WO2007119898A1

WO2007119898A1 - System and method for loading management for passenger and cargo aircraft

Info

Publication number: WO2007119898A1
Application number: PCT/KR2006/001465
Authority: WO
Inventors: Ki Young Oh
Original assignee: Nexzen Interactive Co., Ltd.
Priority date: 2006-04-17
Filing date: 2006-04-19
Publication date: 2007-10-25
Also published as: KR20070102864A

Abstract

A system for loading management includes a loading-object information storing unit for receiving loading-object information from an external unit where the loading-object information is predetermined information about objects loaded in an aircraft; a loading-model creating unit for creating at least one of populations of an initial generation using the loading-object information stored in the loading-object information storing unit as designing variables where the populations of the initial generation is a basic loading model, calculating a fitness of the initial- generation population using predetermined constraint functions and repeatedly creating populations of next-generations by performing at least one of computing processes including crossover, mutation, displacement, duplication, addition and deletion until an optimal loading model is created where the optimal loading model is a population that satisfies a predetermined fitness; and a result storing unit for storing the optimal loading-model created from the loading model creating unit.

Description

SYSTEM AND METHOD FOR LOADING MANAGEMENT FOR PASSENGER AND CARGO AIRCRAFT

Technical Field

[1] The present invention relates to a system and method for loading management for passenger and cargo aircraft for accurately and effectively loading cargos in the aircraft by computing a weight and balance of an aircraft using an automated system, which was manually computed. Background Art

[2] It is very important to evenly distribute loads in an aircraft to balance the aircraft. If not, the center of gravity of the aircraft may move to the front of the aircraft, which is called as a nose-heavy freight aircraft, or a center of gravity of the aircraft may move to the back of the aircraft, which is called as a tail-heavy freight aircraft. Such an unbalanced aircraft may waste fuel unnecessarily. Also, the unbalanced aircraft may have a great difficulty in pulling the nose of the aircraft upwardly when the aircraft takes off or lands and in restoring the balance of the aircraft from stall or spin. That is, the unevenly loaded cargos may cause a serious aircraft accident.

[3] In order to operate the aircraft safely and economically, it is essential to compute an optimal weight and balance of the aircraft in consideration of all loads which are loaded into the aircraft. Such loads may include an aircraft itself, fuel, a pantry, catering, passengers, pilots, stewards and stewardesses, cargos, baggage and mails. Among these loads, the cargos may be the most important factor to balance the aircraft. It is because that the weights and locations of the cargos significantly influence the optimal weight and balance of the aircraft. Also, it is very convenient to control the locations of the cargos for balancing the aircraft. Therefore, the optical weight and balance of the aircraft is generally calculated by controlling the locations of the cargos under an assumption that fixed locations are assigned to other loads such as the fuel, pantry, catering, passengers and pilots.

[4] According to the related art, a load master who has long experience in loading cargos is forced to allocate locations to cargos with consideration of other loads and calculate the optical weight and balance manually in a comparatively short limited time. Therefore, there is a great chance to generate errors in calculating of the optimal weight and balance of the aircraft. Also, the load master takes longer time to calculate the optical weight and balance of the aircraft due to the manual calculation. Since the load master manually performs all of the processes for obtaining the optical weight and balance, it is very difficult to control the loads in order to obtain a MAC% that is converged into a predetermined range of a safe navigation where the MAC% is a scale of a safety zone. Disclosure of Invention

Technical Problem

[5] It is, therefore, an object of the present invention to provide a system and method for loading management for passenger and cargo aircraft for accurately and effectively loading cargos by computing a weight and balance using an automated system with a genetic algorithm. Technical Solution

[6] In accordance with one aspect of the present invention, there is a system for loading management for passenger and cargo aircraft, including: a loading-object information storing unit for receiving loading-object information from an external unit where the loading-object information is predetermined information about objects loaded in an aircraft and storing the received loading-object information; a loading-model creating unit for creating at least one of populations of an initial generation using the loading- object information stored in the loading-object information storing unit as designing variables where the populations of the initial generation is a basic loading model, calculating a fitness of the initial-generation population using predetermined constraint functions and repeatedly creating populations of next-generations by performing at least one of computing processes including crossover, mutation, displacement, duplication, addition and deletion until an optimal loading model is created where the optimal loading model is a population that satisfies a predetermined fitness; and a result storing unit for storing the optimal loading model created from the loading model creating unit.

