Resource allocation method, device and equipment for newly opened route and storage medium

Abstract

The invention discloses a new route resource allocation method, which comprises the steps of generating a data acquisition instruction based on an evaluation requirement of a new route, and acquiring related data from a pre-constructed knowledge base according to the data acquisition instruction; predicting passenger flow index characteristics of the newly opened route based on the collected data; determining an operation plan for the new route according to the passenger flow index characteristics; in combination with the passenger flow index characteristics and the operation plan, carrying out cost benefit evaluation on the newly opened route; according to the passenger flow index characteristics, the operation plan and the cost benefit evaluation result, carrying out resource configuration on the newly opened route; comprehensive and systematic support can be provided for decision making of the new route, and the success rate and the resource utilization efficiency of the new route are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of aviation technology, and in particular to a resource configuration method and device for a new route, an equipment and a storage medium. BACKGROUND

[0002] Under the background of the continuous development of the aviation transportation industry, the decision and operation of the new route become the key link for the airlines to expand business and improve market competitiveness.

[0003] At present, in the practice of new route value evaluation and resource configuration, the traditional method is still dominated by manual experience, relying on personal experience and subjective judgment to analyze the feasibility and value of the new route, which is difficult to fully consider numerous complex data and factors, and is easy to ignore some key information, thereby affecting the scientificity and comprehensiveness of the new route decision and resource configuration. SUMMARY

[0004] The embodiments of the present application provide a resource configuration method for a new route, which can provide comprehensive and systematic support for the decision of the new route and improve the success rate and resource utilization efficiency of the new route.

[0005] In a first aspect, the embodiments of the present application provide a resource configuration method for a new route, comprising: generating a data collection instruction based on the evaluation requirements of the new route, and collecting relevant data from a pre-constructed knowledge base according to the data collection instruction; predicting the passenger flow index characteristics of the new route based on the collected data; determining an operation plan for the new route according to the passenger flow index characteristics; conducting a cost-benefit evaluation of the new route in combination with the passenger flow index characteristics and the operation plan; conducting resource configuration for the new route according to the passenger flow index characteristics, the operation plan and the cost-benefit evaluation result.

[0006] Further, the pre-constructed database comprises: a historical route opening evaluation report knowledge base for storing historical route opening evaluation reports of different time periods and different routes; a route opening evaluation report outline knowledge base for storing a standardized outline of the route opening evaluation report, the standardized outline being used to guide the value evaluation of the new route; a route data knowledge base for storing various types of data collected from external open source platforms and internal systems that can be used for route value evaluation.

[0007] Further, the prediction of the passenger flow index characteristics of the new route based on the collected data comprises: inputting the origin and destination of the new route; collecting historical passenger flow data and city characteristic data of several historical routes of the same city as the origin or destination development type from the pre-constructed database; the historical passenger flow data includes market competition data and passenger flow statistical data, and the city characteristic data includes economic level data and industrial structure data; analyzing the correlation between the historical passenger flow data and the city characteristic data of the historical routes, applying the correlation to the new route, and outputting passenger flow index characteristics of the new route, including but not limited to passenger seat rate prediction value, passenger flow prediction value, and passenger flow fluctuation prediction value.

[0008] Further, the operation plan for the new route is determined according to the passenger flow index characteristics, including: extracting core characteristics from the passenger flow index characteristics, including passenger source type, flight distance, airport type, and seasonal fluctuation, and converting each core characteristic into a core characteristic value to obtain a passenger source type characteristic value, a flight distance characteristic value, an airport type characteristic value, and a seasonal fluctuation characteristic value; According to the core characteristic value, a candidate aircraft model that can be used for the new route is selected from all selectable aircraft models; According to the passenger flow prediction value of the new route, the seat number matching degree of each candidate aircraft model is calculated, and the optimal aircraft model is determined from the candidate aircraft models based on the seat number matching degree.

[0009] Further, the candidate aircraft model that can be used for the new route is selected from all selectable aircraft models according to the core characteristic value, including: The CRITIC method is used to determine the basic weight of each scoring dimension for aircraft model adaptability scoring; the dimensions include business adaptability, tourism branch adaptability, long-distance trunk adaptability, highland adaptability, and low-cost adaptability; The basic weight is fine-tuned according to the core characteristic value to obtain an adjusted weight; Based on the adjusted weight, the aircraft model adaptability score of each selectable aircraft model is calculated, and the candidate aircraft model that can be used for the new route is selected from the selectable aircraft models according to the aircraft model adaptability score and a pre-set aircraft model adaptability score threshold.

[0010] Further, the cost-benefit of the new route is evaluated in combination with the passenger flow index characteristics and the operation plan, including: The fuel consumption cost, crew cost, and airport landing fee corresponding to the optimal aircraft model are obtained, and the cost-benefit of the new route is evaluated in combination with the recent ticket price trend and the passenger seat rate prediction value in the passenger flow index characteristics to obtain a cost-benefit evaluation result.

[0011] Further, the method further includes: According to the passenger flow index feature, the operation plan, and the cost benefit evaluation result, score values of the new route are calculated in the strategic matching dimension, the competitive analysis dimension, the resource matching dimension, the economic feasibility dimension, and the passenger flow potential dimension. Based on the score values of each dimension and pre-determined weight values, a comprehensive opening index of the new route is calculated, the new route is evaluated according to the comprehensive opening index, and an opening evaluation report is generated.

[0012] In a second aspect, an embodiment of the present application provides a resource configuration device for a new route, comprising: A route data collection module is configured to generate a data collection instruction based on an evaluation requirement of the new route, and collect relevant data from a pre-constructed knowledge base according to the data collection instruction. A passenger flow feature prediction module is configured to predict passenger flow index features of the new route based on the collected data. A route plan arrangement module is configured to determine an operation plan for the new route according to the passenger flow index features. A cost benefit evaluation module is configured to evaluate the cost benefit of the new route in combination with the passenger flow index features and the operation plan. A route resource configuration module is configured to perform resource configuration for the new route according to the passenger flow index features, the operation plan, and the cost benefit evaluation result.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, comprising: A memory is configured to store a computer program. A processor is configured to execute the computer program. When the processor executes the computer program, the resource configuration method for a new route in any one of the first aspect is implemented.

