CN112734315B

CN112734315B - Aviation network planning method, aviation network planning equipment and storage medium

Info

Publication number: CN112734315B
Application number: CN201910973995.2A
Authority: CN
Inventors: 王艺之; 柯俞嘉; 赵玲; 文灿; 李玮萱; 殷皓; 王永伟
Original assignee: SF Technology Co Ltd
Current assignee: SF Technology Co Ltd
Priority date: 2019-10-14
Filing date: 2019-10-14
Publication date: 2023-04-07
Anticipated expiration: 2039-10-14
Also published as: CN112734315A

Abstract

The embodiment of the application discloses an aviation network planning method, aviation network planning equipment and a storage medium. The aviation network planning method provided by the embodiment of the application comprises the following steps: step S1: determining a time window of a hub airport, wherein the time window comprises a starting time and an ending time; step S2: determining all selectable flight sections and flight section information thereof for each freight flow direction, and arranging flight combinations with the lowest total transportation cost according to the time windows, the flight section variables and the first constraint conditions; and step S3: and determining optional landing time and actual cargo carrying capacity of the flights needing to enter the hub airport aiming at each cargo flow, and making arrangement for the landing time and the actual cargo carrying capacity of the flights needing to enter the hub airport according to a second constraint condition so as to maximize the cargo carrying capacity of the flights entering the hub airport.

Description

Aviation network planning method, aviation network planning equipment and storage medium

Technical Field

The application relates to the field of air freight transportation planning, in particular to an air network planning method, air network planning equipment and a storage medium.

Background

With the development of the logistics industry, the demand for transportation cargo volume continues to increase, and in order to meet the market demand and further improve the timeliness, the expansion of the existing aviation network is an effective way for improving the service quality and the competitiveness of a logistics company.

The common navigation network has two modes of hub and point-to-point, the former has low cost and high efficiency, the coverage of a target city group can be realized by fewer airplanes, but the problems of flight taking-off and landing time arrangement, cargo transfer, complex distribution of hub airport resources (such as runways and parking spaces), poor transportation timeliness and the like also exist; the latter has the problems of low loading rate and unbalanced arrival, thereby increasing the unit freight cost. At present, the development of air freight transportation is often attached to air passenger transport (belly compartment), and mainly adopts point-to-point direct flights to finish the transportation of goods, although some passenger airports already have a goods transfer function, the capacity of handling the goods is only in the hundred-ton level, and the terminal function played in the whole air network is very limited.

In order to overcome the problems of the existing methods, an aviation network planning method, aviation network planning equipment and a storage medium are needed.

Disclosure of Invention

The embodiment of the invention provides an aviation network planning method, aviation network planning equipment and a storage medium, and is used for opening a direct-navigation aviation network among partial non-hub cities on the basis of a super hub (day throughput thousand-ton level), and arranging the flight line, the taking-off and landing time and the quantity of carried goods of each flight on the premise of ensuring the timeliness (delivery on the next day), so that the maximum transportation quantity and the minimum cost are realized.

In a first aspect, an embodiment of the present application provides an aviation network planning method, including: step S1: determining a time window of a hub airport, wherein the time window comprises a starting time and an ending time; step S2: determining all selectable flight sections and flight section information thereof for each freight flow direction, and arranging flight combinations with the lowest total transportation cost according to the time windows, the flight section variables and the first constraint conditions; and step S3: and determining optional landing time and the actual cargo carrying capacity of the flights needing to enter the hub airport aiming at each cargo transporting flow, and making arrangement for the landing time and the actual cargo carrying capacity of the flights needing to enter the hub airport according to a second constraint condition, so that the cargo carrying capacity of the flights entering the hub airport is maximized.

In some embodiments, the leg variables include:

whether each selectable flight section is opened or not, the theoretical cargo carrying capacity of each selectable flight section, the airplane type used by each selectable flight section and the number of airplane types of each selectable flight section.