[7] In accordance with another aspect of the present invention, there is a method for loading management for passenger and cargo aircraft, including; a loading-object information storing step for receiving loading-object information from an external unit where the loading-object information is predetermined information about objects loaded in an aircraft and storing the received loading-object information; a loading- model creating step for creating at least one of populations of an initial generation using the loading-object information stored in the loading-object information storing unit as designing variables where the populations of the initial generation is a basic loading model, calculating a fitness of the initial-generation population using predetermined constraint functions and repeatedly creating populations of next- generations by performing at least one of computing processes including crossover, mutation, displacement, duplication, addition and deletion until an optimal loading model is created where the optimal loading model is a population that satisfies a pre- determined fitness; and a result storing step for storing the optimal loading model created from the loading model creating step.

Advantageous Effects

[8] A system and method for loading management for passenger and cargo aircraft according to the present invention computes a weight and balance of the aircraft using an automated system with a genetic algorithm. Therefore, cargos can be accurately and quickly loaded in the aircraft according to the present invention.

[9] Also, the system and method for loading management for passenger and cargo aircraft according to the present invention digitalize a result of operation and store the digitalized data thereof. Therefore, overlapped operations can be effectively processed, and related operations at a next stop of an aircraft can be easily processed by transmitting the stored data to a system for loading management in the next stop through a network. Brief Description of the Drawings

[10] The above and other objects and features of the present invention will become apparent from the following description of the preferred embodiments given in conjunction with the accompanying drawings, in which:

[11] FIG. 1 is a block diagram illustrating an entire system having a system for loading management for passenger and cargo aircraft according to an embodiment of the present invention; and

[12] FIG. 2 is a flowchart showing a method for loading management for passenger and cargo aircraft according to an embodiment of the present invention. Best Mode for Carrying Out the Invention

[13] Other objects and aspects of the invention will become apparent from the following description of the embodiments with reference to the accompanying drawings, which is set forth hereinafter.

[14] FIG. 1 is a block diagram illustrating an entire system having a system for loading management for passenger and cargo aircraft according to the present invention. The system of FIG. 1 includes a system for loading managemen 100 for a passenger and cargo aircraft, a user terminal 200, a network 300 and an on-line reservation server 400, as shown in FIG. 1.

[15] The system for loading management 100 for a passenger and cargo aircraft includes a loading-object information storing unit 110, a loading-model creating unit 120, a simulation unit 130 and a result storing unit 140.

[16] The loading-object information storing unit 110 receives loading-object information from the user terminal 200 and the on-line reservation server 400, where the loading- object information is information about objects to load in an aircraft. [17] It is preferable that the loading-object information may include information about a weight, a feature, a shape and a destination if the loading-object is a cargo.

[18] The network 300 may be a public switch telephone network (PSTN) and a wired/ wireless communication network capable of exchanging data between the system for loading management 100 and the on-line reservation server 400.

[19] Also, the user terminal 200 is allowed to access the system for loading management

100 through the network 300 in the present embodiment.

[20] The loading-model creating unit 120 transforms the loading-object information stored in the loading-object information storing unit 110 to a binary string. While transforming, the loading-model creating unit 120 also detects a basic error of the loading-object information.

[21] The basic error may be a weight of a predetermined loading-object which is impossible for the predetermined loading-object to have such a weight according to it's feature. That is, the basic error may be an error generated when related information is inputted.

[22] Then, an initial-generation population is created using the transformed loading- object information. The initial-generation population is a basic loading-model. After creating the basic loading-model, fitness thereof is analyzed through predetermined constraint functions.

[23] Hereinafter, the predetermined constraint functions for analyzing the fitness of the created loading-models will be described. Herein, i and j denote integers.

[24] At first, a constraint function for calculating an index value for a loaded loading- object is shown in below Eq. 1.

[25] Eq. 1

[26]

[27] Using the constraint function of Eq. 1, the fitness is analyzed with regard to weights of loading objects according to locations thereof in an aircraft. [28] In Eq. 1, PΙx(i) denotes a function that returns an index value denoting an influence of an loading-object on the aircraft navigation based on the loading location of the loading-object. The index values of the loading-objects may be provided from each of airlines. In Eq. 1, PΙx(i) outputs an index value of a loading object placed at an i location. [29] In the aircraft, a unique weight limitation condition is defined at each of locations for cargos. Cw(j) is a function that outputs whether a j loading-object satisfies the weight limitation condition of a corresponding location or not. [30] For example, a below table 1 shows a weight limitation condition function of a pre- determined location in an aircraft.