[0014] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores a computer program, and when the computer program is executed, the resource configuration method for a new route in any one of the first aspect is implemented.

[0015] Compared with the prior art, the resource configuration method for a new route provided by the embodiment of the application has the beneficial effects that: data collection instructions are generated based on the evaluation requirements of the new route, relevant data is collected from a pre-constructed knowledge base according to the data collection instructions, passenger flow index characteristics of the new route are predicted based on the collected data, an operation plan for the new route is determined according to the passenger flow index characteristics, cost-benefit evaluation is performed on the new route in combination with the passenger flow index characteristics and the operation plan, and resource configuration is performed on the new route according to the passenger flow index characteristics, the operation plan and the cost-benefit evaluation result. The method can provide comprehensive and systematic support for the decision of the new route and improve the success rate and resource utilization efficiency of the new route. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical features of the embodiments of the application, the drawings needed to be used in the embodiments of the application will be briefly introduced as follows. Obviously, the drawings described below are only some of the embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0017] Figure 1 is a flow diagram of a resource configuration method for a new route provided by the embodiment of the application; Figure 2 is a structural diagram of a resource configuration device for a new route provided by the embodiment of the application; Figure 3 is a structural diagram of an electronic device provided by the embodiment of the application. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0019] It should be noted that although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification and claims and the above-described drawings are used to distinguish similar objects, not necessarily to describe a specific order or sequence.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to be limiting of this application.

[0021] In a first aspect, embodiments of the present application provide a resource configuration method for a new route, referring to Figure 1 FIG. 1 is a flowchart of an embodiment of a resource configuration method for a new route according to the present application.

[0022] As shown in Figure 1 the method comprises the following steps: S1: generating a data collection instruction based on the evaluation requirement of the new route, and collecting relevant data from a pre-constructed knowledge base according to the data collection instruction; S2: predicting the passenger flow index characteristics of the new route based on the collected data; S3: determining an operation plan for the new route according to the passenger flow index characteristics; S4: combining the passenger flow index characteristics and the operation plan to evaluate the cost-effectiveness of the new route; S5: configuring resources for the new route according to the passenger flow index characteristics, the operation plan, and the cost-effectiveness evaluation result.

[0023] In a specific implementation, according to the evaluation requirement of the new route, the type and range of data to be collected are determined, a data collection instruction is generated, the evaluation requirement can be a user input requirement or a default requirement, relevant data is collected from a pre-constructed knowledge base according to the data collection instruction, the passenger flow index characteristics of the new route are predicted based on the collected data, an operation plan for the new route is determined according to the predicted passenger flow index characteristics, the cost-effectiveness of the new route is evaluated in combination with the passenger flow index characteristics and the operation plan, the resources required by the new route, including aircraft, crew, ground service personnel, and aviation materials, are analyzed according to the passenger flow index characteristics, the operation plan, and the cost-effectiveness evaluation result, the required resources are allocated from the resource pool of the airline according to the result of the resource requirement analysis, and the use of the resources and the operation efficiency of the route are continuously monitored, the resource configuration is optimized and adjusted according to the actual situation to improve the resource utilization efficiency.

[0024] In summary, the application provides comprehensive and systematic support for the decision of new route by a series of scientific steps such as data collection, passenger flow prediction, operation plan making, cost benefit evaluation and resource allocation, improves the scientificity and accuracy of the decision, comprehensively considers market, operation, cost and other factors, can accurately grasp the market potential and operation feasibility of the new route, provides all-round reference for the airline route planning and resource allocation, and is suitable for different types of new route evaluation and resource allocation, and can help the airlines to improve the success rate and operation benefit of the new route.

[0025] In an optional embodiment, the pre-constructed database comprises: a historical route opening evaluation report knowledge base for storing historical route opening evaluation reports of different time periods and different routes; a route opening evaluation report outline knowledge base for storing a standardized outline of the route opening evaluation report, the standardized outline being used to guide the value evaluation of the new route; a route data knowledge base for storing various data collected from external open source platforms and internal systems and available for route value evaluation.

[0026] Specifically, the knowledge base provides a solid data foundation and knowledge reserve for the passenger flow index prediction, operation plan making, cost benefit evaluation and resource allocation of the new route by integrating multi-source data and knowledge, and the embodiment constructs three key knowledge bases, namely the historical route opening evaluation report knowledge base, the route opening evaluation report outline knowledge base and the route data knowledge base.

[0027] The historical departure evaluation report knowledge base is used to store historical departure evaluation reports of different time periods and different routes. First, a variety of channels are used to extensively search for past departure evaluation reports in the aviation industry. These reports cover evaluation information of different periods and different routes. For example, reports can be obtained from the internal archives of airlines, industry research institutions, and professional databases. The collected departure evaluation reports are batch uploaded to the HiAgent platform knowledge base, and the integrity and accuracy of the reports are ensured during the uploading process. The reports are numbered and classified for management, so as to facilitate subsequent retrieval and use. The large model is used to deeply learn the departure evaluation reports uploaded to the knowledge base. Natural language processing technology is used to automatically identify common structured elements in the reports, such as background, problem, method, analysis, conclusion, and suggestion. The logical association rules between these elements are analyzed, and the standard usage of professional terms, formal and objective writing style, and data reference format in the reports are learned, so as to improve the professionalism and standardization of subsequent generated content. For example, taking a past evaluation report on the "Chengdu-Shenzhen" route as an example, the report analyzes the close economic ties between the two cities in detail, such as trade volume data of the electronic information industry. The large model learns this analysis method and data usage skill, and when evaluating a new route, if a similar economic structure between cities is encountered, the model can accurately draw on this mode to provide a reference for judging the economic and trade relations of the route.

