Intelligent stowage method for bulk cargo and passenger aircraft
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- XIAMEN AIRLINES CO LTD
- Filing Date
- 2026-01-29
- Publication Date
- 2026-06-19
Smart Images
Figure CN122241965A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of civil aviation transportation technology, and in particular to an intelligent loading method for bulk cargo hold passenger aircraft. Background Technology
[0002] Flight load planning is a critical operation, impacting aircraft balance, fuel economy, and takeoff and landing safety. Traditionally, this task relies on manual experience, requiring load planners to calculate dozens of parameters, from cargo hold allocation and passenger seating arrangement to fuel balance. Each step involves finding a balance point within complex multidimensional constraints, which is time-consuming and often fails to achieve the desired results.
[0003] To address these issues, a new generation of load distribution planning system (NLDP) has emerged to assist in load planning. This system can filter and generate load plans based on flight requirements, but it has not been able to automatically generate the optimal load plan, which urgently needs to be resolved. Summary of the Invention
[0004] Therefore, it is necessary to provide an intelligent loading method for passenger aircraft with bulk cargo holds to address the aforementioned technical problems. This method can automatically generate flight loading plans and improve the accuracy of the loading plans.
[0005] Firstly, this application provides an intelligent loading method for bulk cargo hold-type passenger aircraft, including:
[0006] The objective function for the load of the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0007] Determine the constraints corresponding to the load allocation objective function;
[0008] Based on the load objective function and constraints, determine the flight configuration parameters and weight configuration parameters of the target aircraft;
[0009] Based on flight configuration parameters and weight configuration parameters, determine the flight load plan for the target aircraft.
[0010] In one embodiment, the load objective function includes a first objective function and a second objective function; correspondingly, with the objective of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity, the load objective function corresponding to the target aircraft is constructed, including:
[0011] The first objective function for the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0012] With the goal of minimizing the penalty value corresponding to the target aircraft's payload configuration parameters, a second objective function is constructed for the target aircraft.
[0013] In one embodiment, a first objective function for the target aircraft is constructed with the objective of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity, including:
[0014] Obtain the takeoff operating parameters and takeoff reference baseline of the target aircraft; the takeoff reference baseline includes Class I baseline and Class II baseline;
[0015] The difference between the takeoff operating parameters and the first type of baseline is used as the first variable, and the second type of baseline is used as the second variable. The actual center of gravity of the target aircraft is determined based on the ratio of the first variable to the second variable.
[0016] The first objective function for the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0017] In one embodiment, a second objective function for the target aircraft is constructed, with the goal of minimizing the penalty value corresponding to the target aircraft's payload configuration parameters. This function includes:
[0018] Based on the preset penalty score determination function and the cargo placement location of the target aircraft, the penalty score corresponding to the target aircraft's cargo configuration parameters in different dimensions is determined.
[0019] The objective function for the target aircraft is to minimize the sum of penalty values corresponding to the target aircraft's payload configuration parameters in different dimensions.
[0020] In one embodiment, the constraints include at least one of the following:
[0021] The first constraint condition constraining the flight performance envelope of the target aircraft;
[0022] The second constraint condition constrains the weight and placement of the cargo carried by the target aircraft.
[0023] The third constraint condition constrains the cabin-related data of the target aircraft.
[0024] In one embodiment, the flight load plan for the target aircraft is determined based on flight configuration parameters and weight configuration parameters, including:
[0025] If the flight configuration parameters meet the flight configuration standards and the weight configuration parameters meet the weight configuration standards, the flight load plan for the target aircraft is determined based on the flight configuration parameters and the weight configuration parameters.
[0026] Secondly, this application also provides an intelligent loading device for bulk cargo hold-type passenger aircraft, including:
[0027] The function construction module is used to construct the load objective function for the target aircraft with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0028] The constraint determination module is used to determine the constraint conditions corresponding to the load objective function;
[0029] The first determining module is used to determine the flight configuration parameters and weight configuration parameters of the target aircraft based on the load objective function and constraints.
[0030] The second determination module is used to determine the flight load scheme for the target aircraft based on flight configuration parameters and weight configuration parameters.
[0031] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:
[0032] The objective function for the load of the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0033] Determine the constraints corresponding to the load allocation objective function;
[0034] Based on the load objective function and constraints, determine the flight configuration parameters and weight configuration parameters of the target aircraft;
[0035] Based on flight configuration parameters and weight configuration parameters, determine the flight load plan for the target aircraft.
