Intelligent order dispatching engine system based on own price source
Through the settings of the own price source module and the intelligent order dispatch engine module, the lack of the own price source and intelligent order dispatch engine under the traditional model is solved, and intelligent order disassembly and order dispatch in the international air ticket industry is realized, which improves order processing efficiency and customer booking success rate.
Patent Information
- Application Number
- CN202510301013.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-14
- Publication Date
- 2025-07-25
AI Technical Summary
The lack of own price sources and intelligent order distribution engines under the traditional model has led to the inability to realize intelligent order distribution and order distribution in the international air ticket industry, especially when seats in the shortage of temporary flights cannot be achieved.
Set up the own price source module and the intelligent order dispatch engine module. The own price source module collects and cleanses flight and price data and stores it in a highly available database; the intelligent order dispatch engine module disassembles the composite order into multiple simple orders through a recursive algorithm, and reasonably splits the orders based on the order dispatch results, supporting the number of passengers and route splits.
It improves order processing efficiency, improves customer booking success rate and convenience, and enhances the rationality of the system's intelligent management.
Smart Images
Figure CN120374216A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of airline ticket reservation and distribution, and particularly relates to an intelligent order assignment engine system based on its own price source. Background Art
[0002] At present, in the international airline ticket industry, for the same flight, especially for flights with tight seats such as those about to take off, there are often large differences in unit prices between multiple-person quotes and single-person quotes. In the traditional mode, there are the following two main problems, which lead to the inability to achieve intelligent order splitting and assignment: (1) There is no own price source: In the traditional mode, quotes rely on the quotes of upstream suppliers. Therefore, it is impossible to receive orders without requesting upstream suppliers; (2) There is no intelligent order assignment engine: It is impossible to achieve fully automatic intelligent order splitting, price comparison, and finding the optimal order splitting strategy in the system. In this regard, there is an urgent need to provide an intelligent order assignment engine system based on its own price source to solve the above-mentioned technical problems. Summary of the Invention
[0003] In view of this, the present invention provides an intelligent order assignment engine system based on its own price source, which sets up its own price source and intelligent order assignment engine, can achieve intelligent order splitting and assignment, improve the convenience of customer reservation, and enhance the rationality of system intelligent management. The specific technical solutions are as follows.
[0004] The present invention provides an intelligent order assignment engine system based on its own price source, including:
[0005] An own price source module, which is used to collect various flight and price data, and clean and structure them through big data; store the price data in a highly available content database, and use it as the data source for order receiving and quoting;
[0006] An intelligent order assignment engine module, which is used to efficiently and intelligently disassemble a composite order into multiple simple orders, and the sum of the prices of the multiple orders is lower than the price of the composite order;
[0007] Among them, the intelligent order assignment engine module includes an order assignment engine sub-module and an order splitting and generation sub-module. The order assignment engine sub-module is used to disassemble a composite order into multiple simple orders by using a recursive algorithm; the order splitting and generation sub-module is used to reasonably split the purchase order according to the order assignment result of the intelligent order assignment engine, and support splitting sub-orders by the number of passengers, splitting one-way sub-orders for round-trip tickets, and splitting sub-orders for one-way transit tickets. After the split orders are successfully reserved with the optimal supplier, the order information of the supplier is generated into the intelligent order assignment engine system.
[0008] As an optimization of the above technical solution, the self-owned price source module includes a flight quotation information collection sub-module and a flight quotation data transmission and cleaning sub-module. The flight quotation information collection sub-module uses the official website interfaces of airlines, quotation information provided by high-quality suppliers, and self-operated account interfaces to obtain real-time ticket price data for popular routes of major airlines.
[0009] The flight quotation data transmission and cleaning sub-module uses the Kafka algorithm to quickly transfer massive metric data. The corresponding big data platform uses the Flink processing framework to collect data into the Doris database and conducts complex data cleaning and restructuring work.