[0028] The departure evaluation report outline knowledge base is used to store standardized outlines of departure evaluation reports. The standardized outlines are developed by professional evaluators and industry experts, taking into account various aspects required for the evaluation of new routes. The outlines are general and guiding, such as including an introduction, city profiles and economic and trade conditions, aviation market analysis, flight revenue prediction and schedule planning, and summary. Each part has specific content requirements. The developed standardized default outline is uploaded to the knowledge base. In actual route evaluation, if there is no special format requirement, the system will automatically call the default outline. This fixed evaluation framework can effectively reduce invalid data retrieval, constrain the output structure of the large model, and improve the efficiency and stability of the system. Introduction (not more than 200 words): Mention the Civil Aviation Administration planning; strategic positioning upgrade of A or B city airport; hub construction goal of airlines (such as XX airline) in A or B city area; strategic significance and expected goal of opening A city-B city route.

[0029] City profiles and economic and trade conditions: City profiles include geographical location, population, economic structure, and cultural characteristics; economic and trade conditions include bilateral relations, trade data, tourism cooperation, and distribution of Chinese enterprises.

[0030] Air market analysis: destination city airport profile including destination city airport location, operation, route network; air rights situation including business rights opening, route network flexibility; competition situation including existing transfer flight situation, main competitors; passenger volume prediction including OD volume present situation and growth trend; market off-season analysis including passenger flow seasonality distribution; SWOT analysis including strengths, weaknesses, opportunities, threats.

[0031] Flight revenue prediction and schedule planning: flight plan including flight time, aircraft selection, schedule arrangement; operating efficiency analysis including cost estimation, fare strategy, government subsidies; marketing strategy including revenue plan, sales plan, market promotion measures.

[0032] Summary (not more than 200 words): strategic significance of opening A city-B city route; market potential and competitive advantage; promoting effect on A city hub construction of the airline; specific suggestions (such as flight time, aircraft selection, schedule arrangement).

[0033] Route data knowledge base, used to store various data collected from external open source platforms and internal systems that can be used for route value assessment, such as data related to routes collected from external open source platforms such as civil aviation resources network, ministry of foreign affairs of the people's republic of China, customs, national bureau of statistics, international business department, and internal systems such as OAG flight schedule, DDS market insight, NRS passenger volume and prediction, etc. These internal system data can provide more detailed and accurate route operation information such as flight departure and arrival time, frequency, passenger volume, etc. The collected external data and internal data are structured and purified, redundant descriptions are removed, and key decision factors for route value assessment are extracted, such as geography, population, tourism, trade, flight schedule, market dynamics, passenger volume, etc. These factors are converted into standard format.

[0034] This embodiment constructs a comprehensive, systematic and scientific multi-source knowledge base, which provides rich data and knowledge support for the evaluation and resource allocation of new routes, and helps airlines make more reasonable and forward-looking strategic decisions.

[0035] In an optional implementation, the method further comprises: inputting the origin and destination of the new route; collecting historical passenger flow data and city characteristic data of several historical routes of cities with the same development type as the origin or destination from the pre-constructed database; the historical passenger flow data includes market competition data and passenger flow statistical data, and the city characteristic data includes economic level data and industrial structure data; Analyze the correlation between historical passenger flow data and urban characteristic data of the historical routes, apply the correlation to the newly opened routes, and output the passenger flow index characteristics of the newly opened routes, including but not limited to the predicted load factor, predicted passenger volume, and predicted passenger flow fluctuation.

[0036] Specifically, the system inputs the origin and destination of the newly opened route. It then collects historical passenger flow data and city characteristic data from a pre-built database for several historical routes in cities with similar development types to the origin or destination. Historical passenger flow data includes market competition data (such as flight frequency and fare strategies of other airlines on the route) and passenger flow statistics (such as actual passenger volume and load factor on the route over the past few years). City characteristic data includes economic level data and industrial structure data. The system identifies core predictive indicators, constructs a predictive framework integrating multi-source data, and conducts in-depth analysis of passenger flow growth trends and patterns on similar historical routes. For example, a newly opened air route originates from city A and terminates at city B. City A has experienced rapid economic development recently, with its industrial structure shifting towards high-end service industries. City C is also an economically developed city like City A. Studying the passenger flow changes on the City C-City B route over the past few years reveals that with the rapid development of the internet economy in City C, the business passenger flow on this route has shown a year-on-year upward trend. Combining this with the booming development of the internet economy in City A in recent years and the rise of a large number of internet companies, and referring to passenger volume change data for similar city routes such as the City C-City B route, it can be concluded that the newly opened air route from City A to City B may see a significant increase in business passengers.

[0037] Based on the above analysis, the passenger flow characteristics of the newly opened routes are output, including but not limited to the predicted load factor, predicted passenger volume, and predicted passenger flow fluctuation.

[0038] This embodiment, by integrating historical passenger flow data and city characteristic data, can more comprehensively and accurately reflect the market potential and demand characteristics of newly opened routes, providing a scientific basis for airlines in route planning, resource allocation and marketing strategy formulation, and has significant economic and social benefits.

[0039] In one optional implementation, determining the operational plan for the newly opened route based on the passenger flow indicator characteristics includes: The core features are extracted from the passenger flow index features, including passenger source type, flight length, airport type and seasonal fluctuations. Each of the core features is converted into a core feature value to obtain passenger source type feature value, flight length feature value, airport type feature value and seasonal fluctuation feature value. Based on the core feature values, candidate aircraft models suitable for new routes are selected from all available aircraft models; Based on the passenger flow forecast for the new route, the seat number matching degree of each candidate aircraft type is calculated, and the optimal aircraft type is determined from the candidate aircraft types based on the seat number matching degree.