[31] Table 1

[32] Table 1 shows that the weight of a loading-object loaded at an Al location may not be allowed to exceed 3674kg. Also, a sum of the weight of a loading-object at an Al location and the weight of a loading object loaded at an A2 location may not be exceeded 4808kg.

[33] Therefore, a fitness for loading a predetermined loading-object in an aircraft may be expressed as a sum of values outputted from the functions by applying predetermined locations into the functions.

[34] Eq. 2 shows a constraint function for limiting a loading-object to load at a predetermined location according to the feature of the loading-object. [35] The function Pc(i) of Eq. 2 outputs the fitness for loading a j loading-object according to the weight limitation condition of a i' position. [36] The function CC of Eq. 2 outputs an approval value or a disapproval value by comparing the outputs of functions CCQ) and Pc(i). That is, the function CC outputs the approval value if the i location of the aircraft is allowable to arrange the j loading object. If the i' position of the aircraft is not allowable to arrange the j loading object, the function CC outputs the disapproval value.

[37] Eq. 2 [38]

CC=Cc(j) *Pc(i)

[39] Using the constraint function of Eq. 2, the fitness of the loading-object is analyzed according to the feature of the loading object such as a live animal or a plant or dangerous material.

[40] At first, the function CcQ) reads the feature of the loading-object j and transforms the feature of the loading- object j to a predetermined value. For example, if the j loading-object is a live animal or a plant, the Cc(j) outputs a value of AVI as shown in Table 2. Table 2 shows values assigned to loading-objects according to feature thereof.

[41] The function PcQ) of Eq. 2 outputs the fitness for loading a j loading-object according to the weight limitation condition of a i' position. [42] Table 2

[43] The function CC of Eq. 2 outputs an approval value or a disapproval value by comparing the outputs of functions CC(j) and Pc(i). That is, the function CC outputs tthhee aapppproval value if the i location of the aircraft is allowable to arrange the j loading object.

[44] If the i position of the aircraft is not allowable to arrange the j loading object, the function CC outputs the disapproval value. [45] Eq. 3 shows a constraint function for limiting the loading of loading-object according to the shape of the loading-object. [46] Eq. 3

[47]

[48] Using the function of Eq. 3, the fitness of a loading object is analyzed according to the shape of the loading object.

[49] The functions CtQ) returns a specific value according to shape of loading-object.

[50] The functions Pt(i) contrasts the shape of CtQ)¹S loading-object with shape of nearby loading-object, and returns permission value or prohibition value if the loading- object of CtQ) is loaded of the i location.

[51] Eq. 4 shows a function for effectively loading loading-objects with regard to destinations of the loading-objects.

[52] Eq. 4 [53]

Ci? = CrO)*Cr( l )*Pr(/) *Pr(£)

[54] Using the function of Eq. 4, the fitness of a loading object is analyzed with regard to a distance from a desired loading-location to a cargo door in order to effectively load the loading-object according to a distance to a destination.

[55] At first, the functions Cr(j) and Cr(I) output different values according to the destination of the loading-object. The functions Cr(j) and Cr(I) output 1 when the j loading-object unloads at a first stop. The functions Cr(j) and Cr(I) may output 2 when the j loading object unloads at a second stop.

[56] The functions Pr(i) and Pr(Ic) are functions analyzing a loading-location according to a destination of a loading-object. For example, the functions Pr(i) and Pr(Jc) return 0 if a loading-object having a destination as a first stop is loaded around a cargo door. If the loading-object having a destination as other stops is loaded around the cargo door, the functions Pr(i) and Pr(Ic) return other numbers. That is, the farther a distance to a destination is, the grater the functions Pr(i) and Pr(Jc) return a value.

[57] A general fitness of a created loading-model is calculated using an objective function shown in Eq. 5 by applying the value of Cl into the objective function shown in Eq. 5

[58] Eq. 5

[59] ^o/oλ4Ac={(c*(i-κyvr)+R-Ly{M/ιoo)

[60] In Eq. 5, C, K, R, L and M are basic constants provided from a company manufacturing a corresponding aircraft, and I is a sum of CI, an index of an aircraft, an index of a crew member and an index of a fuel. W denotes a total weight of loading- objects and a weight of the aircraft.