In some embodiments, the first constraint includes:

the cargo loading rate of the selectable legs is greater than 70%.

In some embodiments, the first constraint includes:

the goods to be transported are all delivered;

the theoretical cargo carrying capacity of each optional air section is less than or equal to the maximum cargo collecting capacity of each optional air section; and

and the theoretical cargo carrying capacity of each optional air section is less than or equal to the loading capacity of the airplane type of each optional air section.

In some embodiments, the first constraint includes:

the number of flights entering the hub airport is less than or equal to the number of seats that the hub airport can park.

In some embodiments, the second constraint includes:

and in the same time, the number of flights landing the hub airport is less than or equal to the number of runways of the hub airport.

In some embodiments, the second constraint includes:

the number of flights to enter the hub airport is equal to the number of airplane models of each optional segment.

In a second aspect, an embodiment of the present application further provides an aviation network planning apparatus, including a processor and a storage, where the processor calls a computer program in the storage to execute any one of the aviation network planning methods provided in the embodiments of the present application.

In some embodiments, the computer program comprises:

the segment selection module is used for determining all selectable segments and segment information thereof for each freight flow direction and arranging flight combination with the lowest total transportation cost according to the time window, the segment variable and the first constraint condition; and

the hub scheduling module is used for determining optional landing time and actual cargo carrying capacity of the selected landing time according to the flights of the freight flow to enter the hub airport, and scheduling the landing time and the actual cargo carrying capacity of the flights to enter the hub airport according to a second constraint condition, so that the cargo carrying capacity of the flights to enter the hub airport is maximized.

In a third aspect, the present application further provides a storage medium for storing a computer program, where the computer program is suitable for being loaded by a processor to execute any one of the aviation network planning methods provided in the embodiments of the present application.

The embodiment of the application reduces the single kilogram cost of transportation by improving the cargo loading rate under the condition of transporting the same cargo quantity, and further reduces the transportation cost of the whole air transportation part. For example, when the cargo loading rate is increased from 42.1% to 71.1%, the cost per kilogram can be reduced by 2.3 yuan, so that the cost of air transportation can be saved by about 15.8%. In addition, the use of the small airplane can be reduced, and the fuel consumption and the maintenance cost of the small airplane are saved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a flow chart illustrating steps of a method for planning an aviation network according to an embodiment of the present disclosure;

FIG. 2 is an aviation network planning apparatus provided by an embodiment of the present application;

FIG. 3 is a schematic diagram of the practical operation of the embodiment shown in FIG. 2.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Referring to fig. 1 to 3, fig. 1 is a flowchart illustrating steps of an aviation network planning method according to an embodiment of the present application, fig. 2 is an aviation network planning apparatus according to an embodiment of the present application, and fig. 3 is a schematic diagram illustrating an actual operation process of the embodiment of fig. 2.

The execution subject of the aviation network planning method can be aviation network planning equipment provided by the embodiment of the application. As shown in fig. 1, the aviation network planning method is characterized by comprising:

step S1, determining a time window of a hub airport, wherein the time window comprises a starting time and an ending time. The time window can be used for sorting and transferring the goods and maintaining the airplane. I.e., cargo may be loaded or unloaded, and the aircraft serviced while within the time window. The terminal airport is used as a transfer airport between different origins and destinations in the freight process. The time window of the hub airport is influenced by the cargo handling capacity of the airport, and according to statistics, the daily cargo handling capacity of one hub airport is about 3500 tons, while the average cargo handling capacity of the current international large airport is 2000 tons/hour, so the hub transfer duration is preferably set to 2 hours, for example, 2-4 points per day can be defined as the time window of the hub airport.

And S2, determining all selectable flight sections and flight section information thereof for each freight flow direction, and arranging flight combinations with the lowest total transportation cost according to the time windows, the flight section variables and the first constraint conditions. Each flight segment has its corresponding flight and the theoretical capacity of carrying the cargo of the flight. The freight traffic is defined as the flow direction of the goods from the origin to the destination, and there may be a plurality of origins and a plurality of destinations, and further a plurality of different freight flow directions. In addition, a flow of freight may include both a direct flight and a flight that needs to enter the terminal airport for transfer (i.e., transfer from the origin via the terminal airport to the destination).

