consumption constraint condition can be set; the resource scheduling consumption constraint condition may be a constraint condition set for the total consumption of resource scheduling on all resource scheduling channels under multiple resource scheduling.
The traffic proportion of the resource scheduling in each resource scheduling channel, including the ratio of the number of times of resource scheduling in each resource scheduling channel to the total number of times, may not be balanced with each other. In order to make the flow proportion of resource scheduling on each resource scheduling channel more reasonable, channel proportion constraint conditions can be set; the channel proportion constraint condition may be a constraint condition set for a traffic proportion of resource scheduling performed on each resource scheduling channel.
Taking a payment channel as an example, the resource scheduling consumption can be payment handling fee, and the resource scheduling consumption constraint condition can be set as that the total payment handling fee of all payment channels under multiple times of payment does not exceed the preset consumption proportion of the total payment amount; the channel proportion constraint condition may be set such that the number of payments made in each payment channel does not exceed a corresponding preset number proportion of total number of payments.
Constraint conditions are preset in the tuning model, so that the solved priority adjustment strategy further considers factors such as resource scheduling consumption and channel proportion on the basis of the maximization of the success rate, and is more accurate and effective.
It should be noted that the tuning model may be run on the resource scheduling platform itself, or may also be run on other electronic devices that are not the resource scheduling platform, for example, the tuning model may be run in a cloud computing node with higher computing power, and the resource scheduling platform may request, from the cloud computing node, the priority adjustment policy of each resource scheduling channel that is determined by the tuning model, and store the priority adjustment policy in the resource scheduling channel in the resource scheduling platform, so as to be read when channel recommendation is performed each time, so that the resource scheduling platform can efficiently concentrate on its resource scheduling task.
In an alternative implementation manner, the tuning model may periodically determine the priority tuning strategy of each resource scheduling channel. Specifically, the tuning model may obtain a historical resource scheduling record in a preset time period when an update period is reached, and re-determine the priority adjustment strategy of each resource scheduling channel by using the historical resource scheduling record obtained in the period under a preset constraint condition with the maximum resource scheduling success rate as a target. The preset time period may be the last period, that is, the historical resource scheduling record generated in the last period is obtained.
It is understood that the tuning model may also re-determine the priority adjustment strategy after a parameter such as a constraint condition is changed.
After the priority adjustment strategy is re-determined, the resource scheduling platform can update the failed original priority adjustment strategy by using the re-determined priority adjustment strategy, so that the resource scheduling platform can always obtain the latest determined initial priority of each resource scheduling channel when obtaining the initial priority of each resource scheduling channel. When the tuning model runs on other devices of the non-resource scheduling platform, the resource scheduling platform may receive the notification of the other devices to obtain and update the priority adjustment policy, and the resource scheduling platform may also periodically obtain the priority adjustment policy determined by the tuning model for the period from the other devices to update the priority adjustment policy.
And 106, determining the comprehensive priority of each resource scheduling channel based on the initial priority and the priority adjustment strategy.
Based on the steps, the resource scheduling platform acquires the initial priority and the priority adjustment strategy of each resource scheduling channel, and aiming at each resource scheduling channel, the resource scheduling platform can adjust the initial priority based on the corresponding priority adjustment strategy to obtain the comprehensive priority of the resource scheduling channel. When the initial priority is the initial priority score, the priority adjustment strategy is the allocation weight, and for each resource scheduling channel, the resource scheduling platform can substitute the initial priority score and the allocation weight into an allocation formula to obtain the comprehensive priority of the resource scheduling channel, namely the comprehensive priority score after the initial priority score is allocated.
And 108, sequencing the resource scheduling channels based on the comprehensive priority, and displaying a sequencing result in a visual interface to realize recommendation of the resource scheduling channels.
After the comprehensive priority of all the resource scheduling channels is obtained, the resource scheduling platform sequences the comprehensive priority based on all the resource scheduling channels, and taking the comprehensive priority score as an example, the resource scheduling platform can sequence all the resource scheduling channels according to the numerical value of the comprehensive priority score. And after the sequencing result of the resource scheduling channel is obtained, the resource scheduling platform displays the sequencing result in a visual mode.