[0040] Specifically, core features are extracted from passenger flow indicators, including passenger source type, flight length, airport type, and seasonal fluctuations. Each of these core features is then converted into a core feature value, resulting in passenger source type feature value, flight length feature value, airport type feature value, and seasonal fluctuation feature value. The quantification rules for the core feature values ​​are as follows: Customer type (F1): Clearly distinguish between three categories: tourism, business and leisure, and mixed. Based on the attributes of the destination city of the route, the categories are: tourism (3-5 points), business and leisure (8-10 points), and mixed (6-7 points). Flight distance (F2): A continuous variable, using actual flight distance values ​​(L, in km), determined based on flight distance data from the past 3 years of operating routes, to determine the historical minimum flight distance (L). min ) and maximum range (L max ), calculated using the min-max normalization formula: F2 = 1 + 9 × (L - L) min ) / (L max - L min (Ensure the result is in the range of 1-10 points); Airport type (F3): High-altitude / high-temperature airports (6-8 points): Altitude ≥ 2500m or extreme summer temperature ≥ 35℃; Hub airport (8-10 points): Annual passenger throughput ≥ 30 million; Regional airports (3-5 points): Annual passenger throughput <10 million; Seasonal fluctuations (F4): Obtaining peak season passenger flow (Q) from historical passenger flow data v ) and off-season passenger flow (Q s ), calculate the fluctuation ratio R2=Q v / Q s The quantification formula is as follows: When 5≥R2≥2, F4=8+2×(R2-2) / 3 (maximum 10 points); When 1.2 ≤ R2 < 2, F4 = 5 + 2 × (R2 - 1.2) / 0.8; When 1≤R2<1.2, F4=3+1×(R2-1) / 0.2 (minimum 3 points).

[0041] Based on core feature values, candidate aircraft models suitable for new routes are selected from all available aircraft types. The seat capacity matching degree for each candidate aircraft model is calculated based on the predicted passenger flow for the new routes, using the following formula: Seat matching degree M = (Forecasted passenger flow / Standard number of seats for aircraft type) × 100%; The optimal aircraft model is determined from the candidate aircraft models based on the seat number matching degree. For example, an aircraft model with 60%≤M≤120% can be selected as the optimal aircraft model.

[0042] Furthermore, flight schedules are dynamically adjusted based on factors such as passenger flow characteristics, airport capacity, and competitor schedules. The dynamic adjustment rules are built around dimensions such as demand-driven approaches, resource adaptation, technical support, and conflict resolution. Through the dynamic linkage of multiple factors, the optimal iteration of the flight schedule plan is achieved. The adjustment rules are explained below: 1. Passenger Flow Characteristics Drive Schedule Distribution (Passenger flow characteristics are the primary basis for schedule adjustments; through passenger segmentation and traffic pattern analysis, precise matching of schedule supply and travel demand can be achieved): Segmented and adapted to different customer types: Business-oriented routes focus on flights from Monday to Friday, with 2-3 flights per day during peak hours (8:00 AM and 6:00 PM) to cover business travel needs; while tourism-oriented routes increase the frequency of flights on weekends (Saturday / Sunday), accounting for more than 50% of the total weekly flights, to match the travel rhythm of tourists. Quantitative control of daily passenger flow fluctuations: Extract data from the same routes over the past two years to calculate the "daily passenger flow ratio index" and trigger flight adjustments. For business routes, if the passenger flow ratio index on Monday / Friday is ≥1.2 (i.e., the demand on that day is 20% higher than the daily average), then the number of flights on those two days will be increased by 20%. For tourist routes, if the passenger flow ratio index on Saturday / Sunday is ≥1.3, the weekend flight priority guarantee mechanism will be activated, prioritizing the allocation of resources such as time slots and crew to weekends.

[0043] 2. Refined utilization of slot resources (slot resources are a scarce resource in aviation operations and need to be dynamically optimized in combination with airport capacity constraints and market competition patterns. Professional data platforms such as OAG provide core support for this): Airport capacity adaptation rules: Hub airports have a peak hour capacity of approximately 30 flights. The peak hours for takeoffs and landings are from 8:00 AM to 10:00 AM and from 4:00 PM to 6:00 PM. When adjusting flight schedules, priority should be given to available windows such as 12:00 PM to 2:00 PM or 8:00 PM to 10:00 PM. At the same time, it is necessary to comply with the Civil Aviation Administration's priority rules for coordinating airport slot allocation. Feeder airports have an average of ≤10 available slots per day. Priority should be given to locking in off-peak hours before 9:00 AM (to avoid concentrated takeoffs and landings of daytime tour groups) or after 3:00 PM (to connect with connecting flights at hub airports) to ensure slot approval rate and on-time rate.

[0044] Strategic avoidance of competitor schedules: Analyze the layout of competitors on the same route. If the overlap rate of the schedule with the competitor is ≥60% (e.g., competitors are concentrated in the morning), then adjust the company's schedules to the off-peak hours (e.g., 2 pm) to reduce direct competition. If the competitor's average daily number of flights is ≤2 (insufficient market supply), then increase the company's number of flights to 3-4 to form a high-frequency, high-density capacity advantage.

[0045] 3. Aircraft performance constraints (the performance parameters and maintenance requirements of the aircraft directly determine the feasibility of the shift schedule, and a rigid constraint mechanism of "performance adaptation + maintenance guarantee" needs to be established): Shift planning based on turnaround efficiency: Narrow-body aircraft (such as A320neo) can be used for 10-12 hours per day. If the turnaround time per shift is ≤4 hours, a "A-B-A-B" tandem flight pattern can be arranged to maximize the daily utilization rate. Wide-body aircraft (such as A330-200) can be used for 12-14 hours per day. However, since the turnaround time per shift is ≥6 hours, a maximum of 1 shift can be arranged per day to avoid crew overtime and equipment fatigue.

[0046] Mandatory maintenance window reservation: Strictly follow the manufacturer's maintenance standards and embed maintenance periods into the flight schedule to avoid continuous high-intensity flight operations that could lead to an increase in failure rate.