And S3, determining optional landing time and actual cargo carrying capacity of the flights needing to enter the hub airport according to each freight flow direction, and making arrangement for the landing time and the actual cargo carrying capacity of the flights needing to enter the hub airport according to a second constraint condition so as to maximize the cargo carrying capacity of the flights entering the hub airport.

Further, in step S2, all the selectable legs and their leg information may be as follows:

flight

Origin

Destination

Leg of the voyage

Model type

Load capacity

Maximum cargo collection capacity

Cost of transportation

1

s

d

s-d

B737

14 ton of

t1

c1

2

s

hub

s–hub

B757

28 ton of

t2

c2

3

hub

d

hub-d

B737

14 ton of

t3

c3

The method comprises the steps of starting place, destination, navigation section, model, loading capacity, maximum cargo collection capacity and transportation cost.

Under the aviation network mode, the goods can have two modes of directly flying and passing through a hub airport. There are 1 leg of flight, i.e., origin to destination (e.g., flight number 1 of the above list, from origin s to destination d); there are two legs through the hub airport, namely from origin to hub airport (e.g. flight 2 of the list above, from origin s to hub airport hub), to destination (e.g. flight 3 of the list above, from hub airport hub to origin s), which can be completed by different flight models. Due to the limitation of the time window, the flights passing through the terminal airport need to land before the time window so as to load the goods smoothly.

Step S2 is described by the following example, assuming that the origin is S = { S1, S2,. Sn }, the destination is D = { D1, D2, \8230, dn }, the total quantity of cargo throughout the day is a (S, D), the available models are B = { B1, B2 \8230 }, the loading quantity of each model is Q (B), the number of aircraft in each model fleet is P (B), the number of available aircraft seats in the terminal airport is H, the maximum collection quantity of each optional flight section is T (S, D, B), the transportation cost of each optional flight section is C (S, D, B), and the total transportation cost E.

The flight segment variable according to step S2 includes: whether X (s, d, b) is opened or not in each selectable flight section, the theoretical carrying capacity Y (s, d, b) of each selectable flight section and the number Z (s, d, b) of airplane models used in each selectable flight section and airplane models of each selectable flight section. Wherein

X (s, d, b) =1 is on, X (s, d, b) =0 is off. The first constraint in step S2 includes:

(1) All the quantities A (s, d) must be shipped, i.e. the goods to be shipped, wherein

s＝s1,s2…sn

d＝d1,d2…dn

(2) The theoretical cargo carrying capacity of each selectable navigation section is less than or equal to the maximum cargo collecting capacity T (s, d, b) of each selectable navigation section, wherein

X(s,d,b)×Y(s,d,b)≤T(s,d,b)

s＝s1,s2…sn

d＝d1,d2…dn

b＝b1,b2…bn

(3) The theoretical cargo carrying capacity of each selectable flight section is less than or equal to the loading capacity of the airplane type of each selectable flight section, namely the product of the loading capacity Q (b) of each airplane type and the number Z (s, d, b) of airplanes of each airplane type used in each flight section,

X(s,d,b)×Y(s,d,b)≤Q(b)×Z(s,d,b)

s＝s1,s2…sn

d＝d1,d2…dn

b＝b1,b2…bn

(4) A fleet size limit, the number Z (s, d, b) of aircraft models of each available flight segment is less than or equal to the number P (b) of aircraft of each model fleet,

b＝b1,b2…bn

(5) A limit on the number of flights entering a terminal airport, i.e., the number of flights entering the terminal airport is less than or equal to the number of available slots H at which the terminal airport may park, wherein,

d＝hub

(6) The cargo load rate limit, i.e., the cargo load rate of the selectable leg is greater than 70%, wherein,

X(s,d,b)×Y(s,d,b)≥Q(b)×Z(s,d,b)×0.7

s＝s1,s2…sn

d＝d1,d2…dn

b＝b1,b2...bn

(7) Point balancing of airports, i.e. the number of flights entering the terminal airport is less than or equal to the number of slots the terminal airport can park, wherein,

s1＝d1＝hub

b＝b1,b2…bn

thus, step S2 can make an arrangement for the origin, destination, model used, number of model used, and theoretical cargo carrying capacity of the selectable segment.