[61] If a %MAC value is in a range from 8.5 to 30 in case of a Boeing aircraft 747-400, a safe aerial navigation thereof is guaranteed. If a %MAC value is in a range from 26 to 30 in case of a Boeing 747-400, economic aerial navigation is guaranteed. However, such a range for safe and economic aerial navigation may vary according to predetermined conditions such as a type of the aircraft.

[62] If an initial generation population of the fitness expressed as the %MAC value is not in a range for guaranteed safe or economic aerial navigation such as from 8.5 to 30 or from 26 to 30, populations of next generations are repeatedly created until an optimal loading-model is created through computing processes such as crossover, mutation, displacement, duplication, addition and deletion.

[63] When the populations are repeatedly performed, it is preferable to use a penalty function that assigns a penalty to the constraint functions in order to induce a population of a next generation having a better fitness.

[64] After creating an optimal loading-model, it is preferable to display the optimal loading-model through a graphic user interface (GUI) of the user terminal 200 in order to allow the user to conveniently recognize and analyze the optimal loading-model.

[65] The simulation unit 130 generates a modified loading-model by modifying the optimal loading-model created from the loading-model creating unit 120 according to an user's input received through the user terminal 200, and the simulation unit 130 calculates the fitness of the modified loading-model.

[66] Herein, the modified loading-model and the fitness of the modified loading-model may be displayed through the GUI of the user terminal 200 in order to allow a user to conveniently recognize and analyze the modified loading model. It is preferable that a Drag & Drop mode is provided to a user to input commands for convenience.

[67] By modifying the loading-model according to the user's input, it is also possible to receive the loading-object information through the user terminal 200 which was not received from the on-line reservation server 400. Furthermore, it is possible to modify locations of predetermined loading-objects with regard to factors that were not considered by the loading-model creating unit 120.

[68] As described above, a fitness of a modified loading-model is computed after modifying the optimal loading-model. It makes a user to conveniently estimate the influence of modification of the optimal loading-model. Therefore, a user who does not have long experience for loading the cargos may easily understand the fundamental concept of loading cargos.

[69] Differently from the above shown method, the optimal loading-model may be created after arranging predetermined loading-objects according to a user's input. That is, fixed locations are assigned to the predetermined loading-objects according to the user's input and then optimal loading-model is created by assigning remained locations to other loading-objects.

[70] The result storing unit 140 stores the optimal loading-model and the modified loading-model generated from the loading-model creating unit 120 and the simulation unit 130.

[71] These stored optimal loading-model and modified loading-mode are outputted through the user terminal 200 to the user or transmitted to a server (not shown) in a next stop of the aircraft through the network 300 in order to a user or an operator to use the optimized loading-model or the modified loading-model created at the previous stop. Therefore, the cost and the time for creating a new optimal loading-model for a current stop may be reduced.

[72] Hereinafter, a load control method for a passenger and cargo aircraft according to an embodiment of the present invention will be described with reference to FIG. 2. Same numeral references denote same elements in FIGS. 1 and 2.

[73] At first, the system for loading management 100 for the passenger and cargo aircraft receives loading-object information which is information about predetermined objects to be loaded in the aircraft through the user terminal 200 and/or the on-line reservation server 400 and stores the received loading-object information in the loading-object information storing unit 110 in operation S310.

[74] Then, the loading-model creating unit 120 creates one or more populations of initial generation which is a basic loading-model using the loading-object information stored in the loading-object information storing unit 110 as design variables. After creating the loading model of the initial generation, a fitness of the initial-generation population is analyzed using predetermined constraint functions. Then, the loading-model creating unit 120 repeatedly generates populations of next generations until a population satisfying a predetermined fitness is created. That is, the loading-model creating unit 120 creates loading-models until an optimal loading-model is created through at least one of computing processes including crossover, mutation, displacement, duplication, addition and deletion in operation S320

[75] When the next generation population is generated, it is preferable to use a penalty function that assigns a penalty to the constraint function in order to induce generation of a population of a next generation having a better fitness.

