CN113706240A - Order sorting method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application provides a method and a device for ordering orders, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring a plurality of order information, wherein the order information is information pushed by a target user after triggering a target service; acquiring associated information of a plurality of order information, wherein the associated information is used for describing the order information; processing the associated information by using a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset ranking scheme; and processing the first order sequencing information by using a target algorithm model to obtain target order sequencing information, wherein the target algorithm model is used for sequencing the first order sequencing information to obtain a target sequencing solution. By the method and the device, the problems that orders are unreasonable in sequence and the customer satisfaction degree is low in the related technology are solved.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a method and an apparatus for ordering orders, an electronic device, and a storage medium.
Background
At present, the development of network and hardware technology makes smart phones become the standard for current life and travel. Due to the development of smart phones, software services are developed more and more, and great convenience is brought to life and travel of people, such as take-out services. At present, take-out is very popular, and for restaurants, they receive orders from take-out software and food in the same time period, if the making sequence of the distributed orders is not reasonably distributed, the completion time of a part of orders can be greatly delayed, and the satisfaction degree of customers is reduced; some orders are completed in advance, so that great satisfaction improvement cannot be brought, and the total satisfaction is reduced.
Therefore, the related art has the problems of unreasonable order sorting and low customer satisfaction.
Disclosure of Invention
The application provides an order sorting method and device, a storage medium and electronic equipment, which are used for at least solving the problems of unreasonable order sorting and low customer satisfaction in the related art.
According to an aspect of an embodiment of the present application, there is provided an order ranking method, including: acquiring a plurality of order information, wherein the order information is information pushed by a target user after triggering a target service; acquiring associated information of a plurality of order information, wherein the associated information is used for describing the order information; processing the associated information by using a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset sorting scheme; and processing the first order sorting information by using a target algorithm model to obtain target order sorting information, wherein the target algorithm model is used for sorting the first order sorting information to obtain a target sorting solution.
According to another aspect of the embodiments of the present application, there is also provided an order sorting apparatus, including: the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a plurality of order information, and the order information is information pushed by a target user after a target service is triggered; a second obtaining unit, configured to obtain associated information of the plurality of order information, where the associated information is used to describe the order information; the first processing unit is used for processing the associated information by utilizing a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset ranking scheme; and the second processing unit is used for processing the first order sorting information by using a target algorithm model to obtain target order sorting information, wherein the target algorithm model is used for sorting the first order sorting information to obtain a target sorting solution.
Optionally, the apparatus comprises: the first generating unit is used for generating a sorting constraint condition according to serial and continuous sorting characteristics of the order information before the associated information is processed by using a preset order sorting scheme to obtain first order sorting information; and the second generating unit is used for generating the preset order sorting scheme by using the sorting constraint condition.
Optionally, the association information includes: the order placing time of the order information, the making time of the order, the preset making completion time of the order and the priority of the order, the device further comprises: a third generating unit, configured to generate order making completion time according to order placing time of the order information and making time of the order before processing the first order ranking information by using a target algorithm model to obtain target order ranking information; and the fourth generating unit is used for generating an order optimization target object according to the making completion time of the order, the preset making completion time of the order and the priority of the order.
Optionally, the second processing unit comprises: the first obtaining module is used for optimizing a target object according to the order, utilizing the target algorithm model to carry out sorting processing on the first order sorting information to obtain second order sorting information, and adding one to the total iteration times; a first setting module, configured to use the second order sorting information as the target order sorting information when the total number of iterations corresponding to the second order sorting information is equal to a first preset threshold.
Optionally, the second processing unit comprises: the second obtaining module is used for optimizing a target object according to the order, utilizing the target algorithm model to carry out sorting processing on the first order sorting information to obtain second order sorting information, and adding one to the total iteration times; the comparison module is used for comparing the order sorting information correspondingly generated by each iteration number under the condition that the obtained total iteration number is equal to a first preset threshold value; and the second setting module is used for taking the order sorting information as the target order sorting information under the condition that the matching times among the plurality of order sorting information are equal to a second preset threshold value.
Optionally, the apparatus further comprises: the conversion operation unit is used for performing preset conversion operation on each sub-order information in the first order sorting information to obtain third order sorting information after the associated information is processed by using the preset order sorting scheme to obtain the first order sorting information; and the third processing unit is used for processing the third order sorting information by using the target algorithm model to obtain the target order sorting information.