[0036] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:
[0037] The objective function for the load of the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0038] Determine the constraints corresponding to the load allocation objective function;
[0039] Based on the load objective function and constraints, determine the flight configuration parameters and weight configuration parameters of the target aircraft;
[0040] Based on flight configuration parameters and weight configuration parameters, determine the flight load plan for the target aircraft.
[0041] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:
[0042] The objective function for the load of the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0043] Determine the constraints corresponding to the load allocation objective function;
[0044] Based on the load objective function and constraints, determine the flight configuration parameters and weight configuration parameters of the target aircraft;
[0045] Based on flight configuration parameters and weight configuration parameters, determine the flight load plan for the target aircraft.
[0046] The aforementioned intelligent loading method for bulk cargo hold passenger aircraft aims to minimize the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity. It constructs a loading objective function for the target aircraft, and during the solution process, determines the flight configuration parameters and weight configuration parameters of the target aircraft based on the objective function and constraints. Finally, it determines the flight loading scheme for the target aircraft based on these parameters. Compared to traditional manual loading schemes, this method enables the automatic generation of flight loading schemes and improves their accuracy. Attached Figure Description
[0047] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0048] Figure 1 This is a flowchart illustrating an intelligent loading method for a bulk cargo hold-type passenger aircraft in one embodiment.
[0049] Figure 2 This is a flowchart illustrating the steps for constructing the objective function in one embodiment;
[0050] Figure 3A This is a flowchart illustrating an intelligent loading method for a bulk cargo hold-type passenger aircraft in one embodiment.
[0051] Figure 3B This is a schematic diagram of the algorithm architecture in one embodiment;
[0052] Figure 4 This is a structural block diagram of the intelligent loading device for a bulk cargo hold-type passenger aircraft in one embodiment;
[0053] Figure 5 This is a structural block diagram of the intelligent loading device for a bulk cargo hold-type passenger aircraft in another embodiment;
[0054] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation
[0055] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0056] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.
[0057] In one exemplary embodiment, such as Figure 1 As shown, an intelligent loading method for bulk cargo hold passenger aircraft is provided, including the following steps:
[0058] S110, with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity, constructs the corresponding load objective function for the target aircraft.
[0059] The target aircraft can be any aircraft that requires the generation of flight loading schemes. This application does not impose any restrictions on the flight status or aircraft model of the target aircraft.
[0060] The preset theoretical center of gravity can be determined based on human experience or through extensive experimentation; this application does not impose any limitations on this. It should be noted that the setting of the preset theoretical center of gravity needs to be a balance point that is dynamically adjusted within the preceding and following limits, based on the target aircraft type, the current flight phase, and the flight mission requirements. The core principle of its setting is to ensure the optimal overall balance of the target aircraft's flight stability, maneuverability, and economy.
[0061] For example, in this embodiment, the actual center of gravity of the target aircraft under different loads can be determined based on a preset actual center of gravity determination model. According to the different loads of the target aircraft and the actual center of gravity corresponding to the different loads, a center of gravity determination formula is constructed with the load parameters of the target aircraft as independent variables and the actual center of gravity of the target aircraft as dependent variables. Furthermore, the difference between the center of gravity determination formula and the preset theoretical center of gravity is used as the load objective function corresponding to the target aircraft.
[0062] S120, determine the constraints corresponding to the load objective function.
[0063] In one alternative implementation, the constraints can be determined based on human experience and are used to constrain the flight parameters and load parameters of the target aircraft.
[0064] In another alternative implementation, the constraints include at least one of the following: a first constraint constraining the flight performance envelope of the target aircraft; a second constraint constraining the weight and placement of the cargo carried by the target aircraft; and a third constraint constraining the cabin-related data of the target aircraft.
[0065] The flight performance envelope may include at least one of the following: the fuel-free index envelope, the landing index envelope, and the takeoff index envelope.
[0066] Among them, cabin-related data can be understood as data corresponding to cabin classes of a target aircraft in multiple dimensions. For example, it includes at least one of the following: the number of arrival stations corresponding to the same cabin class, the relationship between long-haul and short-haul baggage in the same cabin class, and the size relationship between the volume of baggage placed in the cabin class and the cabin volume.
[0067] In one alternative implementation, the first constraint may include:
[0068] Oil-free index envelope constraint: ;
[0069] In the formula, ZFIL represents the leading edge of the oil-free index; ZFI represents the oil-free index; and ZFIA represents the trailing edge of the oil-free index.