[76] Meanwhile, the simulation unit 130 modifies the optimal loading-model created from the loading-model creating unit 120 according to user's input received from the user terminal 200, creates a modified loading-model which is the optimal loading- model modified by the user's input and calculates a fitness of the modified loading- model in operation S330

[77] In the present embodiment, it is not required to perform the operations S320 and

S330 in sequence. That is, it is possible to create the optimal loading model after assigning fixed locations to predetermined loading-object according to the user's input. That is, the simulation operation may be performed to assign the fixed locations to the predetermined loading-object according to the user's input at first. Then, the optimal loading model is created by arranging remained loading-objects.

[78] The result storing unit 140 stores the optimal loading-model created from the loading-model creating unit 120 and the modified loading-model generated at the simulation unit 130 in operation S340

[79] The invention can also be embodied as computer-readable codes on a computer- readable recording medium. The computer-readable recording medium is any data storage device that can store data which can be thereafter read by a computer system.

[80] Examples of the computer-readable recording medium include read-only memory (ROM), random- access memory (RAM), CD-ROMs, magnetic tapes, floppy disks, optical data storage devices, and carrier waves (such as data transmission through the Internet). The computer-readable recording medium can also be distributed over network-coupled computer systems so that the computer-readable code is stored and executed in a distributed fashion. (Also, functional programs, codes, and code segments for accomplishing the present invention can be easily construed by programmers skilled in the art to which the present invention pertains.)

[81] While the present invention has been described with respect to certain preferred embodiments, it will be apparent to those skilled in the art that various changes and modifications may be made without departing from the scope of the invention as defined in the following claims.

Claims

[1] A system for loading management for passenger and cargo aircraft, comprising: a loading-object information storing unit for receiving loading-object information from an external unit where the loading-object information is predetermined information about objects loaded in an aircraft and storing the received loading-object information; a loading-model creating unit for creating at least one of populations of an initial generation using the loading-object information stored in the loading-object information storing unit as designing variables where the populations of the initial generation is a basic loading model, calculating a fitness of the initial-generation population using predetermined constraint functions and repeatedly creating populations of next-generations by performing at least one of computing processes including crossover, mutation, displacement, duplication, addition and deletion until an optimal loading model is created where the optimal loading model is a population that satisfies a predetermined fitness; and a result storing unit for storing the optimal loading model created from the loading model creating unit.

[2] The system for loading management of claim 1, wherein the loading-object information storing unit receives the loading-object information from an on-line reservation server and stores the received loading-object information.

[3] The system for loading management of claim 1, wherein the loading-model creating unit assigns a penalty when a population of a next generation is created in order to induce the population of the next generation to have a better fitness.

[4] The system for loading management of claim 1, further comprising: a simulation unit for creating a modified loading-model by modifying the optimal loading- model created from the loading-model creating unit according to a user's input and calculating a fitness of the modified loading-model, wherein the result storing unit stores the modified loading model generated from the simulation unit.

[5] The system for loading management of claim 1, wherein the loading-object information includes at least one of information about a weight, a feature, a shape and a destination of a loading object.

[6] A method for loading management for passenger and cargo aircraft, comprising: a loading-object information storing step for receiving loading-object information from an external unit where the loading-object information is predetermined information about objects loaded in an aircraft and storing the received loading-object information; a loading-model creating step for creating at least one of populations of an initial generation using the loading-object information stored in the loading-object information storing unit as designing variables where the populations of the initial generation is a basic loading model, calculating a fitness of the initial-generation population using predetermined constraint functions and repeatedly creating populations of next-generations by performing at least one of computing processes including crossover, mutation, displacement, duplication, addition and deletion until an optimal loading model is created where the optimal loading model is a population that satisfies a predetermined fitness; and a result storing step for storing the optimal loading model created from the loading model creating unit.

[7] The method for loading management of claim 6, wherein the loading-object information storing step receives the loading-object information from an on-line reservation server and stores the received loading-object information.

[8] The method for loading management of claim 6, wherein the loading-model creating step assigns a penalty when a population of a next generation is created in order to induce the population of the next generation to have a better fitness.

[9] The method for loading management of claim 6, further comprising: a simulation step for creating a modified loading-model by modifying the optimal loading- model created from the loading-model creating step according to a user's input and calculating a fitness of the modified loading-model, wherein the result storing step stores the modified loading model generated from the simulation unit.

[10] A computer readable recording medium storing a program for executing the The method for loading management of any one of claims 6 through 9.