Optionally, the transform operation unit comprises at least one of: the exchange module is used for acquiring the position information of any two pieces of sub-order information and executing position exchange operation; the inserting module is used for inserting any sub-order information into any position except the position of the current sub-order information; and the reverse order module is used for acquiring any two pieces of sub order information and other sub order information between the two pieces of sub order information and executing reverse order operation on the two pieces of sub order information and the other sub order information.
According to another aspect of the embodiments of the present application, there is also provided an electronic device, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory communicate with each other through the communication bus; wherein the memory is used for storing the computer program; a processor for performing the method steps of order ordering in any of the above embodiments by running the computer program stored on the memory.
According to a further aspect of an embodiment of the present application, there is also provided a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to perform the method steps of order ordering in any of the above embodiments when executed.
The scheme can be applied to the technical field of operation and research optimization to perform heuristic algorithm, in the embodiment of the application, a mode of order sorting is adopted, and a plurality of pieces of order information are obtained, wherein the order information is information pushed by a target user after a target service is triggered; acquiring associated information of a plurality of order information, wherein the associated information is used for describing the order information; processing the associated information by using a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset ranking scheme; and processing the first order sequencing information by using a target algorithm model to obtain target order sequencing information, wherein the target algorithm model is used for sequencing the first order sequencing information to obtain a target sequencing solution. According to the method and the device, the obtained order information is firstly sequenced by using the preset sequencing scheme, and then the sequenced order information is subjected to optimal solution calculation by using the target algorithm model to obtain the final target sequencing information, wherein the target sequencing information is the order sequencing considering the client priority and the client satisfaction, so that guidance is provided for the order sequencing of the restaurant, the overall delay time of the order is shortest, the overall satisfaction of the order is improved, and the problems that the order sequencing is unreasonable and the client satisfaction is low in the related technology are solved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
FIG. 1 is a diagram of a hardware environment for an alternative method of order ordering according to an embodiment of the invention;
FIG. 2 is a flow diagram illustrating an alternative method of order ordering according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a hill climbing algorithm to find an optimal solution;
FIG. 4 is a schematic diagram of a simulated annealing algorithm to find an optimal solution;
FIG. 5 is a block diagram of an alternative order ordering apparatus according to an embodiment of the present application;
fig. 6 is a block diagram of an alternative electronic device according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
At present, take-out is very popular, and for catering restaurants, the catering restaurants receive orders from take-out software and eating in the same time period, and if the order making sequence of the distributed orders is not reasonably distributed, the completion time of a part of orders can be greatly delayed, so that the satisfaction degree of customers is reduced; some orders are completed in advance, so that great satisfaction improvement cannot be brought, and the total satisfaction is reduced. In order to solve the above problem, according to an aspect of the embodiments of the present application, a method for order ranking is provided. Optionally, in this embodiment, the order sorting method described above may be applied to a hardware environment as shown in fig. 1. As shown in fig. 1, the terminal 102 may include a memory 104, a processor 106, and a display 108 (optional components). The terminal 102 may be communicatively coupled to a server 112 via a network 110, the server 112 may be configured to provide services (e.g., application services, etc.) for the terminal or for clients installed on the terminal, and a database 114 may be provided on the server 112 or separate from the server 112 for providing data storage services for the server 112. Additionally, a processing engine 116 may be run in the server 112, and the processing engine 116 may be used to perform the steps performed by the server 112.
Alternatively, the terminal 102 may be, but is not limited to, a terminal capable of calculating data, such as a mobile terminal (e.g., a mobile phone, a tablet Computer), a notebook Computer, a PC (Personal Computer) Computer, and the like, and the network may include, but is not limited to, a wireless network or a wired network. Wherein, this wireless network includes: bluetooth, WIFI (Wireless Fidelity), and other networks that enable Wireless communication. Such wired networks may include, but are not limited to: wide area networks, metropolitan area networks, and local area networks. The server 112 may include, but is not limited to, any hardware device capable of performing computations.
In addition, in this embodiment, the order sorting method described above may also be applied, but not limited to, to an independent processing device with a relatively high processing capability, without data interaction. For example, the processing device may be, but is not limited to, a terminal device with a relatively high processing capability, that is, each operation in the above order sorting method may be integrated into a single processing device. The above is merely an example, and this is not limited in this embodiment.
Optionally, in this embodiment, the order sorting method may be executed by the server 112, the terminal 102, or both the server 112 and the terminal 102. The method for the terminal 102 to execute the order ranking according to the embodiment of the present application may also be executed by a client installed thereon.