[0070] Landing index envelope constraints: ;
[0071] In the formula, LIL represents the leading edge of the landing index envelope; LI represents the landing index; and LIA represents the trailing edge of the landing index envelope. LI represents the Landing Index, ZFI represents the No Oil Index, and RLT represents the Remaining Oil Index.
[0072] Takeoff index envelope constraint: ;
[0073] In the formula, TKIL represents the leading edge of the takeoff index envelope; TKI represents the takeoff index; and TKIA represents the trailing edge of the takeoff index envelope.
[0074] In one alternative implementation, the second constraint may include:
[0075] Cargo weight constraints: ;
[0076] In the formula, This represents the weight matrix for placing goods; l represents a single item; L represents the set of goods. ; Indicates the weight of the goods. This constraint indicates that the sum of the weight matrix columns is equal to the weight of the goods themselves corresponding to that column.
[0077] Cargo location constraints: ;
[0078] In the formula, This represents the weight matrix for placing goods; M represents a sufficiently large constant used to linearize logical constraints. Represents the goods placement matrix. If cargo l is placed in hold h, then Otherwise, it is 0; A weight chart indicating that the luggage has been split into smaller pieces. H represents cabin class; this constraint indicates that for baggage, when the placement matrix is 1, the weight matrix must be allocated according to the split weight; for non-baggage, when the placement matrix is 1, the weight matrix must be >0.
[0079] Weight matrix and placement matrix constraints: ;
[0080] In the formula, This represents the weight matrix for placing goods; M represents a sufficiently large constant used to linearize logical constraints. Represents the goods placement matrix. If cargo l is placed in hold h, then Otherwise, it is 0; H represents the cargo space; L represents the cargo set; this constraint means that when the placement matrix is 0, the weight matrix must be 0.
[0081] In one alternative implementation, the third constraint may include:
[0082] Weight difference constraint between front and rear cabins: ;
[0083] In the formula, This represents the weight matrix for cargo placement; H represents the cargo hold; L represents the cargo collection; ED represents the weight difference limit between the front and rear holds.
[0084] Weight difference constraint between front and rear cabins in long-threaded operation: ;
[0085] In the formula, This represents the weight matrix for cargo placement; H represents the cargo hold; LL represents the long-threaded cargo set; ED represents the weight difference limit between the front and rear holds.
[0086] After removing baggage weight difference constraints between the front and rear cabins:
[0087] ;
[0088] In the formula, The matrix represents the weight of cargo placement; HB represents the rear hold set; L represents the cargo set; HF represents the front hold set; LU represents the baggage set; and ED represents the weight difference limit between the front and rear holds.
[0089] Cabin structure weight limits: ;
[0090] In the formula, This represents the weight matrix for cargo placement; H represents the cargo hold. This indicates the structural weight limit for each compartment.
[0091] Cabin volume constraints: ;
[0092] In the formula, This represents the weight matrix for cargo placement; H represents the cargo hold. Indicates the volume of goods; Indicates cabin volume; VCR indicates volume conversion rate. Indicates the weight of the goods. .
[0093] Combined cabin weight restrictions:
[0094] ;
[0095] In the formula, This represents the weight matrix for cargo placement; H represents the cargo hold. Indicates the weight limit for combined cabins; ;if If there is no joint weight limit, then .
[0096] Cargo volume constraints at hatch positions:
[0097] ;
[0098] In the formula, Represents the weight matrix of the placed goods; Indicates the volume of goods; Indicates the weight of the goods. M represents a sufficiently large constant used for linearizing logic constraints. Represents the goods placement matrix. If cargo l is placed in hold h, then Otherwise, it is 0; VCR represents the volume of the cargo hold; H represents the cargo hold; HD represents the set of cargo holds; this constraint means that if the requirement of placing baggage in a cargo hold is not met, then the volume of the cargo placed in a cargo hold at a cargo hold must not exceed 50% of the volume of that cargo hold.
[0099] Location constraints for baggage on medium- and long-haul flights and cargo on short-haul flights:
[0100] ;
[0101] ;
[0102] In the formula, Represents the weight matrix of the placed goods; Represents the goods placement matrix. If cargo l is placed in hold h, then Otherwise, it is 0; H represents the cargo space; L represents the cargo collection; This indicates the pre-allocation result. This indicates that if cargo l has a pre-allocation result in hold h, then ,on the contrary This constraint means that pre-allocated goods are guaranteed to be allocated according to the pre-allocation plan.