[0010] As an optimization of the above technical solution, the self-owned price source module further includes a self-owned price source library construction sub-module and a self-owned price source receipt sub-module. The self-owned price source library construction sub-module constructs a self-owned price source system from the cleaned and restructured price data, and intelligently eliminates cache objects by applying the LRU algorithm to optimize the return on investment.
[0011] The self-owned price source receipt sub-module is used to determine the self-owned price source and return flight and quotation information during the search, price verification, and reservation stages when the customer makes a reservation, so as to complete the customer's reservation and payment.
[0012] As an optimization of the above technical solution, the self-owned price source library construction sub-module uses an open-source distributed high-performance key-value storage system as the cache medium and constructs a self-owned price source system from the cleaned and restructured price data.
[0013] As an optimization of the above technical solution, the recursive algorithm evaluates each component in the conforming order according to predefined rules and logic, identifies sub-orders that can be processed independently, and continues to recursively apply the same process until all possible simple orders are successfully separated.
[0014] As an optimization of the above technical solution, the construction process of the self-owned price source library corresponding to the self-owned price source module includes:
[0015] S60: Obtain the flight data sources, where the flight data sources include the official website interfaces of airlines, quotation information provided by high-quality suppliers, and self-operated account interfaces;
[0016] S61: Develop differentiated data acquisition strategies for different data sources to obtain flight data;
[0017] S62: Use the transmission ability of Kafka to quickly transfer massive metric data;
[0018] S63: The big data platform uses the Flink processing framework to accurately collect data into the Doris database and perform complex data cleaning and restructuring tasks;
[0019] S64: By relying on an open-source distributed high-performance key-value storage system as the cache medium, the cleaned and restructured price data is built into its own price source system.
[0020] As an optimization of the above technical solution, the order splitting process executed by the intelligent order assignment engine module includes:
[0021] S70: Obtain the order reserved by the customer, where the passengers in the order reserved by the customer include two adults and one child;
[0022] S71: Initiate search and price verification to multiple upstream suppliers in two ways: single adult and child, and two adults and child respectively;
[0023] S72: Determine whether the search and price verification in both ways are successful;
[0024] S73: Determine whether the price of the search and price verification result in the single adult and child way is the lowest;
[0025] S74: Initiate a reservation for a single adult and child to the supplier and correspondingly determine whether the reservation is successful;
[0026] S75: Initiate search and price verification for the remaining one adult to multiple upstream suppliers in the single adult way;
[0027] S76: Determine whether the combination price of the single adult and child price plus the single adult is the lowest;
[0028] S77: If the price in S76 is the lowest, initiate a reservation for the remaining one adult to multiple upstream suppliers in the single adult way and correspondingly determine whether the reservation is successful;
[0029] S78: When the judgment results of S75, S76, and S78 are negative, cancel the reservation upstream;
[0030] S79: When the judgment results of S72, S73, S74, S75, S76, and S77 are negative, no more order splitting is performed;
[0031] S80: After S79 stops splitting the order, the order is assigned as a whole order, where the whole order way is two adults and one child;
[0032] S81: When the reservation in S77 is successful, split the order to obtain the split result.
[0033] Preferably, for the above technical solution, an order corresponding to two adults and one child is recorded as a two - adults - and - one - child order, an order corresponding to one adult and one child is recorded as a one - adult - and - one - child order, and an order corresponding to one adult in a single - person manner is recorded as a one - adult order.
[0034] Preferably, for the above technical solution, the order - splitting result is a one - adult - and - one - child order and a one - adult order, and the whole - order method is a two - adults - and - one - child order.