Taking the example of operating in the server, fig. 2 is a schematic flowchart of an alternative order sorting method according to an embodiment of the present application, and as shown in fig. 2, the flow of the method may include the following steps:
step S201, obtaining a plurality of order information, where the order information is information pushed by a target user after triggering a target service.
Optionally, in this embodiment of the application, after acquiring a target service clicked by a target user, the server triggers the generated push information, where the target user may be any client who operates ordering on a mobile terminal of the target user or an ordering terminal of a dining room counter, such as user 1, user 2, and the like, and the target service may be a service that can be clicked and purchased, such as a dining service, a take-out service, and the like, displayed on a screen of the mobile terminal or the ordering terminal of the dining room counter. The pushed message may be some order messages, such as an order number, generated about the purchased product after the current target user clicks to complete the target service.
Step S202, obtaining the associated information of a plurality of order information, wherein the associated information is used for describing the order information.
Optionally, after obtaining a plurality of order information, obtaining associated information characterizing and describing the order information, where the associated information may be a code of the order, a generation order of the order, a preset completion time of the order, and the like.
Step S203, processing the associated information by using a preset order sorting scheme to obtain first order sorting information, where the preset order sorting scheme is a preset sorting scheme.
Optionally, a preset order sorting scheme may be generated based on the obtained order related information, such as a generation order of the order, a priority number of the order, and the like, and the preset order sorting scheme may be used to perform a processing of the ranking scheme on the plurality of order information, so as to generate the first order sorting information.
It should be noted that the preset order ordering scheme is set in the following direction: the first order has no order in front and one order behind; there is no order behind the last order, there is an order in front; with one order before and one after the middle order, etc.
And step S204, processing the first order sequencing information by using a target algorithm model to obtain target order sequencing information, wherein the target algorithm model is used for sequencing the first order sequencing information to obtain a target sequencing solution.
Optionally, in this embodiment of the application, a target algorithm model is used to perform sorting processing on the first order sorting information, and an optimal target sorting solution is obtained in a manner of solving the sorting for multiple times, where the sorting information corresponding to the target sorting solution is the target order sorting information. Here, the target algorithm model is preferably a simulated annealing algorithm in the embodiment of the present application, and the embodiment of the present application does not specifically limit the target algorithm model.
In the embodiment of the application, a mode of order sorting is adopted, and a plurality of pieces of order information are obtained, wherein the order information is information pushed by a target user after a target service is triggered; acquiring associated information of a plurality of order information, wherein the associated information is used for describing the order information; processing the associated information by using a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset ranking scheme; and processing the first order sequencing information by using a target algorithm model to obtain target order sequencing information, wherein the target algorithm model is used for sequencing the first order sequencing information to obtain a target sequencing solution. According to the method and the device, the obtained order information is firstly sequenced by using the preset sequencing scheme, and then the sequenced order information is subjected to optimal solution calculation by using the target algorithm model to obtain the final target sequencing information, wherein the target sequencing information is the order sequencing considering the client priority and the client satisfaction, so that guidance is provided for the order sequencing of the restaurant, the overall delay time of the order is shortest, the overall satisfaction of the order is improved, and the problems that the order sequencing is unreasonable and the client satisfaction is low in the related technology are solved.
As an optional embodiment, before processing the associated information by using a preset order sorting scheme to obtain first order sorting information, the method includes:
generating a sorting constraint condition according to serial and continuous sorting characteristics of order information;
and generating a preset order sorting scheme by using the sorting constraint condition.
Optionally, in the embodiment of the present application, a sorting constraint condition is generated according to a serial and continuous sorting characteristic among a plurality of order information, where the sorting constraint condition is a constraint condition set in consideration of a priority of each order and an order sorting rule, and a preset order sorting scheme is obtained according to the constraint condition. The setting formula of the constraint condition is as follows:
wherein x isijThe value is 0 or 1, if the order i and the order j are continuously manufactured, the order i is made first, then the order j is made, the value is 1, otherwise, the value is 0; c. CjDesignating the preset manufacturing completion time of the order j; c. CiDesignating the preset manufacturing completion time of the order i; m isiThe making time of the order i; n is N total orders participating in sequencing, and the serial numbers 0 and N +1 are virtual head-to-tail orders; m is an infinite positive number.