For example, a client program of the resource scheduling platform may be installed on the user equipment, the resource scheduling channel ranking result returned by the resource scheduling platform may be displayed in a list form in a visual interface of the client program, and the resource scheduling channel with the higher comprehensive priority is located at the front of the resource scheduling channel in the list, and the resource scheduling channel with the lower comprehensive priority is located at the back of the resource scheduling channel in the list, so that recommendation of the resource scheduling channel to the user is achieved.
After obtaining the sequencing result of each resource scheduling channel with recommendation displayed in a visual manner, a user needs to select a target resource scheduling channel from each resource scheduling channel and execute a calling operation aiming at the target resource scheduling channel. It should be noted that although the sorting result has a recommendation meaning, the specific selection of the target resource scheduling channel by the user is not limited, and the user may select the resource scheduling channel with the top sorting but may select the resource scheduling channel with the back sorting result.
And the resource scheduling platform responds to a call request of a user for a target resource scheduling channel, executes resource scheduling based on the target resource scheduling channel, and returns an execution result of the resource scheduling to the user. Taking a payment channel as an example, in response to a call request of a user for a target payment channel, a payment platform determines a target bank or a third-party payment mechanism connected with the target payment channel in a butt joint manner, and sends a related request of the commodity transaction payment information to the target bank or the third-party payment mechanism, so that the target bank or the third-party payment mechanism completes fund transfer between the user and the payment platform and/or between the user and a merchant.
As can be seen from the above description, in this specification, after a user initiates a resource scheduling request, in response to the request, first determining an initial priority of each resource scheduling channel, then obtaining a priority adjustment policy of each resource scheduling channel that has been determined by an optimization model, determining a comprehensive priority of all resource scheduling channels in combination with the initial priority and the priority adjustment policy, and then recommending each resource scheduling channel ranked based on the comprehensive priority to the user in a visual manner, and in response to a call request of the user for a target resource scheduling channel, completing resource scheduling based on the target resource scheduling channel.
In the scheme, the priority adjustment strategy of each resource scheduling channel is determined in advance by the optimization model based on the preset constraint condition under the goal of the maximum resource scheduling success rate, the initial priority of each resource scheduling channel is adjusted by combining the priority adjustment strategy determined by the optimization model, and the comprehensive priority obtained after adjustment is used for sequencing and recommending, so that the recommended resource scheduling channel can take the resource scheduling success rate and the preset constraint into account, the method is more accurate and effective, the success rate of resource scheduling is improved, and the use experience of a user is also improved.
In order to make those skilled in the art better understand the above technical solution, the following description is made with reference to an alternative implementation manner for the process of determining the priority adjustment policy of each resource scheduling channel by the tuning model in step 104.
An initial resource scheduling success rate function is preset in the tuning model, the initial resource scheduling success rate function takes a priority adjustment strategy as an independent variable, and takes an initial priority as a fixed parameter.
Marking an initial priority by p, in j (j is 1 and 2.) resource scheduling of multiple times of resource scheduling, the initial priority of a resource scheduling channel i (i is 1 and 2.) is pji(ii) a Identifying a priority adjustment strategy by x, wherein the priority adjustment strategy of a resource scheduling channel i (i is 1 and 2.) is xi(i 1, 2.). The initial resource scheduling success rate function for multiple resource scheduling may be identified as f (x)i；pji)(i＝1、2...，j＝1、2...)。
In addition, constraint conditions are also preset in the tuning model, and the constraint conditions comprise resource scheduling consumption constraint conditions, channel proportion constraint conditions and the like.
The resource scheduling consumption constraint condition may be a constraint condition set for the total consumption of resource scheduling on all resource scheduling channels under multiple resource scheduling.
Identifying resource scheduling consumption of primary resource scheduling through the resource scheduling channel by using c, and performing the consumption of the primary resource scheduling through the resource scheduling channel i (i is 1 and 2), namely ci(i＝1. 2.. to.). The resource scheduling cost constraint may be identified as C (x)i；pji；ci) (i 1, 2, j 1, 2), wherein the resource scheduling consumes ciIs used as the reference.