[0047] 4. In-depth application of OAG data (As a leading global aviation data service provider, OAG's data is integrated throughout the entire process of demand analysis, competitive assessment, and execution monitoring for flight schedule adjustments, serving as the core technical support for rule implementation): By using OAG's flight schedule database, the system can query the flight distribution of competitors on the same route in real time and calculate the "flight overlap rate" (flights at the same time as competitors / total flights). If the overlap rate is too high, the time slot avoidance rule is triggered. If the competitor's capacity is insufficient, the density advantage strategy is activated.

[0048] 5. Resource conflict resolution (When there is a shortage of core resources such as aircraft and crew, standardized alternative solutions are activated to ensure that flight schedules are not interrupted): To address insufficient aircraft resources, a combination of "suboptimal aircraft replacement + flight compensation" will be adopted. Priority will be given to alternative aircraft with a score difference of ≤1 from the optimal aircraft. Flights will be increased according to the formula "flight adjustment coefficient = number of seats in the optimal aircraft / number of seats in the suboptimal aircraft". For example, if the optimal aircraft has 180 seats and the suboptimal aircraft has 150 seats, the adjustment coefficient will be 1.2, and 20% more flights will be needed to make up for the capacity gap. Addressing insufficient crew resources: Based on the Civil Aviation Administration's regulations on crew duty hours, a tiered allocation strategy is adopted, prioritizing the allocation of crews with a monthly duty hour balance of ≥20 hours to avoid overtime. A "connecting flights + stopover rest" model is adopted, such as reserving 2 hours of stopover rest time at airport B when a crew is flying the "A-B-C" connecting flight route.

[0049] This embodiment can accurately select the optimal aircraft type by extracting and quantifying the core features of the route. At the same time, it can dynamically adjust the flight schedule based on factors such as passenger flow characteristics, airport capacity, and competitor slots, thus realizing the scientific formulation and efficient operation of the new route operation plan.

[0050] In one optional implementation, the step of selecting candidate aircraft models suitable for new routes from all available aircraft models based on the core feature value includes: The CRITIC method was used to determine the basic weights of each scoring dimension for aircraft compatibility; the dimensions include business and official business compatibility, tourism and feeder route compatibility, long-haul trunk route compatibility, high-altitude compatibility, and low-cost compatibility. The basic weights are fine-tuned based on the core feature values ​​to obtain the adjusted weights; Based on the adjusted weights, the aircraft suitability score of each available aircraft type is calculated. Based on the aircraft suitability score and the pre-set aircraft suitability score threshold, candidate aircraft types that can be used for new routes are selected from the available aircraft types.

[0051] Specifically, first determine the scoring dimensions and specific scoring methods for each model, as shown below: 1. Business and public sector suitability (D1): D1 = 1 + 9 × (0.4 × a + 0.3 × b + 0.3 × c); Where, a = actual proportion of business and first class / 15% (maximum value is 1; if the actual proportion of business and first class is 18%, then a = 1.2, take 1), b = actual cabin width / 3.5m (maximum value is 1; if the actual cabin width is 3.6m, then b = 1.03, take 1), c = actual seat pitch / 34 inches (maximum value is 1; if the actual seat pitch is 35 inches, then c = 1.03, take 1).

[0052] 2. Adaptability of tourist branch lines (D2): D2 = 1 + 9 × (0.3 × d + 0.4 × e + 0.3 × f); Where d = 1 - |actual passenger capacity - 125| / 125, e = 2000m / actual runway demand (maximum value is 1, if the actual runway demand is 1800m, then e = 1.11, take 1), f = actual turnover times / 4 times (maximum value is 1, if the actual turnover times are 5 times, then f = 1.25, take 1).

[0053] 3. Long-distance trunk line adaptability (D3): D3 = 1 + 9 × (0.4 × g + 0.3 × h + 0.3 × i); Where g = actual range / 6000km (maximum value is 1, for example, if the actual range is 6500km, then g = 1.08, take 1), h = actual endurance / 8 hours (maximum value is 1, for example, if the actual endurance is 9 hours, then h = 1.125, take 1), i = actual cruising speed / 850km / h (maximum value is 1, for example, if the actual cruising speed is 860km / h, then i = 1.01, take 1).

[0054] 4. High-altitude adaptability (D4): D4 = 1 + 9 × (0.3 × j + 0.3 × k + 0.4 × l); Where, j = actual thrust / 30000 lbs (maximum value is 1, such as j = 1.07 if the actual thrust is 32000 lbs, take 1), k = 1 - actual load reduction rate / 5% (maximum value is 1, such as k = 0.4 if the actual load reduction rate is 3%), L = 1 (capable of taking off and landing at full weight on plateau) or 0.5 (not capable of taking off and landing at full weight on plateau).

[0055] 5. Low-cost adaptability (D5): D5 = 1 + 9 × (0.3 × m + 0.3 × n + 0.4 × p); Where m is the fuel consumption compliance rate, n is the maintenance cost compliance rate, and p is the single-seat cost compliance rate.

[0056] Furthermore, the CRITIC method was used to determine the basic weights of each scoring dimension. Three to five historical routes of the company with characteristics similar to the newly opened routes were selected, and historical scoring data for the five dimensions were extracted. A scoring matrix of 10 aircraft types × 5 dimensions was constructed, and the standard deviation σ was used to determine the weights. j Quantifying data fluctuations across various dimensions: ; Where n=10 represents the number of aircraft models. Let i be the score of model i in dimension j. This represents the average score for all models in dimension j.

[0057] The correlation between dimensions is quantified using the Pearson correlation coefficient, and the conflict index r is calculated. j : ; in, For the conflict index of the j-th dimension, The Pearson correlation coefficient between dimension j and dimension k, with values ​​ranging from... A value between 1 and 1 is used to measure the degree of linear correlation between two dimensions.

[0058] The information content is calculated based on the standard deviation and conflict index. The greater the information content, the more important that dimension may be in the overall evaluation. ; in, Let be the information content of the j-th dimension.