The constraint conditions can be obtained, and the specific ordering rule corresponding to the preset order ordering scheme is as follows: the first order has no order in front and one order behind; there is no order behind the last order, there is an order in front; there is one order in front of and behind the middle order; the completion time of the post-production order is later than that of the early-production order; the food of the same order is continuously made, namely, only once. For example, according to a preset order sorting scheme, the first order sorting information is obtained as follows: 2-4-1-5-3, wherein the number is the order number.
In the embodiment of the application, the ordering constraint condition is set through the ordering characteristic based on the order information, so that the generated ordering constraint condition is more in line with the actual order condition.
As an alternative embodiment, the association information includes: the order placing time of the order information, the order making time, the preset order making completion time and the order priority, wherein before the first order ranking information is processed by using the target algorithm model to obtain the target order ranking information, the method comprises the following steps:
generating the order making completion time according to the order placing time of the order information and the order making time;
and generating an order optimization target object according to the order making completion time, the preset order making completion time and the order priority.
Optionally, in order to minimize the overall delay time of the order and maximize the overall satisfaction, the embodiment of the present application needs to set an optimization target (i.e., an order optimization target object), where the optimization target is: the priority of each customer is considered to minimize the overall delay time for the order.
At this time, the server obtains associated information of a plurality of order information, and the associated information mainly includes: the order information comprises order placing time, order making time, preset order making completion time and order priority. Further, the order making completion time of the order is generated according to the order placing time of the order information and the order making time of the order, for example, the order placing time when the order information is received is 15:00, and then the order making completion time of the order is 15:05 according to the order making time corresponding to the order information, for example, the order is ice cream, and the making time is 5 minutes.
Wherein 15:05 is the ideal completion time of the order, and the priority of the subsequently issued customer may be higher, so that the order of the customer with higher priority is considered when the order processing is performed. At this time, a preset manufacturing completion time of the order is acquired, for example, the preset manufacturing completion time is 15: 15.
Generating an order optimization target object according to the order making completion time, the preset order making completion time and the order priority, wherein the setting formula of the order optimization target object is as follows:
Minz＝wi×max(ci-pi,0)
wherein Minz is an order optimization target object, namely an optimization target order, and Minz means that the overall delay time is shortest; w is aiIs the priority of order i; c. CiDesignating the preset manufacturing completion time of the order i; p is a radical ofiRefers to the production completion time of order i (i.e., the ideal completion time for the order).
In the embodiment of the application, when the first order ranking information is processed by using the target algorithm model, the order optimization target object is set as the optimization target for processing the first order ranking information, so that the obtained target order ranking information can meet the optimization target, the overall delay time of the order is shortest, and the user satisfaction is improved.
As an optional embodiment, processing the first order ranking information by using the target algorithm model, and obtaining the target order ranking information includes:
optimizing a target object according to the order, sequencing the first order sequencing information by using a target algorithm model to obtain second order sequencing information, and adding one to the total iteration times;
and taking the second order sorting information as target order sorting information under the condition that the total iteration number corresponding to the second order sorting information is equal to a first preset threshold value.
Optionally, in this embodiment of the present application, the target object is optimized according to the order, and the target algorithm model is used to perform ranking processing on the first order ranking information, where the preferred target algorithm model is a simulated annealing algorithm, so that the first order ranking information, such as 2-4-1-5-3, is processed to obtain an optimal target solution.
Before introducing the simulated annealing algorithm, the embodiment of the present application first introduces a hill-climbing algorithm, which is a simple greedy search algorithm and may also be referred to as a local search algorithm, and the algorithm selects an optimal solution from a solution space adjacent to a current solution each time as the current solution until a local optimal solution is reached. The algorithm idea is simple, but a great defect exists. During the search selection, a local optimal solution may be trapped, and the local optimal solution is not necessarily a global optimal solution. As shown in fig. 3, assuming that a is the current solution, the hill-climbing algorithm continues searching forward, and when B, which is the local optimal solution, is searched, the search is stopped. Because no matter which side the point B goes, no better solution is obtained. However, the global optimal solution is at point C.
The simulated annealing algorithm introduces a random factor in the search process. The simulated annealing algorithm receives a solution worse than the current solution with a certain probability, so that the local optimal solution may be jumped out to reach the global optimal solution. After searching the local optimal solution B, the simulated annealing algorithm accepts rightward movement with a certain probability. The peak D between BC may be reached after several such moves that are not locally optimal, thus jumping out the locally optimal solution B, and continuing to move to the right makes it possible to obtain the globally optimal solution C, see fig. 4.