In actual implementation, due to the limitation of the number of runways of the hub airport and the operation rule of the airspace, all flights cannot be scheduled to land at the same time, and the time of arriving at the hub airport affects the time of taking off from the origin, and further affects the actual cargo carrying capacity (i.e. the finely adjusted theoretical cargo carrying capacity) of the flights. Assuming that the number of flights entering the terminal airport in step S2 is M, the number of runways of the terminal airport is N, and the time interval of the take-off and landing of two adjacent flights is limited by the airspace operation rule to be not less than 2min, so that K min is required for landing the M flights at least, wherein K min is required for landing the M flights

That is, there is an extra K min for loading, and the actual carrying capacity can be obtained by using K min in combination with the time-sharing cargo collection capacity (for example, the time-sharing cargo collection capacity per 2 min) as shown in the following table. The origin, destination and model of flight a and flight B are the same, and the theoretically carried cargo volume should be the same, but the actual carried cargo volume will be different because the time for entering (landing) the terminal airport is different (influenced by the number of runways of the terminal airport and the airspace operation rules), that is, the time for taking off at the origin is different.

Flight

Origin

Destination

Flight segment

Time to enter hinge

Actual volume of goods carried

Model type

Number of

A

s

hub

s-hub

k1

t1

B737

1

B

s

hub

s-hub

k2

t2

B737

1

In step S3, it is assumed that the model of the flight to enter the terminal airport is B = { B1, B2 \8230 }, the optional landing time is K = { K1, K2 \8230; kn }, the actual cargo capacity is T (S, K, B), the number of aircraft of each model used in each flight segment Z (S, K, B), and the open flight X (S, K, B), so as to maximize the transfer cargo capacity G entering the terminal of the airport, wherein,

furthermore, the following constraints need to be satisfied:

(1) A hub runway limit, wherein flights X (s, k, b) opened at the same time value k are less than or equal to the number of runways N of the hub airport. The number of flights X (s, k, b) opened here, i.e. the number of landed flights, i.e. the same time value k, is less than or equal to the number N of runways at the terminal airport.

k＝k1,k2....kn

(2) Limitation of flight number of each model, i.e. the number of open flights X (s, k, b) is equal to the number of airplanes Z (s, k, b) of each model used in each flight segment

s＝s1,s2…sn

b＝b1,b2…bn

Therefore, step S3 can make an arrangement for the landing time and the actual cargo carrying capacity of the flight that needs to enter the hub airport.

This application embodiment is under the condition of the same goods volume of transportation, reduces the single kilogram cost of transporting through improving the goods loading rate, and then reduces the transportation cost of whole air transportation part. For example, when the cargo loading rate is increased from 42.1% to 71.1%, the cost per kilogram can be reduced by 2.3 yuan, so that the cost of air transportation can be saved by about 15.8%. In addition, the use of the small airplane can be reduced, and the fuel consumption and the maintenance cost of the small airplane are saved.

In order to better implement the aviation network planning method provided by the embodiment of the present application, the embodiment of the present application further provides an aviation network planning device, wherein the meaning of the noun is the same as that of the aviation network planning method, and specific implementation details can refer to the description in the method embodiment. As shown in fig. 2, the airline planning device 200 can include one or more processors 210 of one or more processing cores, storage 220 of one or more computer-readable storage media, an input unit 230, a display unit 240, a power supply 250, and the like. Those skilled in the art will appreciate that the structural schematic shown in fig. 2 does not constitute a limitation of the airline network planning device 200, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.