[0035] The present invention provides an intelligent order - dispatching engine system based on its own price source. By setting up an own - price - source module and an intelligent order - dispatching engine module, the own - price - source module collects various flight and price data, cleans and structures them through big data, stores the price data in a highly available content database, and uses it as the data source for order - receiving quotes; the intelligent order - dispatching engine module efficiently and intelligently disassembles a composite order into multiple simple orders, and the sum of the prices of the multiple orders is lower than the price of the composite order. By gradually decomposing complex order problems into simpler sub - problems, the order - processing efficiency of the system can be improved. According to the order - dispatching result of the intelligent order - dispatching engine, the purchase order is reasonably split, which improves the success rate of customer reservations. By setting up the own - price - source and the intelligent order - dispatching engine, intelligent order - splitting and order - dispatching can be achieved, improving the convenience of customer reservations and enhancing the rationality of the system's intelligent management. BRIEF DESCRIPTION OF THE DRAWINGS
[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.
[0037] Figure 1 It is a structural block diagram of the intelligent order - dispatching engine system based on its own price source provided by the present invention;
[0038] Figure 2 It is a construction process diagram of the own - price - source library provided by the present invention;
[0039] Figure 3 It is a order - splitting process diagram executed by the intelligent order - dispatching engine module provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0040] The following will describe in detail the embodiments of the present invention. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.
[0041] Refer to Figure 1 , the present invention provides an intelligent order assignment engine system based on its own price source, including:
[0042] An own price source module, configured to collect various flight and price data, and perform cleaning and structuring through big data; store the price data in a highly available content database, and use it as the data source for order receiving and quoting;
[0043] An intelligent order assignment engine module, configured to efficiently and intelligently disassemble a composite order into multiple simple orders, and the sum of the prices of the multiple orders is lower than the price of the composite order;
[0044] Among them, the intelligent order assignment engine module includes an order assignment engine sub-module and a disassembling and generating sub-module. The order assignment engine sub-module is configured to disassemble a composite order into multiple simple orders by using a recursive algorithm; the disassembling and generating sub-module is configured to reasonably split a purchase order according to the order assignment result of the intelligent order assignment engine, and support splitting sub-orders by the number of passengers, splitting one-way sub-orders for round trips, and splitting sub-orders for one-way transfers. After the split orders are successfully reserved with the optimal supplier, the order information of the supplier is generated into the intelligent order assignment engine system.
[0045] In this embodiment, the own price source module includes a flight quotation information collection sub-module and a flight quotation data transmission and cleaning sub-module. The flight quotation information collection sub-module uses the official website interface of airlines, the quotation information provided by high-quality suppliers, and the self-operated account interface to obtain real-time ticket price data for popular routes of major airlines; the flight quotation data transmission and cleaning sub-module uses the Kafka algorithm to quickly transfer a large amount of metric data, and the corresponding big data platform uses the Flink processing framework to collect data into the Doris database, and performs complex data cleaning and restructuring work. The own price source module further includes a self-owned price source library construction sub-module and a self-owned price source order receiving sub-module. The self-owned price source library construction sub-module constructs a self-owned price source system from the cleaned and restructured price data, and intelligently eliminates cache objects by applying the LRU (Least Recently Used) algorithm to optimize the return on investment (ROI); the self-owned price source order receiving sub-module is configured to determine the own price source to return flight and quotation information during the search, price verification, and reservation phases when a customer makes a reservation, so as to complete the customer's reservation and payment.
[0046] It should be noted that the sub-module for building its own price source library uses an open-source distributed high-performance key-value storage system as a caching medium, and constructs its own price source system from the cleaned and restructured price data. The recursive algorithm evaluates each component in the composite order according to predefined rules and logic, identifies sub-orders that can be processed independently, and continues to recursively apply the same process until all possible simple orders are successfully separated. Apache Doris is a high-performance, real-time analytical database based on the MPP architecture, known for its extremely fast and easy-to-use characteristics. It can return query results under massive data with a response time of only sub-seconds. It can not only support high-concurrency point query scenarios but also high-throughput complex analysis scenarios. The overall architecture of Doris includes Frontend (FE) and Backend (BE). Frontend (FE) is mainly responsible for user request access, query parsing and planning, metadata management, and node management related work; Backend (BE) is mainly responsible for data storage and query plan execution. Kafka is a distributed event streaming platform widely used in high-performance data pipelines, stream analysis, data integration, and mission-critical related applications. The architecture of Flink follows the principle of hierarchical design, mainly divided into three layers: API & Libraries layer, Runtime core layer, and physical deployment layer.