The Simulated Annealing Algorithm (SA) is used for solving the global optimization problem, and is a random optimization Algorithm based on a monte carlo iteration solution strategy. The simulated annealing algorithm has a simpler flow and randomly generates an initial solution starting from a higher temperature. Randomly selecting a candidate solution in the neighborhood of the current solution according to a certain rule, and replacing the current solution with the candidate solution if the current solution is superior to the candidate solution; otherwise, the solution candidate for the corruption is accepted with a certain probability. And when a certain number of iterations is reached, reducing the temperature and repeatedly executing the iterations. The annealing process is controlled by a cooling schedule. In each iteration, whether a stopping criterion is met or not is checked, if yes, the iteration is stopped, and the current optimal solution is output.
In the embodiment of the application, the first order ranking information is ranked by using a simulated annealing algorithm model to obtain second order ranking information, and an initial solution with better quality is continuously generated according to the order optimization target object, wherein the second order ranking information is one of the initial solutions.
The step of generating an initial solution comprises:
step 1: consider the best completion time for an order: the orders are ordered from morning to evening according to the best completion time for each order. This order does not take into account the order priority and therefore also requires an adjustment of the order ordering.
Step 2: consider the priority of the order: priority may have an impact on the ordering of orders, with high priority orders tending to line up first and vice versa. After the best completion time sequence is considered in the first step, the order priority affects order ranking, and a certain time can be selected, for example, orders within 15s are ranked from high to low according to the priority.
And performing iterative search on the basis, then adding one to the current total iteration number, stopping processing under the condition that the total iteration number corresponding to the second order sorting information is equal to a first preset threshold value, and taking the second order sorting information as target order sorting information. The first preset threshold is a common iteration number, and may be obtained according to historical experience or set manually in advance.
As an optional embodiment, processing the first order ranking information by using the target algorithm model, and obtaining the target order ranking information includes:
optimizing a target object according to the order, sequencing the first order sequencing information by using a target algorithm model to obtain second order sequencing information, and adding one to the total iteration times;
comparing order sorting information correspondingly generated by each iteration number under the condition that the obtained total iteration number is equal to a first preset threshold value;
and taking the order sorting information as target order sorting information under the condition that the matching times among the plurality of order sorting information are equal to a second preset threshold value.
Optionally, in the manner of determining to stop iteration, in addition to stopping iteration after the number of iterations reaching the preset first preset threshold in the above embodiment, the iteration may also be stopped if the historical optimal solution is not changed for several times, and then the iteration is stopped, and the current historical optimal solution is output.
Further, in the embodiment of the present application, under the condition that the obtained total number of iterations is equal to a first preset threshold, comparing order ranking information correspondingly generated for each iteration number; and if the plurality of pieces of order sorting information are all identical, and meanwhile, the identical times (namely, the matching times) are equal to a second preset threshold value, taking the order sorting information as target order sorting information. The second preset threshold is an integer value, and may be obtained according to historical experience or set manually in advance.
As an optional embodiment, after the processing the associated information by using a preset order sorting scheme to obtain the first order sorting information, the method further includes:
executing preset conversion operation on each sub-order information in the first order sorting information to obtain third order sorting information;
and processing the third order sequencing information by using a target algorithm model to obtain target order sequencing information.
Optionally, after the associated information is processed by using a preset order sorting scheme to obtain first order sorting information, performing preset transformation operation on each sub-order information in the first order sorting information to obtain third order sorting information, where the sub-order information is order information for each user to place an order independently, for example, the first order sorting information is 2-4-1-5-3, and then the sub-order information may be: any one of order information numbered 2, order information numbered 4, order information numbered 1, order information numbered 5, and order information numbered 3.
Further, the preset transform operation includes: point exchange, point insertion, and point reverse order. The executing of the preset transformation operation on each sub-order information includes at least one of:
and acquiring the position information of any two pieces of sub-order information, and executing position exchange operation. For example, exchanging the order information numbered 2 and the position information of the order information numbered 1 to obtain third order ranking information: 1-4-2-5-3.
And inserting any sub-order information into any position except the position of the current sub-order information. For example, the order information numbered 2 is inserted behind the order information numbered 3 to obtain third order ranking information: 4-1-5-3-2.
And acquiring any two pieces of sub-order information and other sub-order information between the two pieces of sub-order information, and performing reverse order operation on the two pieces of sub-order information and the other sub-order information. For example, the order information numbered 2 and the order information numbered 1 are obtained, the order information numbered 2 and the order information numbered 1, and other sub-order information between the two order information, that is, the order information numbered 4, are subjected to reverse order operation to obtain third order ordering information: 4-2-1-5-3.