The channel proportion constraint condition may be a constraint condition set for a traffic proportion of resource scheduling performed on each resource scheduling channel.
The channel proportion constraint condition is marked by R, and the constraint condition R can be respectively set corresponding to different resource scheduling channels i (i is 1 and 2.)i(xi；pji)(i＝1、2...，j＝1、2...)。
When the priority adjustment strategy of each resource scheduling channel is determined, historical resource scheduling records in a preset historical time period are obtained, wherein the historical resource scheduling records comprise the initial priority of each resource scheduling channel in each historical resource scheduling. For example, if the preset historical period is the last week, a record of all historical resource schedules in the previous week may be obtained, where the record includes the initial priority of each resource scheduling channel in each historical resource schedule in the previous week.
And inputting the acquired initial priority of each resource scheduling channel in each historical resource scheduling in the historical time period as an input parameter into the tuning model, and determining the priority adjustment strategy of each resource scheduling channel by taking the maximum success rate function of the initial resource scheduling as a target.
Specifically, after obtaining the historical resource scheduling record, a parameter p of the initial resource scheduling success rate function in the tuning model may be determinedjiAfter the initial resource scheduling success rate function f (x) is input into the tuning model as an input parameter, the initial resource scheduling success rate function f (x) can be determinedi；pji) Constraint C (x)i；pji；ci) And the constraint Ri(xi；pji) (i 1, 2., j 1, 2.), wherein the fixed ginseng ciA preset value is used.
After determining the objective function and constraints, the tuning model may be optimized using algorithms such as genetic algorithms and simulated annealing algorithmsAlgorithm under said constraints C and RiThen, a priority adjustment strategy x capable of maximizing the initial resource scheduling success rate f is solvedi。
Taking simulated annealing algorithm as an example, the tuning model can randomly generate initial solution x'iDetermining the initial solution x'iWhether preset constraint condition C (x ') can be met'i；pji；ci) And Ri(x′i；pji) And in the case that the constraint condition is not met, randomly generating the initial solution x 'again'iUntil it can satisfy the constraint condition C (x'i；pji；ci) And Ri(x′i；pji) Based on the finally determined initial solution x'iDetermining an initial resource scheduling success rate function f (x'i；pji)。
At the final determined initial solution x'iOn the basis of which the disturbance generates a new solution xiDetermining the new solution xiWhether or not the constraint condition C (x) can be satisfiedi；pji；ci) And Ri(xi；pji) Re-perturbation produces a new solution x 'if the constraint is not satisfied'iUntil it can satisfy the constraint condition C (x)i；pji；ci) And Ri(xi；pji) Based on the new solution x determined this timeiDetermining an initial resource scheduling success rate function f (x)i；pji)。
Determining the initial resource scheduling success rate function f (x)i；pji) Whether or not is greater than f (x'i；pji) At f (x)i；pji) Is greater than f (x'i；pji) In case of accepting the new solution xi(ii) a At f (x)i；pji) Is less than or equal to f (x'i；pji) Determining whether to accept the new solution x based on Metropolis criteriai。
Finishing the iteration, determining whether the current iteration times reach the preset iteration times, if the current iteration times do not reach the preset iteration times, and if the current iteration receives a new solution, disturbing to generate a next new solution on the basis of the new solution received by the current iteration, and repeating the steps; and if the iteration rejects the new solution, disturbing to generate a next new solution on the basis of the original solution reserved in the iteration, and repeating the steps.
And under the condition that the current iteration times reach the preset iteration times, determining whether the currently accepted optimal solution reaches a preset termination condition, under the condition that the currently accepted optimal solution cannot reach the preset termination condition, reducing disturbance, resetting the iteration times, continuing to disturb to generate a new solution, and repeating the steps.
And under the condition that the currently accepted optimal solution can reach a preset termination condition, terminating the operation, and outputting the currently accepted optimal solution, namely the finally determined priority adjustment strategy of each resource scheduling channel.