[0047] Specifically, after the customer payment is completed, the order dispatching engine sub-module efficiently disassembles a composite order into multiple simple orders through an intelligent order dispatching strategy by the intelligent order dispatching engine, while ensuring that the sum of the prices of the simple orders is lower than the original composite order, providing a more competitive price advantage for the customer. The recursive algorithm will play a crucial role in this process. It achieves this by gradually decomposing complex order problems into simpler sub-problems. Specifically, the algorithm evaluates each component in the composite order according to predefined rules and logic, and identifies sub-orders that can be processed independently. Then, it will continue to recursively apply the same process until all possible simple orders are successfully separated.
[0048] Specifically, the sub-module for order splitting and generation reasonably splits the purchase order according to the order dispatching result of the intelligent order dispatching engine, and needs to support sub-orders for splitting the number of passengers, splitting round-trip into one-way sub-orders, and splitting one-way with transfers into sub-orders. After the split orders are successfully reserved with the optimal suppliers, the supply order information is generated into the system.
[0049] It should be understood that by setting up a proprietary price source module and an intelligent dispatch engine module, the proprietary price source module collects data on various flights and prices, cleans and structures them through big data, stores the price data in a high-availability content database, and serves as a data source for order collection quotations; the intelligent dispatch engine module efficiently and intelligently decomposes compound orders into multiple simple orders, and the sum of the prices of multiple orders is lower than the price of the compound order. By gradually decomposing complex order problems into simpler sub-problems, the order processing efficiency of the system can be improved, and the purchase orders can be reasonably split according to the dispatch results of the intelligent dispatch engine, thereby improving the success rate of customer reservations. Setting up a proprietary price source and an intelligent dispatch engine can realize intelligent order splitting and dispatching, thereby improving the convenience of customer reservations and the rationality of the system's intelligent management.
[0050] See also Figure 2 The construction process of the proprietary price source library corresponding to the proprietary price source module includes:
[0051] S60: Obtaining flight data sources, where the flight data sources include airline official website interfaces, quotation information provided by high-quality suppliers, and self-operated account interfaces;
[0052] S61: Develop differentiated data acquisition strategies for different data sources to obtain flight data;
[0053] S62: Use Kafka's transmission capabilities to quickly transfer massive amounts of indicator data;
[0054] S63: The big data platform uses the Flink processing framework to accurately collect data into the Doris database and carry out complex data cleaning and re-structuring;
[0055] S64: It uses an open source distributed high-performance key-value storage system as a cache medium to build its own price source system with cleaned and restructured price data.
[0056] In this embodiment, building a proprietary price source database can be understood as follows: the source of flight data is the official website interface of the airline, the quotation information provided by high-quality suppliers, and the self-operated account interface; differentiated data acquisition strategies are formulated for different data sources to obtain flight data; with the help of Kafka's powerful transmission capabilities, massive indicator data is quickly transferred; the big data platform uses Flink, an efficient stream processing framework, to accurately collect data to Doris DB (database), and carry out complex data cleaning and re-structuring work; relying on the open source distributed high-performance key-value (Key-Value, KV) storage system as a cache medium, the cleaned and re-structured price data is built into a large and efficient proprietary price source system.