And then, processing the third order ordering information obtained through the preset transformation operation by using a target algorithm model, finding an optimal target solution, and obtaining final target order ordering information.
In the embodiment of the application, the transformation operation is executed on each sub-order information summarized by the first order ranking information, so that the target algorithm model can find a more accurate optimal solution conveniently.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (e.g., a ROM (Read-Only Memory)/RAM (Random Access Memory), a magnetic disk, an optical disk) and includes several instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the methods of the embodiments of the present application.
According to another aspect of the embodiment of the application, an order sorting device for implementing the order sorting method is further provided. Fig. 5 is a block diagram of an alternative order sorting apparatus according to an embodiment of the present application, and as shown in fig. 5, the apparatus may include:
a first obtaining unit 501, configured to obtain a plurality of order information, where the order information is information pushed by a target user after triggering a target service;
a second obtaining unit 502, configured to obtain associated information of a plurality of order information, where the associated information is used to describe the order information;
the first processing unit 503 is configured to process the associated information by using a preset order sorting scheme to obtain first order sorting information, where the preset order sorting scheme is a preset ranking scheme;
the second processing unit 504 is configured to process the first order ranking information by using a target algorithm model to obtain target order ranking information, where the target algorithm model is configured to rank the first order ranking information to obtain a target ranking solution.
It should be noted that the first acquiring unit 501 in this embodiment may be configured to execute the step S201, the second acquiring unit 502 in this embodiment may be configured to execute the step S202, the first processing unit 503 in this embodiment may be configured to execute the step S203, and the second processing unit 504 in this embodiment may be configured to execute the step S204.
Through the module, a plurality of order information is acquired in an order sorting mode, wherein the order information is information pushed by a target user after a target service is triggered; acquiring associated information of a plurality of order information, wherein the associated information is used for describing the order information; processing the associated information by using a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset ranking scheme; and processing the first order sequencing information by using a target algorithm model to obtain target order sequencing information, wherein the target algorithm model is used for sequencing the first order sequencing information to obtain a target sequencing solution. According to the method and the device, the obtained order information is firstly sequenced by using the preset sequencing scheme, and then the sequenced order information is subjected to optimal solution calculation by using the target algorithm model to obtain the final target sequencing information, wherein the target sequencing information is the order sequencing considering the client priority and the client satisfaction, so that guidance is provided for the order sequencing of the restaurant, the overall delay time of the order is shortest, the overall satisfaction of the order is improved, and the problems that the order sequencing is unreasonable and the client satisfaction is low in the related technology are solved.
As an alternative embodiment, the apparatus comprises: the first generation unit is used for generating a sorting constraint condition according to serial and continuous sorting characteristics of the order information before processing the associated information by using a preset order sorting scheme to obtain first order sorting information; and the second generation unit is used for generating a preset order sorting scheme by using the sorting constraint condition.
As an alternative embodiment, the association information includes: the order placing time of the order information, the making time of the order, the preset making completion time of the order and the priority of the order, the device also comprises: the third generating unit is used for generating order making completion time according to the order placing time of the order information and the order making time before the first order ordering information is processed by using the target algorithm model to obtain the target order ordering information; and the fourth generating unit is used for generating the order optimization target object according to the order making completion time, the preset order making completion time and the order priority.
As an alternative embodiment, the second processing unit comprises: the first obtaining module is used for optimizing a target object according to an order, utilizing a target algorithm model to carry out sorting processing on the first order sorting information to obtain second order sorting information, and adding one to the total iteration times; and the first setting module is used for taking the second order sorting information as the target order sorting information under the condition that the total iteration number corresponding to the second order sorting information is equal to a first preset threshold value.
As an alternative embodiment, the second processing unit comprises: the second obtaining module is used for optimizing a target object according to the order, utilizing the target algorithm model to carry out sorting processing on the first order sorting information to obtain second order sorting information, and adding one to the total iteration times; the comparison module is used for comparing the order sorting information correspondingly generated by each iteration number under the condition that the obtained total iteration number is equal to a first preset threshold value; and the second setting module is used for taking the order sorting information as the target order sorting information under the condition that the matching times among the plurality of order sorting information are equal to a second preset threshold value.