The processor 210 is a control center of the aviation network planning apparatus 200, connects various parts of the entire aviation network planning apparatus 200 by using various interfaces and lines, performs various functions of the aviation network planning apparatus 200 and processes data by operating or executing software programs and/or modules stored in the memory 220 and calling data stored in the memory 220, thereby performing overall monitoring of the aviation network planning apparatus 200. Optionally, the processor 210 may include one or more processing cores; preferably, the processor 210 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, an application program, and the like, and the modem processor mainly processes wireless communication. It will be appreciated that the modem processor described above may not be integrated into the processor 210.

The memory 220 may be used to store software programs and modules, and the processor 401 executes various functional applications and data processing by operating the software programs and modules stored in the memory 220. The memory 220 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required by at least one function, and the like; the storage data area may store data created according to the use of the server, and the like. Further, the memory 220 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 220 may also include a memory controller to provide the processor 210 access to the memory 220.

The input unit 230 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

The display unit 240 may be used to display input information or various types of information processed by the processor 210. The Display unit 240 may include a Display panel, and optionally, the Display panel may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.

The power supply 250 is configured to supply power to each component of the aviation network planning device 200, and preferably, the power supply 250 may be logically connected to the processor 210 through a power management system, so as to implement functions of managing charging, discharging, and power consumption through the power management system. The power supply 250 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.

Specifically, in this embodiment, the processor 210 in the aviation network planning device 200 may load an executable file corresponding to one or more processes of an application program/module into the memory 220 according to the following instructions, and the processor 210 runs the application program/module stored in the memory 220, so as to implement various functions as follows:

the processor 210 invokes a computer program in the memory to perform the previously described aviation network planning method. The computer program includes: an information collection module 222, a leg selection module 224, and a hub shift module 226.

The information collection module 222 is used to collect all the selectable segments and their segment information, hub airport information (such as time window), cargo distribution information (such as maximum cargo collection amount), and other types of required information. The leg selection module 224 is configured to determine all selectable legs and leg information thereof for each freight flow direction, and arrange a flight combination with the lowest total transportation cost according to the time window, the leg variable, and the first constraint condition. The hub scheduling module 226 is configured to determine an optional landing time and an actual cargo carrying capacity of the selected landing time for the flight that needs to enter the hub airport according to each freight flow, and schedule the landing time and the actual cargo carrying capacity of the flight that needs to enter the hub airport according to a second constraint condition, so as to maximize the cargo carrying capacity of the flight that enters the hub airport.

Taking fig. 3 as an example, the information collecting module 222 may collect various types of information such as the ending time 11 of each hub airport, the time-sharing cargo collection rate 12 of each city, the cargo processing time 13 of the hub airport, the time window 14 of the hub airport, the fleet size 21, the flight/airport model restrictions 22, the number of airport stands 23, the model capacity 24, the number of airport runways 25, and the airspace operation rules 26.

The ending time 11 of each hub airport, the time-sharing cargo collection rate 12 of each city, the cargo handling time 13 of each hub airport, the time window 14 of each hub airport, the fleet size 21, the flight/airport model limit 22, the number of airport parking spaces 23 and the model capacity 24 are input into the flight selection module. The flight section selection module arranges the flight combination with the lowest total transportation cost according to the input information, and outputs information such as the open flight section 31 and the theoretical cargo carrying capacity 32 of the flight. Then, the data of the open flight segment 31, the theoretical carried capacity of the flight 32, the number of airport runways 25, the airspace operation rules 26, etc. are input into the hub scheduling module, and the hub scheduling module processes the information according to the maximization of the transported capacity of the hub airport, so as to arrange the landing time and the actual carried capacity of the flight that needs to enter the hub airport, namely to perform scheduling. The hub shift module typically outputs the leg landing time 41 and the flight load 42. The flight landing time 41 is required to determine whether the right of way 50 can be acquired, and if the right of way is acquired successfully, the shift arrangement result 60 is output. If the right of way cannot be acquired, the right of way time limit 51 is confirmed again, and the right of way time limit 51 is input into the hub scheduling module for scheduling again.