[0057] See also Figure 3, the order splitting process executed by the intelligent order assignment engine module includes:
[0058] S70: Obtain the order reserved by the customer. The passengers in the order reserved by the customer include two adults and one child;
[0059] S71: Initiate search and price verification to multiple upstream suppliers in two ways: single adult and child, and two adults and child respectively;
[0060] S72: Determine whether the search and price verification in both ways are successful;
[0061] S73: Determine whether the price of the search and price verification result in the way of single adult and child is the lowest;
[0062] S74: Initiate a reservation for single adult and child to the supplier, and correspondingly determine whether the reservation is successful;
[0063] S75: Initiate search and price verification for the remaining one adult to multiple upstream suppliers in the way of single adult;
[0064] S76: Determine whether the combination price of the price of single adult and child plus a single adult is the lowest;
[0065] S77: If the price in S76 is the lowest, initiate a reservation for the remaining one adult to multiple upstream suppliers in the way of single adult, and correspondingly determine whether the reservation is successful;
[0066] S78: When the judgment results of S75, S76, and S78 are negative, cancel the reservation upstream;
[0067] S79: When the judgment results of S72, S73, S74, S75, S76, and S77 are negative, no longer perform order splitting;
[0068] S80: After S79 no longer performs order splitting, the order is assigned as a whole order. Among them, the whole order way is two adults and one child;
[0069] S81: When the reservation in S77 is successful, split the order to obtain the order splitting result.
[0070] In this embodiment, the intelligent order assignment engine executes according to the order splitting logic for passengers (two adults and one child), specifically as follows: (1) Two adults and one child mean that the passengers in the order reserved by the customer include two adults and one child; (2) Search for price verification is initiated to multiple upstream suppliers in two ways: single adult + child and two adults + child respectively; (3) Determine whether the search for price verification in both ways is successful; (4) Determine whether the price of the search for price verification result in the single adult + child mode is the lowest; (5) Initiate a reservation for single adult + child to the supplier and determine whether the reservation is successful; (6) Search for price verification is initiated to multiple upstream suppliers for the remaining one adult in the single adult mode; (7) Whether the combined price corresponding to the price of single adult + child plus the price of a single adult is the lowest; (8) If the combined price is the lowest, the remaining one adult initiates a reservation upstream in the single adult mode and determine whether the reservation is successful; (9) When the judgments in steps (6), (7), and (8) are negative, cancel the reservation upstream; (10) When the judgments in steps (3), (4), (5), (6), (7), and (8) are negative, no further order splitting is performed; (11) After no further order splitting in step (10), the order is assigned as a whole order (two adults and one child); (12) After the reservation in step (8) is successful, the order is split (one adult and one child order + one adult order).
[0071] In all the examples shown and described here, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values.
[0072] It should be noted that like reference numerals and letters denote like items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.
[0073] The above-described embodiments merely represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention.
Claims
1. An intelligent order dispatching engine system based on its own price source, characterized in that, including: An in-house price source module for collecting various flight and price data and cleaning and structuring them through big data; Storing the price data in a highly available content database and using it as the data source for acquiring orders and quoting prices; An intelligent order dispatching engine module for efficiently and intelligently disassembling a composite order into multiple simple orders, where the sum of the prices of the multiple orders is lower than the price of the composite order; Among them, the intelligent order dispatching engine module includes an order dispatching engine sub-module and an order disassembling and generating sub-module. The order dispatching engine sub-module is used to disassemble a composite order into multiple simple orders by using a recursive algorithm; the order disassembling and generating sub-module is used to reasonably split a purchase order according to the order dispatching result of the intelligent order dispatching engine, and support splitting sub-orders by the number of passengers, splitting one-way sub-orders for round trips, and splitting sub-orders for one-way transfers. After the split orders are successfully reserved from the optimal supplier, the order information of the supplier is generated into the intelligent order dispatching engine system.