It should be noted that the initial resource scheduling success rate function and the constraint condition are only used as examples, and specific setting manners of the resource scheduling success rate function and the constraint condition and specific algorithms adopted when solving the priority adjustment policy are not limited in this specification.
In another alternative implementation, when the priority adjustment strategy of each resource scheduling channel is determined by adopting an optimization model, the method can be further improved by combining a lagrangian dual algorithm.
In the tuning model, a Lagrange dual algorithm is adopted, and based on a preset constraint condition, an initial resource scheduling success rate function is converted into a target resource scheduling success rate function without the constraint condition; and the independent variables in the initial resource scheduling success rate function and the target resource scheduling success rate function are priority adjustment strategies.
Based on the foregoing, a success rate function f (x) is scheduled for the initial resourcei；pji) Constraint C (x)i；pji；ci) And the constraint Ri(xi；pji) (i 1, 2, j 1, 2), the initial resource scheduling success rate function f (x) may be obtained by using a lagrange dual algorithmi；pji) Converting into a target resource scheduling success rate function F (x)i；pji) The target resource scheduling success rate function F is no longer subject to the above constraints C and RiFor the specific transformation method, reference may be made to the principle related to lagrangian duality, which is not described herein again.
Referring to fig. 3, the process of determining the priority adjustment policy of each resource scheduling channel may include the following steps:
And 304, inputting the initial priority of each resource scheduling channel as an input parameter into the tuning model, and determining a priority adjustment strategy of each resource scheduling channel according to the maximum target of the target resource scheduling success rate function.
Referring to the foregoing, obtaining historical resource scheduling records and determining a parameter p of a target resource scheduling success rate function in a tuning modeljiAfter the target resource scheduling success rate function F (x) is input into the tuning model as an input parameter, the target resource scheduling success rate function F (x) can be determinedi；pji)。
The target resource scheduling success rate function F (x)i；pji) Without constraint conditions, the tuning model can adopt optimization algorithms such as genetic algorithm and simulated annealing algorithm, is not limited by the constraint conditions, and solves the priority tuning strategy x which can enable the target resource scheduling success rate F to be maximumi. Specifically, taking the simulated annealing algorithm described above as an example, no new solution x needs to be determined in each stepiWhether or not a preset constraint condition C (x) is satisfiedi；pji；ci) And Ri(xi；pji) And other procedures are unchanged.
In the implementation mode, based on a Lagrange dual algorithm, the initial resource scheduling success rate function with the constraint condition is converted into the target resource scheduling success rate function without the constraint condition, and when the priority adjustment strategy of each resource scheduling channel is determined in an iterative mode, the limitation of the constraint condition is not required to be considered, so that the calculation amount is reduced, and the efficiency of determining the priority adjustment strategy is improved.
As can be seen from the above description, in this specification, after a user initiates a resource scheduling request, in response to the request, first determining an initial priority of each resource scheduling channel, then obtaining a priority adjustment policy of each resource scheduling channel that has been determined by an optimization model, determining a comprehensive priority of all resource scheduling channels in combination with the initial priority and the priority adjustment policy, and then recommending each resource scheduling channel ranked based on the comprehensive priority to the user in a visual manner, and in response to a call request of the user for a target resource scheduling channel, completing resource scheduling based on the target resource scheduling channel.
In the scheme, the priority adjustment strategy of each resource scheduling channel is determined in advance by the optimization model based on the preset constraint condition under the goal of the maximum resource scheduling success rate, the initial priority of each resource scheduling channel is adjusted by combining the priority adjustment strategy determined by the optimization model, and the comprehensive priority obtained after adjustment is used for sequencing and recommending, so that the recommended resource scheduling channel can take the resource scheduling success rate and the preset constraint into account, the method is more accurate and effective, the success rate of resource scheduling is improved, and the use experience of a user is also improved.