[0103] Luggage obstruction restrictions: ;
[0104] In the formula, Represents the goods placement matrix. If cargo l is placed in hold h, then Otherwise, it is 0; H represents the cabin class; LU represents the baggage collection; this constraint means that long-haul baggage in the same cabin class will not obstruct short-haul cargo.
[0105] Cargo delivery sequence constraints: ;
[0106] In the formula, Represents the goods placement matrix; This constraint indicates the order in which goods are pulled; PN represents the total number of goods that can be pulled; this constraint means that goods are guaranteed to be pulled in the order they are pulled.
[0107] ;
[0108] In the formula, L represents the cargo matrix; L represents the cargo set. This indicates the order in which goods can be pulled; PN represents the total number of goods that can be pulled; this constraint means that goods not in the pulling order must not be pulled.
[0109] Cargo arrival station constraints: ;
[0110] In the formula, H represents the cargo placement matrix; LL represents the long-haul cargo set; LS represents the short-haul cargo set; this constraint means that for certain terminals, the same cargo space can only have cargo destined for the same destination.
[0111] S130 determines the flight configuration parameters and weight configuration parameters of the target aircraft based on the load objective function and constraints.
[0112] The flight configuration parameters include at least one of the following: aircraft reference baseline, mean aerodynamic chord length, etc.
[0113] The weight configuration parameters include at least one of the following: takeoff weight, cargo weight, etc.
[0114] Specifically, in this embodiment, the load objective function can be solved. During the solution process, constraints are considered to ensure that the solution results meet the constraints. Furthermore, the parameters in the solution results are used as the flight configuration parameters and weight configuration parameters of the target aircraft.
[0115] It should be noted that this application does not impose any limitations on the solution method or process for the loading objective function. For example, Benders decomposition can be used for iterative solution.
[0116] S140 determines the flight load plan for the target aircraft based on flight configuration parameters and weight configuration parameters.
[0117] In one alternative implementation, flight configuration parameters and weight configuration parameters can be directly used as the flight load scheme for the target aircraft.
[0118] In another alternative implementation, to improve the feasibility of the flight load planning scheme, if both the flight configuration parameters and weight configuration parameters meet the flight configuration standards, the flight load planning scheme for the target aircraft can be determined based on these parameters. In this way, the flight load planning scheme for the target aircraft throughout the entire journey complies with safety standards, and only when it meets these standards is it put into use, thus improving the flight safety of the target aircraft.
[0119] The flight configuration standards and weight configuration standards can be developed based on experience, and this application does not impose any restrictions on them.
[0120] In the aforementioned intelligent loading method for bulk cargo hold passenger aircraft, the objective is to minimize the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity. A loading objective function for the target aircraft is constructed. During the solution process for this objective function, based on the objective function and constraints, the flight configuration parameters and weight configuration parameters of the target aircraft are determined. Finally, based on these parameters, the flight loading scheme for the target aircraft is determined. Compared to traditional manual loading schemes, this method enables the automatic generation of flight loading schemes and improves their accuracy.
[0121] Based on the technical solutions of the above embodiments, this application also provides an optional embodiment. In this optional embodiment, the load objective function includes a first objective function and a second objective function. In this case, the process of constructing the load objective function corresponding to the target aircraft with the objective of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity is refined.
[0122] See Figure 2 The steps for constructing the load objective function shown include:
[0123] S210, with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity, constructs the first objective function corresponding to the target aircraft.
[0124] In one optional implementation, the takeoff operating parameters and takeoff reference baseline of the target aircraft can be obtained; the takeoff reference baseline includes a first-class baseline and a second-class baseline; the difference between the takeoff operating parameters and the first-class baseline is used as the first variable, and the second-class baseline is used as the second variable. Based on the ratio of the first variable to the second variable, the actual center of gravity of the target aircraft is determined; the objective is to minimize the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity, and a first objective function corresponding to the target aircraft is constructed.
[0125] Among them, takeoff operating parameters can be understood as takeoff index; Type I baseline can be understood as the leading edge of mean aerodynamic chord; Type II baseline can be understood as mean aerodynamic chord length.
[0126] For example, the actual center of gravity of the target aircraft can be as follows:
[0127] ;
[0128] In the formula, The target aircraft's actual center of gravity is represented by TKI; takeoff index is represented by NNC, which is a non-negative constant; CC is represented by the conversion constant; TKW is represented by takeoff weight; RB is represented by the aircraft reference baseline; LEMAC is represented by the mean aerodynamic chord leading edge; and MAC is represented by the mean aerodynamic chord length.