2. The intelligent order dispatch engine system based on its own price source according to claim 1, wherein The in-house price source module includes a flight quote information collection sub-module and a flight quote data transmission and cleaning sub-module. The flight quote information collection sub-module uses the official website interface of airlines, the quote information provided by high-quality suppliers, and the self-operated account interface to obtain real-time ticket price data for popular routes of major airlines; The flight quote data transmission and cleaning sub-module uses the Kafka algorithm to quickly transfer massive metric data. The corresponding big data platform uses the Flink processing framework to collect data into the Doris database and perform complex data cleaning and restructuring work.
3. The intelligent order assignment engine system based on its own price source according to claim 2, wherein The in-house price source module also includes a self-owned price source library construction sub-module and a self-owned price source order acquisition sub-module. The self-owned price source library construction sub-module constructs the cleaned and restructured price data into a self-owned price source system and intelligently eliminates cache objects by applying the LRU algorithm to optimize the return on investment; The self-owned price source order acquisition sub-module is used to determine the flight and quote information returned by the self-owned price source during the search, price verification, and reservation stages when a customer makes a reservation to complete the customer's reservation and payment.
4. The intelligent order dispatching engine system based on its own price source according to claim 3, characterized in that The self-owned price source library construction sub-module uses an open-source distributed high-performance key-value storage system as the cache medium and constructs the cleaned and restructured price data into a self-owned price source system.
5. The intelligent order dispatching engine system based on its own price source according to claim 1, characterized in that The recursive algorithm evaluates each component in the composite order according to predefined rules and logic, identifies sub-orders that can be processed independently, and continues to recursively apply the same process until all possible simple orders are successfully separated.
6. The intelligent order assignment engine system based on its own price source according to claim 1, characterized in that, The construction process of the self-owned price source library corresponding to the in-house price source module includes: S60: Obtain the flight data sources, where the flight data sources include the official website interface of airlines, the quote information provided by high-quality suppliers, and the self-operated account interface; S61: Develop a differentiated data acquisition strategy for different data sources to obtain flight data; S62: Use the transmission ability of Kafka to quickly transfer massive metric data; S63: The big data platform uses the Flink processing framework to accurately collect data into the Doris database and perform complex data cleaning and restructuring work; S64: Use an open-source distributed high-performance key-value storage system as the cache medium to build a self-owned price source system with the cleaned and restructured price data.
7. The intelligent order dispatching engine system based on its own price source according to claim 1, characterized in that, The order splitting process executed by the intelligent order dispatching engine module includes: S70: Obtain the order reserved by the customer, where the passengers in the order reserved by the customer include two adults and one child; S71: Initiate search for price verification to multiple upstream suppliers in two ways: single adult and child, and two adults and child; S72: Determine whether the search for price verification in both ways is successful; S73: Determine whether the price of the search for price verification result in the single adult and child way is the lowest; S74: Initiate a reservation for single adult and child to the supplier and correspondingly determine whether the reservation is successful; S75: Initiate search for price verification to multiple upstream suppliers for the remaining one adult in the single adult way; S76: Determine whether the combined price of the single adult and child price plus the single adult is the lowest; S77: If the price in S76 is the lowest, initiate a reservation for the remaining one adult to multiple upstream suppliers in the single adult way and correspondingly determine whether the reservation is successful; S78: When the judgment results of S75, S76, and S78 are negative, cancel the reservation upstream; S79: When the judgment results of S72, S73, S74, S75, S76, and S77 are negative, no longer perform order splitting; S80: After S79 no longer performs order splitting, the order is dispatched as a whole order, where the whole order way is two adults and one child; S81: When the reservation in S77 is successful, perform order splitting on the order to obtain the order splitting result.
8. The intelligent order assignment engine system based on its own price source according to claim 7, characterized in that, The order corresponding to two adults and one child is recorded as a two adults and one child order, the order corresponding to one adult and one child is recorded as a one adult and one child order, and the order corresponding to one adult in the single person way is recorded as a one adult order.
9. The intelligent order dispatching engine system based on its own price source according to claim 8, characterized in that The order splitting result is a one adult and one child order and a one adult order, and the whole order way is a two adults and one child order.