Fig. 4 is a schematic structural diagram of an electronic device in which an apparatus for resource scheduling is provided according to an exemplary embodiment. Referring to fig. 4, at the hardware level, the apparatus includes a processor 402, an internal bus 404, a network interface 406, a memory 408, and a non-volatile memory 410, but may also include hardware required for other services. One or more embodiments of the present description may be implemented in software, such as by processor 402 reading corresponding computer programs from non-volatile storage 410 into memory 408 and then executing. Of course, besides software implementation, the one or more embodiments in this specification do not exclude other implementations, such as logic devices or combinations of software and hardware, and so on, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or logic devices.
Referring to fig. 5, the apparatus for resource scheduling may be applied to the device shown in fig. 4 to implement the technical solution of the present specification. The resource scheduling apparatus may include an initial priority determining unit 510, a priority policy obtaining unit 520, a comprehensive priority determining unit 530, a ranking recommending unit 540, and a resource scheduling unit 550:
the initial priority determining unit 510, in response to a resource scheduling request of a user, determines an initial priority of each resource scheduling channel;
the priority policy obtaining unit 520 obtains a priority adjustment policy of each resource scheduling channel, where the priority adjustment policy is determined based on a tuning model, and the tuning model has a maximum resource scheduling success rate as a target when meeting a preset constraint condition;
the integrated priority determining unit 530, for each resource scheduling channel, determines an integrated priority of the resource scheduling channel based on the initial priority and the priority adjustment policy;
the sorting recommendation unit 540 sorts the resource scheduling channels based on the comprehensive priority, and displays the sorting result in a visual interface;
the resource scheduling unit 550, in response to a call request of a user for a target resource scheduling channel, performs resource scheduling based on the target resource scheduling channel.
Optionally, an initial resource scheduling success rate function is preset in the tuning model;
the tuning model adopts a Lagrange dual algorithm, and converts the initial resource scheduling success rate function into a target resource scheduling success rate function without constraint conditions based on the preset constraint conditions; the independent variables in the initial resource scheduling success rate function and the target resource scheduling success rate function are the priority adjustment strategies;
the process of determining the priority adjustment strategy of each resource scheduling channel based on the optimization model comprises the following steps:
acquiring historical resource scheduling records in a preset historical time period, wherein the historical resource scheduling records comprise the initial priority of each resource scheduling channel in each historical resource scheduling;
and inputting the initial priority of each resource scheduling channel as an input parameter into the tuning model, and determining the priority adjustment strategy of each resource scheduling channel by taking the maximum target of the target resource scheduling success rate function as a target.
Optionally, the preset constraint condition includes a resource scheduling consumption constraint condition and a channel proportion constraint condition.
Optionally, the apparatus further comprises:
the priority policy updating unit 560 periodically updates the priority adjustment policy of each resource scheduling channel.
Optionally, the apparatus further comprises:
a resource scheduling type determining unit 570, configured to determine a resource scheduling type corresponding to the current resource scheduling in response to a resource scheduling request of a user;
the initial priority determining unit 510 determines the initial priority of each resource scheduling channel supporting the resource scheduling type when determining the initial priority of each resource scheduling channel.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is a computer, which may take the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email messaging device, game console, tablet computer, wearable device, or a combination of any of these devices.
In a typical configuration, a computer includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic disk storage, quantum memory, graphene-based storage media or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. The use of the phrase "including a" does not exclude the presence of other, identical elements in the process, method, article, or apparatus that comprises the same element, whether or not the same element is present in all of the same element.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The terminology used in the description of the one or more embodiments is for the purpose of describing the particular embodiments only and is not intended to be limiting of the description of the one or more embodiments. As used in one or more embodiments of the present specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used in one or more embodiments of the present description to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of one or more embodiments herein. The word "if," as used herein, may be interpreted as "when or" responsive to a determination, "depending on the context.
The above description is only for the purpose of illustrating the preferred embodiments of the one or more embodiments of the present disclosure, and is not intended to limit the scope of the one or more embodiments of the present disclosure, and any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the one or more embodiments of the present disclosure should be included in the scope of the one or more embodiments of the present disclosure.