[0129] in, TKI represents the takeoff index; ZFI represents the zero-fuel index; TWI represents the takeoff fuel index correction. ZFI represents the zero-oil index; HI represents the cargo hold index; DOI represents the adjusted operating index; CI represents the passenger cabin index. HI indicates the cargo hold index; This represents the weight matrix for cargo placement; H represents the cargo hold; CPK represents the index per kilogram.
[0130] Accordingly, the first objective function can be as follows:
[0131] ;
[0132] In the formula, TKGC represents the actual center of gravity of the target aircraft; TKIA represents the rear edge of the takeoff index envelope; and TKIL represents the front edge of the takeoff index envelope.
[0133] S220 constructs a second objective function for the target aircraft, with the goal of minimizing the penalty value corresponding to the target aircraft's payload configuration parameters.
[0134] In one alternative implementation, a penalty score can be determined based on a preset penalty score function and the cargo placement location of the target aircraft to determine the penalty score corresponding to the target aircraft's cargo configuration parameters in different dimensions; with the goal of minimizing the sum of the penalty scores corresponding to the target aircraft's cargo configuration parameters in different dimensions, a second objective function corresponding to the target aircraft is constructed.
[0135] For example, the preset penalty value determination function may include at least one of the following:
[0136] First penalty point determination function: ;
[0137] In the formula, PEN1 represents the first penalty point; LU represents baggage collection; Let represent the cargo placement matrix; HD represent the set of cargo door positions; and HB represent the set of rear cargo doors. The first penalty value determination function is used to constrain baggage on one-way flights to be placed in the rear cargo door positions as much as possible.
[0138] Second penalty point determination function: ;
[0139] In the formula, PEN2 represents the second penalty point; HB represents the cargo placement matrix; HF represents the aft hold set; and HF represents the forward hold set. The second penalty value determination function is used to constrain cargo to be placed in the forward or aft hold as much as possible after palletizing.
[0140] Third penalty point determination function:
[0141] ;
[0142] In the formula, PEN3 represents the third penalty point; LU represents the cargo placement matrix; H represents the baggage set; and the third penalty value determination function is used to constrain the target aircraft to avoid dismantling its cargo hold as much as possible.
[0143] Fourth penalty point determination function:
[0144] ;
[0145] In the formula, PEN4 represents the fourth penalty point; represents the cargo placement matrix; LU represents the baggage set; HF represents the front cabin set; LL represents the long-haul cargo set; LS represents the short-haul cargo set; the fourth penalty value determination function is used to constrain the front cabin to contain as little baggage as possible that has connecting flights to different destinations.
[0146] Fifth penalty point determination function:
[0147] ;
[0148] In the formula, PEN5 represents the fifth penalty point; LU represents the cargo placement matrix; LL represents the baggage set; LS represents the long-haul cargo set; HB represents the aft cabin set; the fifth penalty value determination function is used to constrain the aft cabin to contain as little baggage as possible from connecting flights to different destinations.
[0149] Sixth penalty point determination function: ;
[0150] In the formula, PEN6 represents the sixth penalty point; Let L represent the cargo matrix; L represents the cargo set; the sixth penalty score determination function is used to constrain cargo to be pulled as little as possible.
[0151] Accordingly, the function for determining the preset penalty value can be as follows:
[0152] ;
[0153] In the formula, PEN represents the total penalty points; i This represents the function that determines the i-th penalty value; This represents the weight coefficient corresponding to the function that determines the i-th penalty value.
[0154] In the above embodiments, considering penalty points when constructing the load objective function can make the flight configuration parameters and weight configuration parameters of the target aircraft obtained based on the load objective function more reliable.
[0155] Accordingly, the loading objective function can be as follows:
[0156] ;
[0157] In the formula, TKGC represents the actual center of gravity of the target aircraft; TKIA represents the trailing edge of the takeoff index envelope; TKIL represents the leading edge of the takeoff index envelope; and PEN represents the total penalty points.
[0158] Based on the technical solutions of the above embodiments, this application also provides an optional embodiment. In this optional embodiment, the intelligent loading method for bulk cargo hold passenger aircraft provided by this application is described in detail.