[0059] Finally, the basic weights of each dimension are calculated based on the amount of information. The information content of each dimension is then normalized to obtain the weight of each dimension in the overall evaluation. ; in, represents the base weight of the j-th dimension.

[0060] The calculated base weights are fine-tuned based on the core feature values ​​of the newly opened routes to obtain the adjusted weights, ensuring that the sum of the corrected weights for each dimension is 1. The fine-tuning formula is as follows: ; in, The weights are adjusted for the j-th dimension. For dimension Associated route feature values.

[0061] For each available model, calculate its model compatibility score: ; in, Rate the compatibility of the optional model i. Let i be the score of model i in dimension j. The weight is adjusted for the j-th dimension.

[0062] Finally, aircraft models with a model compatibility score greater than the preset model compatibility score threshold are selected as candidate aircraft models that can be used for new routes.

[0063] In one optional implementation, the step of combining the passenger flow characteristics and the operational plan to conduct a cost-benefit assessment of the newly opened route includes: By obtaining the fuel consumption cost, crew cost, and airport landing fee corresponding to the optimal aircraft type, and combining the recent ticket price trend and the load factor prediction value in the passenger flow indicator characteristics, a cost-benefit assessment is conducted on the newly opened route to obtain the cost-benefit assessment results.

[0064] Specifically, based on the airport landing and takeoff fees corresponding to OAG flight times, oil price fluctuation data from DDS market insights, and the fuel consumption characteristics of the optimal aircraft type, fuel consumption costs are automatically calculated. Based on the crew staffing standards and compensation system for the aircraft type, combined with flight frequency and flight time in the operational plan, crew compensation costs are calculated. According to the airport landing and takeoff fees corresponding to OAG flight times, and considering factors such as the number of takeoffs and landings and aircraft type, airport landing and takeoff fees are accurately calculated. Combined with fare strategies and the load factor forecast from previously predicted passenger flow indicators, a revenue plan is generated.

[0065] By integrating the results of cost calculations and revenue planning, a cost-benefit assessment is conducted on the new route to determine its cost-effectiveness.

[0066] In one optional implementation, the method further includes: Based on the passenger flow characteristics, the operation plan, and the cost-benefit assessment results, calculate the scores of the new routes in the dimensions of strategic matching, competitive analysis, resource matching, economic feasibility, and passenger flow potential. Based on the scores of each dimension and the predetermined weight values, the comprehensive opening index of the new route is calculated. The new route is evaluated based on the comprehensive opening index, and an opening evaluation report is generated.

[0067] Specifically, a quantitative evaluation system is constructed, comprising five primary indicators: strategic alignment, competitive analysis, resource matching, economic feasibility, and customer traffic potential. Each primary indicator has several sub-items, with corresponding weight values ​​determined. The weights of each indicator are determined using the analytic hierarchy process combined with industry expert experience. The dimensions and their corresponding weights are as follows: 1. Strategic Alignment Dimension (Weight 20%) Hub Coordination (weight 65%): Scoring is based on whether the departure or destination of the route includes Guangzhou, Beijing, or Urumqi. If it does, 10 points are awarded; if not, 1 point is awarded.

[0068] Policy Coordination (Weight 35%): Assess whether the route aligns with the "Belt and Road" initiative, free trade zone policies, or receives government subsidies, and classify it as highly aligned (9 points), moderately aligned (7 points), generally aligned (5 points), poorly aligned (3 points), and basically not aligned (1 point).

[0069] Strategic alignment score = (hub coordination score × 65% + policy coordination score × 35%) × 20%.

[0070] 2. Competitiveness Analysis Dimension (Weight 15%) Number of competitors (weight 30%): This is calculated based on the number of existing operating airlines. If there are fewer than 2, you get 10 points. For each additional airline, you lose 2 points.

[0071] Market share potential (weight 35%): The estimated market share that the company can seize. 10 points for greater than 35%, 8 points for 30% - 35%, 6 points for 25% - 30%, 4 points for 20% - 25%, 2 points for 15% - 20%, and 1 point for less than 15%.

[0072] Price war risk (weight 35%): Assess the risk of competitors lowering prices to suppress prices. No risk: 10 points; low risk: 8 points; medium risk: 6 points; high risk: 1 point.

[0073] The overall competitive analysis score is calculated as follows: (Competitor number score × 30% + Market share potential score × 35% + Price war risk score × 35%) × 15%.

[0074] 3. Resource matching dimension (weight 5%) Aircraft compatibility (weight 60%): Assess whether there is an aircraft model with matching range and passenger / cargo capacity. If yes, get 10 points; otherwise, get 1 point.

[0075] Human Resources and Support (Weight 40%): Analyze the adequacy of resources such as crew, ground support, and maintenance. 10 points are awarded if no new resources are needed, and 1 point is awarded if a large number of external hires are required.

[0076] The overall score for resource matching is calculated as follows: (Aircraft adaptability score × 60% + Human resources and support score × 40%) × 5%.

[0077] 4. Economic feasibility dimension (weight 30%) Cost per seat (weight 40%): Compare the estimated cost per seat with the industry average. 10 points are awarded if the cost is 20% lower than the average, 1 point if it is higher than the average, and 5 points if there is no data.

[0078] Expected occupancy rate (weight 60%): scored by range, below 60% gets 0 points, 60% - 70% gets 2 points, 70% - 78% gets 4 points, 78% - 85% gets 6 points, 85% - 93% gets 8 points, 93% and above gets 10 points, no data gets 5 points.

[0079] Economic feasibility score = (single seat cost score × 40% + expected occupancy rate score × 60%) × 30%.

[0080] 5. Potential for customer traffic (weight 30%) Potential passenger volume (weight 60%): Based on population, economic and tourism data, predict daily demand. More than 2,000 passengers get 10 points, less than 100 passengers get 1 point.