Claims (10)
1. A method of resource scheduling, the method comprising:
responding to a resource scheduling request of a user, and determining the initial priority of each resource scheduling channel;
acquiring a priority adjustment strategy of each resource scheduling channel, wherein the priority adjustment strategy is determined based on an optimization model, and the maximum success rate of resource scheduling is a target under the condition that the optimization model meets a preset constraint condition;
for each resource scheduling channel, determining the comprehensive priority of the resource scheduling channel based on the initial priority and the priority adjustment strategy;
sequencing the resource scheduling channels based on the comprehensive priority, and displaying the sequencing result in a visual interface;
and responding to a call request of a user for a target resource scheduling channel, and executing resource scheduling based on the target resource scheduling channel.
2. The method of claim 1, wherein an initial resource scheduling success rate function is preset in the tuning model;
the tuning model adopts a Lagrange dual algorithm, and converts the initial resource scheduling success rate function into a target resource scheduling success rate function without constraint conditions based on the preset constraint conditions; the independent variables in the initial resource scheduling success rate function and the target resource scheduling success rate function are the priority adjustment strategies;
the process of determining the priority adjustment strategy of each resource scheduling channel based on the optimization model comprises the following steps:
acquiring historical resource scheduling records in a preset historical time period, wherein the historical resource scheduling records comprise the initial priority of each resource scheduling channel in each historical resource scheduling;
and inputting the initial priority of each resource scheduling channel as an input parameter into the tuning model, and determining the priority adjustment strategy of each resource scheduling channel by taking the maximum target of the target resource scheduling success rate function as a target.
3. The method of claim 1, the preset constraints comprising resource scheduling cost constraints and channel proportion constraints.
4. The method of claim 1, further comprising:
and periodically updating the priority adjustment strategy of each resource scheduling channel.
5. The method of claim 1, further comprising:
responding to a resource scheduling request of a user, and determining a resource scheduling type corresponding to the current resource scheduling;
the determining the initial priority of each resource scheduling channel comprises the following steps:
and determining the initial priority of each resource scheduling channel supporting the resource scheduling type.
6. A device for scheduling resources comprises an initial priority determining unit, a priority strategy acquiring unit, a comprehensive priority determining unit, a sequencing recommending unit and a resource scheduling unit:
the initial priority determining unit is used for responding to the resource scheduling request of the user and determining the initial priority of each resource scheduling channel;
the priority strategy acquisition unit is used for acquiring a priority adjustment strategy of each resource scheduling channel, wherein the priority adjustment strategy is determined based on a tuning model, and the maximum success rate of resource scheduling is a target under the condition that the tuning model meets a preset constraint condition;
the comprehensive priority determining unit is used for determining the comprehensive priority of the resource scheduling channels according to the initial priority and the priority adjusting strategy aiming at each resource scheduling channel;
the sequencing recommendation unit sequences the resource scheduling channels based on the comprehensive priority and displays the sequencing result in a visual interface;
and the resource scheduling unit responds to a call request of a user for a target resource scheduling channel and executes resource scheduling based on the target resource scheduling channel.
7. The apparatus of claim 6, wherein an initial resource scheduling success rate function is preset in the tuning model;
the tuning model adopts a Lagrange dual algorithm, and converts the initial resource scheduling success rate function into a target resource scheduling success rate function without constraint conditions based on the preset constraint conditions; the independent variables in the initial resource scheduling success rate function and the target resource scheduling success rate function are the priority adjustment strategies;
the process of determining the priority adjustment strategy of each resource scheduling channel based on the optimization model comprises the following steps:
acquiring historical resource scheduling records in a preset historical time period, wherein the historical resource scheduling records comprise the initial priority of each resource scheduling channel in each historical resource scheduling;
and inputting the initial priority of each resource scheduling channel as an input parameter into the tuning model, and determining the priority adjustment strategy of each resource scheduling channel by taking the maximum target of the target resource scheduling success rate function as a target.
8. The apparatus of claim 6, the preset constraints comprising resource scheduling cost constraints and channel proportion constraints.
9. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor implements the steps in the method of any one of claims 1-5 by executing the executable instructions.
10. A computer readable storage medium having stored thereon computer instructions which, when executed by a processor, carry out the steps of the method according to any one of claims 1-5.
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