[0159] See Figure 3A The intelligent load planning method for the bulk cargo hold type of passenger aircraft shown includes:
[0160] S310: Obtain the takeoff operating parameters and takeoff reference baseline of the target aircraft; the takeoff reference baseline includes Type I baseline and Type II baseline;
[0161] S320 uses the difference between the takeoff operating parameters and the first type of baseline as the first variable and the second type of baseline as the second variable. Based on the ratio of the first variable to the second variable, the actual center of gravity of the target aircraft is determined.
[0162] S330, with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity, constructs the first objective function corresponding to the target aircraft;
[0163] S340, based on the preset penalty value determination function and the cargo placement position of the target aircraft, determines the penalty value corresponding to the target aircraft's cargo configuration parameters in different dimensions;
[0164] S350, with the goal of minimizing the sum of penalty values corresponding to the target aircraft's payload configuration parameters in different dimensions, constructs a second objective function for the target aircraft;
[0165] S360, determine the load allocation objective function based on the first objective function and the second objective function;
[0166] S370, Determine the constraints corresponding to the load objective function;
[0167] The constraints include at least one of the following: a first constraint constraining the flight performance envelope of the target aircraft; a second constraint constraining the weight and placement of the cargo carried by the target aircraft; and a third constraint constraining the cabin-related data of the target aircraft.
[0168] S380 determines the flight configuration parameters and weight configuration parameters of the target aircraft based on the load objective function and constraints.
[0169] S390 determines the flight load plan for the target aircraft based on the flight configuration parameters and weight configuration parameters, provided that the flight configuration parameters and weight configuration parameters meet the flight configuration standards.
[0170] In short, the intelligent loading method for bulk cargo hold passenger aircraft provided in this application embodiment can be applied to, for example... Figure 3B The algorithm architecture diagram shown includes the following components:
[0171] The first part is the data processing engine, which automatically breaks down baggage according to business input requirements and dynamically constructs indices, constraints, and penalty points based on factors such as aircraft type, route, cabin, and package, which vary with different flights, so that the algorithm can be widely adapted to different aircraft types.
[0172] The second part is the operations research framework, which will construct a mixed-integer linear programming model based on the output conditions of the first part, and use Benders decomposition to solve iteratively.
[0173] The third part is the result verification module, which performs rule verification on the results of the operations research framework to ensure that they meet safety standards before submitting them to the load allocation system.
[0174] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.
[0175] Based on the same inventive concept, this application also provides an intelligent loading device for a bulk cargo hold passenger aircraft, which implements the intelligent loading method for the bulk cargo hold passenger aircraft described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the intelligent loading device for bulk cargo hold passenger aircraft provided below can be found in the limitations of the intelligent loading method for bulk cargo hold passenger aircraft described above, and will not be repeated here.
[0176] In one exemplary embodiment, such as Figure 4 As shown, an intelligent loading device for a bulk cargo hold passenger aircraft is provided, comprising: a function construction module 410, a constraint determination module 420, a first determination module 430, and a second determination module 440, wherein:
[0177] The function construction module 410 is used to construct the load objective function corresponding to the target aircraft with the objective of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0178] The constraint determination module 420 is used to determine the constraint conditions corresponding to the load objective function;
[0179] The first determining module 430 is used to determine the flight configuration parameters and weight configuration parameters of the target aircraft based on the load objective function and constraints.
[0180] The second determining module 440 is used to determine the flight load scheme of the target aircraft based on flight configuration parameters and weight configuration parameters.
[0181] In one embodiment, the loading objective function includes a first objective function and a second objective function; correspondingly, such as Figure 5 As shown, the function construction module 410 includes a first construction unit 4101, which is used to construct a first objective function corresponding to the target aircraft with the objective of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity; and a second construction unit 4102, which is used to construct a second objective function corresponding to the target aircraft with the objective of minimizing the penalty value corresponding to the load configuration parameters of the target aircraft.
[0182] In one embodiment, the first construction unit includes an acquisition subunit for acquiring the takeoff operating parameters and takeoff reference baseline of the target aircraft; the takeoff reference baseline includes a first-class baseline and a second-class baseline; a first determination subunit for determining the actual center of gravity of the target aircraft based on the ratio of the first variable to the second variable, using the difference between the takeoff operating parameters and the first-class baseline as a first variable and the second-class baseline as a second variable; and a first construction subunit for constructing a first objective function corresponding to the target aircraft with the objective of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0183] In one embodiment, the second construction unit includes a second determining subunit, used to determine the penalty values corresponding to the target aircraft's carrying configuration parameters in different dimensions based on a preset penalty value determination function and the cargo placement position of the target aircraft; the second construction subunit is used to construct a second objective function corresponding to the target aircraft with the objective of minimizing the sum of the penalty values corresponding to the target aircraft's carrying configuration parameters in different dimensions.