[0081] Demand stability (weight 22%): Assess seasonal or event-driven fluctuations, with 10 points for stability and 1 point for extreme fluctuations.

[0082] Transit demand percentage (weight 18%): Statistical hub transit dependence, greater than 40% gets 10 points, pure point-to-point gets 5 points.

[0083] Passenger flow potential comprehensive score = (potential passenger volume score × 60% + demand stability score × 22% + transit demand ratio score × 18%) × 30%.

[0084] The comprehensive scores of the above dimensions are added together to obtain the comprehensive opening index of the new route. The new route is evaluated based on the comprehensive opening index, and an opening evaluation report is generated. The report includes the scores of each dimension, the comprehensive opening index, and the corresponding evaluation conclusions and recommendations.

[0085] This embodiment constructs a quantitative evaluation system that includes five primary indicators and multiple sub-items. It comprehensively considers factors such as strategy, competition, resources, economy, and passenger flow, making the evaluation results more comprehensive and accurate. By calculating the comprehensive launch index, it realizes the quantitative rating of route value, providing an intuitive and scientific basis for airlines to make decisions on opening new routes. This helps airlines to rationally plan their route networks and improve operational efficiency.

[0086] Secondly, embodiments of the present invention provide a resource allocation device for newly opened air routes, see [link to relevant documentation]. Figure 2 This is a schematic diagram of one embodiment of a resource allocation device for newly opened air routes provided by the present invention.

[0087] like Figure 2 As shown, the device includes: The route data acquisition module 21 is used to generate data acquisition instructions based on the evaluation requirements of newly opened routes, and to collect relevant data from a pre-built knowledge base according to the data acquisition instructions. Passenger flow characteristic prediction module 22 is used to predict the passenger flow indicator characteristics of newly opened routes based on the collected data; The route planning and scheduling module 23 is used to determine the operation plan for the newly opened route based on the passenger flow index characteristics. Cost-benefit assessment module 24 is used to conduct a cost-benefit assessment of the newly opened route by combining the passenger flow indicator characteristics and the operation plan; The route resource allocation module 25 is used to allocate resources for the newly opened route based on the passenger flow index characteristics, the operation plan, and the cost-benefit evaluation results.

[0088] In one alternative implementation, the pre-built database includes: A knowledge base for historical flight launch assessment reports, used to store historical flight launch assessment reports for different time periods and routes; A knowledge base for the opening assessment report outline is used to store standardized outlines for opening assessment reports, which are used to guide the value assessment of new routes. The route data knowledge base is used to store various types of data collected from external open-source platforms and internal systems that can be used for route value assessment.

[0089] In one optional implementation, the step of predicting passenger flow characteristics of newly opened air routes based on collected data includes: Enter the origin and destination of the newly opened route; Historical passenger flow data and city characteristic data of several historical routes from cities with the same development type as the origin or destination are collected from the pre-built database; the historical passenger flow data includes market competition data and passenger flow statistics, and the city characteristic data includes economic level data and industrial structure data. Analyze the correlation between historical passenger flow data and urban characteristic data of the historical routes, apply the correlation to the newly opened routes, and output the passenger flow index characteristics of the newly opened routes, including but not limited to the predicted load factor, predicted passenger volume, and predicted passenger flow fluctuation.

[0090] In one optional implementation, determining the operational plan for the newly opened route based on the passenger flow indicator characteristics includes: The core features are extracted from the passenger flow index features, including passenger source type, flight length, airport type and seasonal fluctuations. Each of the core features is converted into a core feature value to obtain passenger source type feature value, flight length feature value, airport type feature value and seasonal fluctuation feature value. Based on the core feature values, candidate aircraft models suitable for new routes are selected from all available aircraft models; Based on the passenger flow forecast for the new route, the seat number matching degree of each candidate aircraft type is calculated, and the optimal aircraft type is determined from the candidate aircraft types based on the seat number matching degree.

[0091] In one optional implementation, the step of selecting candidate aircraft models suitable for new routes from all available aircraft models based on the core feature value includes: The CRITIC method was used to determine the basic weights of each scoring dimension for aircraft compatibility; the dimensions include business and official business compatibility, tourism and feeder route compatibility, long-haul trunk route compatibility, high-altitude compatibility, and low-cost compatibility. The basic weights are fine-tuned based on the core feature values ​​to obtain the adjusted weights; Based on the adjusted weights, the aircraft suitability score of each available aircraft type is calculated. Based on the aircraft suitability score and the pre-set aircraft suitability score threshold, candidate aircraft types that can be used for new routes are selected from the available aircraft types.

[0092] In one optional implementation, the step of combining the passenger flow characteristics and the operational plan to conduct a cost-benefit assessment of the newly opened route includes: By obtaining the fuel consumption cost, crew cost, and airport landing fee corresponding to the optimal aircraft type, and combining the recent ticket price trend and the load factor prediction value in the passenger flow indicator characteristics, a cost-benefit assessment is conducted on the newly opened route to obtain the cost-benefit assessment results.

[0093] In an optional embodiment, the device is further configured to: Based on the passenger flow characteristics, the operation plan, and the cost-benefit assessment results, calculate the scores of the new routes in the dimensions of strategic matching, competitive analysis, resource matching, economic feasibility, and passenger flow potential. Based on the scores of each dimension and the predetermined weight values, the comprehensive opening index of the new route is calculated. The new route is evaluated based on the comprehensive opening index, and an opening evaluation report is generated.

[0094] Thirdly, embodiments of the present invention provide an electronic device, see [link to previous document]. Figure 3 The diagram shown is a structural schematic of an electronic device provided in an embodiment of the present invention.

[0095] like Figure 3 As shown, the device includes: Memory 31 is used to store computer programs; Processor 32 is used to execute the computer program; When the processor 32 executes the computer program, it implements the resource allocation method for opening new routes as described in any of the above embodiments.