The specific implementation of the operation of the aviation network planning device can be referred to the foregoing embodiments, and is not described herein again.

It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by instructions controlling associated hardware, and the instructions may be stored in a computer readable storage medium and loaded and executed by the processor.

To this end, a storage medium is further provided in an embodiment of the present application, where the storage medium is used to store a computer program, and the computer program is suitable for being loaded by a processor to execute the aviation network planning method provided in the embodiment of the present application. For example, the computer program, loaded by the processor, may perform the steps of:

step S1: determining a time window of a hub airport, wherein the time window comprises a starting time and an ending time; step S2: determining all selectable flight sections and flight section information thereof for each freight flow direction, and arranging flight combinations with the lowest total transportation cost according to the time windows, the flight section variables and the first constraint conditions; and step S3: and determining optional landing time and the actual cargo carrying capacity of the flights needing to enter the hub airport aiming at each cargo transporting flow, and making arrangement for the landing time and the actual cargo carrying capacity of the flights needing to enter the hub airport according to a second constraint condition, so that the cargo carrying capacity of the flights entering the hub airport is maximized.

The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.

It should be understood by those skilled in the art that the storage medium may include a Memory, such as a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic or optical disk, and the like.

The beneficial effects of the storage medium provided by the embodiment of the present application for executing the computer program stored therein are detailed in the foregoing embodiments and will not be described herein again.

The aviation network planning method, the aviation network planning device and the storage medium provided by the embodiments of the present application are introduced in detail, and specific examples are applied in the present application to explain the principle and implementation manner of the present application, and the description of the embodiments is only used to help understand the method and core ideas of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. An aviation network planning method, comprising:

step S1: determining a time window of a hub airport, wherein the time window comprises a starting time and an ending time;

step S2: determining all selectable segments and segment information thereof for each freight flow direction, and arranging flight combinations with the lowest total transportation cost according to the time windows, segment variables and first constraint conditions, wherein the segment variables comprise: whether each selectable flight section is opened or not, the theoretical cargo carrying capacity of each selectable flight section, the number of airplane models used by each selectable flight section and the number of airplane models of each selectable flight section are determined, wherein the first constraint condition comprises the following steps: the cargo loading rate of the selectable leg is more than 70%; and

and step S3: determining optional landing time and actual cargo carrying capacity of the flights needing to enter the hub airport aiming at each cargo flow, and making arrangement for the landing time and the actual cargo carrying capacity of the flights needing to enter the hub airport according to second constraint conditions so as to maximize the cargo carrying capacity of the flights needing to enter the hub airport, wherein the second constraint conditions comprise: and in the same time, the number of flights landing the hub airport is less than or equal to the number of runways of the hub airport, and the number of flights needing to enter the hub airport is equal to the number of airplane models of each available flight section.

2. The aviation network planning method of claim 1, wherein the first constraint comprises:

the goods to be transported are all delivered;

the theoretical cargo carrying capacity of each selectable navigation section is less than or equal to the maximum cargo collecting capacity of each selectable navigation section; and

and the theoretical cargo carrying capacity of each selectable flight section is less than or equal to the loading capacity of the airplane type of each selectable flight section.

3. The aviation network planning method of claim 1, wherein the first constraint comprises:

4. An aviation network planning apparatus comprising a processor and a memory, the processor invoking a computer program in the memory to perform an aviation network planning method according to any one of claims 1 to 3.

5. The airborne network planning apparatus of claim 4 wherein said computer program comprises:

6. A storage medium for storing a computer program adapted to be loaded by a processor for performing the method of aircraft network planning according to any one of claims 1 to 3.