[0184] In one embodiment, the constraint determination module 420 is used to determine the constraint conditions corresponding to the load objective function; the constraint conditions include at least one of the following: a first constraint condition constraining the flight performance envelope of the target aircraft; a second constraint condition constraining the weight and placement position of the cargo carried by the target aircraft; and a third constraint condition constraining the cabin-related data of the target aircraft.
[0185] In one embodiment, the second determining module 440 is specifically used to determine the flight load scheme of the target aircraft based on the flight configuration parameters and the weight configuration parameters, provided that the flight configuration parameters meet the flight configuration standards and the weight configuration parameters meet the weight configuration standards.
[0186] The various modules in the intelligent load planning system of the aforementioned bulk cargo hold passenger aircraft can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.
[0187] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements an intelligent loading method for bulk cargo hold-type passenger aircraft. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.
[0188] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0189] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:
[0190] The objective function for the load of the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0191] Determine the constraints corresponding to the load allocation objective function;
[0192] Based on the load objective function and constraints, determine the flight configuration parameters and weight configuration parameters of the target aircraft;
[0193] Based on flight configuration parameters and weight configuration parameters, determine the flight load plan for the target aircraft.
[0194] In one embodiment, the processor, when executing a computer program, also performs the following steps:
[0195] The first objective function for the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0196] With the goal of minimizing the penalty value corresponding to the target aircraft's payload configuration parameters, a second objective function is constructed for the target aircraft.
[0197] In one embodiment, the processor, when executing a computer program, also performs the following steps:
[0198] Obtain the takeoff operating parameters and takeoff reference baseline of the target aircraft; the takeoff reference baseline includes Class I baseline and Class II baseline;
[0199] The difference between the takeoff operating parameters and the first type of baseline is used as the first variable, and the second type of baseline is used as the second variable. The actual center of gravity of the target aircraft is determined based on the ratio of the first variable to the second variable.
[0200] The first objective function for the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0201] In one embodiment, the processor, when executing a computer program, also performs the following steps:
[0202] Based on the preset penalty score determination function and the cargo placement location of the target aircraft, the penalty score corresponding to the target aircraft's cargo configuration parameters in different dimensions is determined.
[0203] The objective function for the target aircraft is to minimize the sum of penalty values corresponding to the target aircraft's payload configuration parameters in different dimensions.
[0204] In one embodiment, the processor, when executing a computer program, also performs the following steps:
[0205] If the flight configuration parameters meet the flight configuration standards and the weight configuration parameters meet the weight configuration standards, the flight load plan for the target aircraft is determined based on the flight configuration parameters and the weight configuration parameters.
[0206] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:
[0207] The objective function for the load of the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0208] Determine the constraints corresponding to the load allocation objective function;
[0209] Based on the load objective function and constraints, determine the flight configuration parameters and weight configuration parameters of the target aircraft;
[0210] Based on flight configuration parameters and weight configuration parameters, determine the flight load plan for the target aircraft.
[0211] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:
[0212] The first objective function for the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0213] With the goal of minimizing the penalty value corresponding to the target aircraft's payload configuration parameters, a second objective function is constructed for the target aircraft.
[0214] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:
[0215] Obtain the takeoff operating parameters and takeoff reference baseline of the target aircraft; the takeoff reference baseline includes Class I baseline and Class II baseline;
[0216] The difference between the takeoff operating parameters and the first type of baseline is used as the first variable, and the second type of baseline is used as the second variable. The actual center of gravity of the target aircraft is determined based on the ratio of the first variable to the second variable.
[0217] The first objective function for the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0218] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:
[0219] Based on the preset penalty score determination function and the cargo placement location of the target aircraft, the penalty score corresponding to the target aircraft's cargo configuration parameters in different dimensions is determined.
[0220] The objective function for the target aircraft is to minimize the sum of penalty values corresponding to the target aircraft's payload configuration parameters in different dimensions.
[0221] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:
[0222] If the flight configuration parameters meet the flight configuration standards and the weight configuration parameters meet the weight configuration standards, the flight load plan for the target aircraft is determined based on the flight configuration parameters and the weight configuration parameters.
[0223] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:
[0224] The objective function for the load of the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0225] Determine the constraints corresponding to the load allocation objective function;
[0226] Based on the load objective function and constraints, determine the flight configuration parameters and weight configuration parameters of the target aircraft;
[0227] Based on flight configuration parameters and weight configuration parameters, determine the flight load plan for the target aircraft.