[0096] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 31 and executed by the processor 32 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0097] The processor 32 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0098] The memory 31 can be used to store the computer programs and / or modules. The processor 32 implements various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory 31 and calling the data stored in the memory 31. The memory 31 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 31 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0099] It should be noted that the aforementioned electronic devices include, but are not limited to, processors and memory, as will be understood by those skilled in the art. Figure 3 The structural diagram is merely an example of the electronic device described above and does not constitute a limitation on the electronic device. It may include more components than shown in the diagram, or combine certain components, or use different components.

[0100] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed, implements the resource allocation method for opening new air routes as described in any of the above embodiments.

[0101] It should be understood that the implementation of all or part of the process in the above-mentioned resource allocation method for newly opened air routes can also be accomplished by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the above-mentioned resource allocation method for newly opened air routes. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0102] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. It should be noted that, for those skilled in the art, several equivalent obvious modifications and / or equivalent substitutions can be made without departing from the technical principles of the present invention, and these obvious modifications and / or equivalent substitutions should also be considered within the scope of protection of the present invention.

Claims

1. A resource allocation method for newly opened air routes, characterized in that, include: Data collection instructions are generated based on the evaluation requirements of newly opened routes, and relevant data is collected from a pre-built knowledge base according to the data collection instructions. Predict passenger flow characteristics for newly opened routes based on collected data; Based on the passenger flow characteristics, determine the operational plan for the newly opened route; A cost-benefit assessment of the newly opened route is conducted by combining the passenger flow characteristics and the operation plan. Based on the passenger flow characteristics, the operation plan, and the cost-benefit assessment results, resources are allocated for the newly opened routes.

2. The resource allocation method for newly opened air routes as described in claim 1, characterized in that, The pre-built database includes: A knowledge base for historical flight launch assessment reports, used to store historical flight launch assessment reports for different time periods and routes; A knowledge base for the opening assessment report outline is used to store standardized outlines for opening assessment reports, which are used to guide the value assessment of new routes. The route data knowledge base is used to store various types of data collected from external open-source platforms and internal systems that can be used for route value assessment.

3. The resource allocation method for newly opened air routes as described in claim 1, characterized in that, The passenger flow characteristics predicted based on the collected data for newly opened air routes include: Enter the origin and destination of the newly opened route; Historical passenger flow data and city characteristic data of several historical routes from cities with the same development type as the origin or destination are collected from the pre-built database; the historical passenger flow data includes market competition data and passenger flow statistics, and the city characteristic data includes economic level data and industrial structure data. Analyze the correlation between historical passenger flow data and urban characteristic data of the historical routes, apply the correlation to the newly opened routes, and output the passenger flow index characteristics of the newly opened routes, including but not limited to the predicted load factor, predicted passenger volume, and predicted passenger flow fluctuation.

4. The resource allocation method for newly opened air routes as described in claim 1, characterized in that, The step of determining the operational plan for the newly opened route based on the passenger flow characteristics includes: The core features are extracted from the passenger flow index features, including passenger source type, flight length, airport type and seasonal fluctuations. Each of the core features is converted into a core feature value to obtain passenger source type feature value, flight length feature value, airport type feature value and seasonal fluctuation feature value. Based on the core feature values, candidate aircraft models suitable for new routes are selected from all available aircraft models; Based on the passenger flow forecast for the new route, the seat number matching degree of each candidate aircraft type is calculated, and the optimal aircraft type is determined from the candidate aircraft types based on the seat number matching degree.

5. The resource allocation method for newly opened air routes as described in claim 4, characterized in that, The process of selecting candidate aircraft models suitable for new routes from all available aircraft models based on the core feature values ​​includes: The CRITIC method was used to determine the basic weights of each scoring dimension for aircraft compatibility; the dimensions include business and official business compatibility, tourism and feeder route compatibility, long-haul trunk route compatibility, high-altitude compatibility, and low-cost compatibility. The basic weights are fine-tuned based on the core feature values ​​to obtain the adjusted weights; Based on the adjusted weights, the aircraft suitability score of each available aircraft type is calculated. Based on the aircraft suitability score and the pre-set aircraft suitability score threshold, candidate aircraft types that can be used for new routes are selected from the available aircraft types.

6. The resource allocation method for newly opened air routes as described in claim 4, characterized in that, The cost-benefit assessment of the newly opened route, combining the passenger flow characteristics and the operational plan, includes: By obtaining the fuel consumption cost, crew cost, and airport landing fee corresponding to the optimal aircraft type, and combining the recent ticket price trend and the load factor prediction value in the passenger flow indicator characteristics, a cost-benefit assessment is conducted on the newly opened route to obtain the cost-benefit assessment results.

7. The resource allocation method for newly opened air routes as described in claim 1, characterized in that, The method further includes: Based on the passenger flow characteristics, the operation plan, and the cost-benefit assessment results, calculate the scores of the new routes in the dimensions of strategic matching, competitive analysis, resource matching, economic feasibility, and passenger flow potential. Based on the scores of each dimension and the predetermined weight values, a comprehensive opening index for the new route is calculated. The new route is then evaluated based on the comprehensive opening index, and an opening evaluation report is generated.

8. A resource allocation device for newly opened air routes, characterized in that, include: The route data acquisition module is used to generate data acquisition instructions based on the evaluation requirements of newly opened routes, and to collect relevant data from a pre-built knowledge base according to the data acquisition instructions. The passenger flow characteristic prediction module is used to predict the passenger flow characteristics of newly opened routes based on the collected data. The route planning and scheduling module is used to determine the operation plan for the newly opened route based on the passenger flow index characteristics. The cost-benefit assessment module is used to conduct a cost-benefit assessment of the newly opened route by combining the passenger flow indicator characteristics and the operation plan. The route resource allocation module is used to allocate resources for the newly opened routes based on the passenger flow characteristics, the operation plan, and the cost-benefit evaluation results.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program; Wherein, when the processor executes the computer program, it implements the resource allocation method for newly opened routes as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, implements the resource allocation method for opening new routes as described in any one of claims 1 to 7.

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