As an alternative embodiment, the apparatus further comprises: the conversion operation unit is used for performing preset conversion operation on each sub-order information in the first order sorting information to obtain third order sorting information after the associated information is processed by using a preset order sorting scheme to obtain the first order sorting information; and the third processing unit is used for processing the third order sorting information by using the target algorithm model to obtain the target order sorting information.
As an alternative embodiment, the transformation operation unit includes at least one of: the exchange module is used for acquiring the position information of any two pieces of sub-order information and executing position exchange operation; the inserting module is used for inserting any sub-order information into any position except the position of the current sub-order information; and the reverse order module is used for acquiring any two pieces of sub order information and other pieces of sub order information between the two pieces of sub order information and executing reverse order operation on the two pieces of sub order information and the other pieces of sub order information.
It should be noted here that the modules described above are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the disclosure of the above embodiments. It should be noted that the modules described above as a part of the apparatus may be operated in a hardware environment as shown in fig. 1, and may be implemented by software, or may be implemented by hardware, where the hardware environment includes a network environment.
According to another aspect of the embodiments of the present application, there is also provided an electronic device for implementing the above order sorting method, where the electronic device may be a server, a terminal, or a combination thereof.
Fig. 6 is a block diagram of an alternative electronic device according to an embodiment of the present application, as shown in fig. 6, including a processor 601, a communication interface 602, a memory 603, and a communication bus 604, where the processor 601, the communication interface 602, and the memory 603 complete communication with each other through the communication bus 604, where,
a memory 603 for storing a computer program;
the processor 601, when executing the computer program stored in the memory 603, implements the following steps:
s1, acquiring a plurality of order information, wherein the order information is information pushed by a target user after triggering a target service;
s2, acquiring the associated information of a plurality of order information, wherein the associated information is used for describing the order information;
s3, processing the associated information by using a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset sorting scheme;
and S4, processing the first order sorting information by using a target algorithm model to obtain target order sorting information, wherein the target algorithm model is used for sorting the first order sorting information to obtain a target sorting solution.
Alternatively, in this embodiment, the communication bus may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 6, but this is not intended to represent only one bus or type of bus.
The communication interface is used for communication between the electronic equipment and other equipment.
The memory may include RAM, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory. Alternatively, the memory may be at least one memory device located remotely from the processor.
As an example, as shown in fig. 6, the memory 603 may include, but is not limited to, a first obtaining unit 501, a second obtaining unit 502, a first processing unit 503, and a second processing unit 504 of the order sorting apparatus. In addition, the order sorting device may further include, but is not limited to, other module units in the order sorting device, which is not described in this example again.
The processor may be a general-purpose processor, and may include but is not limited to: a CPU (Central Processing Unit), an NP (Network Processor), and the like; but also a DSP (Digital Signal Processing), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component.
In addition, the electronic device further includes: and the display is used for displaying the sequencing result of the order.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment is not described herein again.
It can be understood by those skilled in the art that the structure shown in fig. 6 is only an illustration, and the device implementing the order sorting method may be a terminal device, and the terminal device may be a terminal device such as a smart phone (e.g., an Android phone, an iOS phone, etc.), a tablet computer, a palm computer, a Mobile Internet Device (MID), a PAD, and the like. Fig. 6 is a diagram illustrating a structure of the electronic device. For example, the terminal device may also include more or fewer components (e.g., network interfaces, display devices, etc.) than shown in FIG. 6, or have a different configuration than shown in FIG. 6.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program instructing hardware associated with the terminal device, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disk, ROM, RAM, magnetic or optical disk, and the like.
According to still another aspect of an embodiment of the present application, there is also provided a storage medium. Optionally, in this embodiment, the storage medium may be used for a program code for executing the order sorting method.
Optionally, in this embodiment, the storage medium may be located on at least one of a plurality of network devices in a network shown in the above embodiment.
Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps:
s1, acquiring a plurality of order information, wherein the order information is information pushed by a target user after triggering a target service;
s2, acquiring the associated information of a plurality of order information, wherein the associated information is used for describing the order information;
s3, processing the associated information by using a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset sorting scheme;
and S4, processing the first order sorting information by using a target algorithm model to obtain target order sorting information, wherein the target algorithm model is used for sorting the first order sorting information to obtain a target sorting solution.
Optionally, the specific example in this embodiment may refer to the example described in the above embodiment, which is not described again in this embodiment.
Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing program codes, such as a U disk, a ROM, a RAM, a removable hard disk, a magnetic disk, or an optical disk.