[0228] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:
[0229] The first objective function for the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0230] With the goal of minimizing the penalty value corresponding to the target aircraft's payload configuration parameters, a second objective function is constructed for the target aircraft.
[0231] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:
[0232] Obtain the takeoff operating parameters and takeoff reference baseline of the target aircraft; the takeoff reference baseline includes Class I baseline and Class II baseline;
[0233] The difference between the takeoff operating parameters and the first type of baseline is used as the first variable, and the second type of baseline is used as the second variable. The actual center of gravity of the target aircraft is determined based on the ratio of the first variable to the second variable.
[0234] The first objective function for the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
[0235] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:
[0236] Based on the preset penalty score determination function and the cargo placement location of the target aircraft, the penalty score corresponding to the target aircraft's cargo configuration parameters in different dimensions is determined.
[0237] The objective function for the target aircraft is to minimize the sum of penalty values corresponding to the target aircraft's payload configuration parameters in different dimensions.
[0238] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:
[0239] If the flight configuration parameters meet the flight configuration standards and the weight configuration parameters meet the weight configuration standards, the flight load plan for the target aircraft is determined based on the flight configuration parameters and the weight configuration parameters.
[0240] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.
[0241] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.
[0242] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.
[0243] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.
Claims
1. A smart loading method for bulk cargo hold passenger aircraft, characterized in that, The method includes: The target aircraft's load objective function is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity. Determine the constraints corresponding to the load allocation objective function; Based on the load objective function and the constraints, determine the flight configuration parameters and weight configuration parameters of the target aircraft; Based on the flight configuration parameters and the weight configuration parameters, the flight load plan for the target aircraft is determined.
2. The method according to claim 1, characterized in that, The load allocation objective function includes a first objective function and a second objective function; correspondingly, constructing the load allocation objective function for the target aircraft with the objective of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity includes: A first objective function for the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity. With the goal of minimizing the penalty value corresponding to the load configuration parameters of the target aircraft, a second objective function corresponding to the target aircraft is constructed.
3. The method according to claim 2, characterized in that, The first objective function for constructing the target aircraft, with the objective of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity, includes: Obtain the takeoff operating parameters and takeoff reference baseline of the target aircraft; the takeoff reference baseline includes a first-class baseline and a second-class baseline; The difference between the takeoff operating parameters and the first type of baseline is used as the first variable, and the second type of baseline is used as the second variable. The actual center of gravity of the target aircraft is determined based on the ratio of the first variable to the second variable. The first objective function corresponding to the target aircraft is constructed with the goal of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity.
4. The method according to claim 2, characterized in that, The step of constructing a second objective function for the target aircraft, with the goal of minimizing the penalty value corresponding to the target aircraft's payload configuration parameters, includes: Based on the preset penalty score determination function and the cargo placement location of the target aircraft, the penalty score corresponding to the cargo configuration parameters of the target aircraft in different dimensions is determined. The second objective function for the target aircraft is constructed with the goal of minimizing the sum of penalty values corresponding to the load configuration parameters of the target aircraft in different dimensions.
5. The method according to any one of claims 1-4, characterized in that, The constraints include at least one of the following: The first constraint condition constrains the flight performance envelope of the target aircraft; A second constraint condition that restricts the weight and placement of the cargo carried by the target aircraft; The third constraint condition constrains the cabin-related data of the target aircraft.
6. The method according to any one of claims 1-4, characterized in that, The step of determining the flight load plan for the target aircraft based on the flight configuration parameters and the weight configuration parameters includes: If the flight configuration parameters meet the flight configuration standards and the weight configuration parameters meet the weight configuration standards, the flight load plan for the target aircraft is determined based on the flight configuration parameters and the weight configuration parameters.
7. An intelligent loading device for a bulk cargo hold-type passenger aircraft, characterized in that, The device includes: The function construction module is used to construct the load objective function corresponding to the target aircraft with the objective of minimizing the difference between the actual center of gravity of the target aircraft and the preset theoretical center of gravity. The constraint determination module is used to determine the constraint conditions corresponding to the loading objective function; The first determining module is used to determine the flight configuration parameters and weight configuration parameters of the target aircraft based on the load objective function and the constraint conditions. The second determining module is used to determine the flight load scheme of the target aircraft based on the flight configuration parameters and the weight configuration parameters.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-6.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-6.