According to yet another aspect of an embodiment of the present application, there is also provided a computer program product or a computer program comprising computer instructions stored in a computer readable storage medium; the computer instructions are read by a processor of a computer device from a computer-readable storage medium, and the computer instructions are executed by the processor to cause the computer device to perform the method steps of order ordering in any of the embodiments described above.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
The integrated unit in the above embodiments, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in the above computer-readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or a part or all of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a storage medium, and including several instructions for causing one or more computer devices (which may be personal computers, servers, network devices, or the like) to execute all or part of the steps of the order ordering method of the embodiments of the present application.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed client may be implemented in other manners. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit is merely a division of a logic function, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, and may also be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution provided in the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. A method of order ordering, the method comprising:
acquiring a plurality of order information, wherein the order information is information pushed by a target user after triggering a target service;
acquiring associated information of a plurality of order information, wherein the associated information is used for describing the order information;
processing the associated information by using a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset sorting scheme;
and processing the first order sorting information by using a target algorithm model to obtain target order sorting information, wherein the target algorithm model is used for sorting the first order sorting information to obtain a target sorting solution.
2. The method according to claim 1, wherein before the processing the associated information by using the preset order sorting scheme to obtain the first order sorting information, the method comprises:
generating a sorting constraint condition according to the serial and continuous sorting characteristics of the order information;
and generating the preset order sorting scheme by using the sorting constraint condition.
3. The method of claim 2, wherein the association information comprises: the order placing time of the order information, the order making time, the preset order making completion time and the order priority, wherein before the first order ranking information is processed by using a target algorithm model to obtain target order ranking information, the method comprises the following steps:
generating the order making completion time according to the order placing time of the order information and the order making time;
and generating an order optimization target object according to the making completion time of the order, the preset making completion time of the order and the priority of the order.
4. The method of claim 3, wherein the processing the first order ranking information using the target algorithm model to obtain target order ranking information comprises:
optimizing a target object according to the order, sequencing the first order sequencing information by using the target algorithm model to obtain second order sequencing information, and adding one to the total iteration times;
and taking the second order sorting information as the target order sorting information under the condition that the total iteration number corresponding to the second order sorting information is equal to a first preset threshold value.
5. The method of claim 3, wherein the processing the first order ranking information using the target algorithm model to obtain target order ranking information comprises:
optimizing a target object according to the order, sequencing the first order sequencing information by using the target algorithm model to obtain second order sequencing information, and adding one to the total iteration times;
comparing the order sorting information correspondingly generated by each iteration number under the condition that the obtained total iteration number is equal to a first preset threshold value;
and taking the order sorting information as the target order sorting information under the condition that the matching times among the plurality of order sorting information are equal to a second preset threshold value.
6. The method according to claim 1, wherein after the processing the associated information by using the preset order sorting scheme to obtain first order sorting information, the method further comprises:
executing preset conversion operation on each sub-order information in the first order sorting information to obtain third order sorting information;
and processing the third order sequencing information by using the target algorithm model to obtain the target order sequencing information.
7. The method of claim 6, wherein performing a preset transformation operation on each sub-order information in the first order ranking information comprises at least one of:
acquiring the position information of any two pieces of sub-order information, and executing position exchange operation;
inserting any sub-order information into any position except the position of the current sub-order information;
and acquiring any two pieces of sub-order information and other sub-order information between the two pieces of sub-order information, and performing reverse order operation on the two pieces of sub-order information and the other sub-order information.
8. An apparatus for ordering orders, the apparatus comprising:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a plurality of order information, and the order information is information pushed by a target user after a target service is triggered;
a second obtaining unit, configured to obtain associated information of the plurality of order information, where the associated information is used to describe the order information;
the first processing unit is used for processing the associated information by utilizing a preset order sorting scheme to obtain first order sorting information, wherein the preset order sorting scheme is a preset ranking scheme;
and the second processing unit is used for processing the first order sorting information by using a target algorithm model to obtain target order sorting information, wherein the target algorithm model is used for sorting the first order sorting information to obtain a target sorting solution.
9. An electronic device comprising a processor, a communication interface, a memory and a communication bus, wherein said processor, said communication interface and said memory communicate with each other via said communication bus,
the memory for storing a computer program;
the processor for performing the method steps of order sequencing of any of claims 1 to 7 by running the computer program stored on the memory.
10. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to carry out the method steps of order ordering according to any of claims 1 to 7 when executed.
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