Aviation encasement matching optimization method based on dynamic cargo quantity analysis
By optimizing air cargo container configuration through dynamic cargo volume analysis and adaptive algorithms, the problems of low resource utilization and insufficient dynamic response in traditional technologies have been solved, achieving efficient, safe and controllable container management for air freight, and improving space utilization and overall loading efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-06
- Publication Date
- 2026-04-17
AI Technical Summary
Traditional aviation container fitting technology relies on manual experience, resulting in low resource utilization, lack of full-process control and traceability mechanisms, and inability to dynamically respond to real-time changes in aviation cargo space requirements, leading to low space utilization, high operating costs, and insufficient safety.
The air cargo loading and matching optimization method based on dynamic cargo volume analysis obtains real-time air cargo space demand data and package attributes, and combines dynamic priority matching and adaptive new container allocation algorithms to achieve the optimal loading strategy. It also adopts a two-dimensional adaptive scoring mechanism to optimize resource allocation.
It enables real-time dynamic management of air cargo space, improves space utilization and loading efficiency, reduces the risk of overloading and underloading, increases the rate of achieving the target load ratio and overall loading efficiency, and ensures the optimal balance between safety and operating costs.
Smart Images
Figure CN121882887A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of aircraft container configuration optimization, and more particularly to an aircraft container configuration optimization method based on dynamic cargo volume analysis. Background Technology
[0002] In the field of air cargo transportation, with the rapid development of global trade and the booming growth of e-commerce, air freight has become an indispensable and important component of the modern logistics system. However, the air cargo loading process faces many challenges, mainly reflected in the heterogeneity of cargo volume, weight, and shape, the complex structure of aircraft cargo hold space, and multiple constraints such as load balance and safety requirements. These factors often make it difficult for traditional loading methods to maximize space utilization, resulting in wasted capacity and increased operating costs.
[0003] Traditional air cargo container matching technology is ill-equipped to handle the dynamic and uncertain nature of reality. It also suffers from problems such as reliance on manual experience, low utilization of air cargo space resources, lack of full-process control and traceability mechanisms in the container packing process, and inability to dynamically respond to real-time changes in air cargo space requirements. Therefore, there is an urgent need for a flexible and efficient solution to promote the transformation of air cargo towards intelligence and green practices, and to achieve the optimal balance between maximizing space utilization, minimizing costs, and ensuring safety. Summary of the Invention
[0004] This invention provides an air cargo loading and matching optimization method based on dynamic cargo volume analysis to solve the technical problems of traditional air cargo loading and matching technology, such as reliance on manual experience, low utilization rate of air cargo space resources, lack of full-process control and traceability mechanism in the loading process, and inability to dynamically respond to real-time changes in air cargo space demand.
[0005] The present invention provides an air cargo container matching optimization method based on dynamic cargo volume analysis, comprising the following steps: S1. Real-time acquisition of dynamic demand data for air cargo space, collection of physical attributes of packages, calculation of the remaining actual weight of cargo space intervals and the remaining upper limit of the compliant weight of cargo space intervals. S2. Based on the physical attributes of the package and combined with the remaining weight limit of the warehouse space, a dynamic priority matching and adaptive new box allocation algorithm is introduced to determine the optimal packing strategy for the currently processed single package in real time, obtain the recommended shipping box, and verify the packing. After the verification is successful, the association between the current package and the recommended shipping box is established.
[0006] Preferably, S1 specifically includes: The dynamic demand data for air cargo space includes the division of cargo space into zones, the set of carton specifications that can be used in the zone, the current cumulative actual weight of the cargo space zone, the target cutoff weight, and the cargo space zone's throughput threshold; the physical attributes of the parcels include the parcel's actual weight, length, width, and height, and the parcel's unique identification code.
[0007] Preferably, S1 specifically includes: Based on the target cutoff weight and the current accumulated actual weight of the storage area, calculate the remaining actual weight of the storage area; when the remaining actual weight is equal to zero, mark the storage area as full; when the remaining actual weight is greater than zero, introduce the aviation standard volumetric weight coefficient, calculate and accumulate the volumetric weight of all cartons allocated to the storage area, and combine it with the storage area's load-bearing ratio threshold to calculate the upper limit of the remaining compliant weight of the storage area.
[0008] Preferably, S2 specifically includes: When the remaining maximum weight limit of the storage space is greater than 0, it indicates that the shipping box is not full. In the implementation of the dynamic priority matching and adaptive new box allocation algorithm, all current unsealed shipping boxes are traversed. Combining the dynamic demand data of air cargo space, the physical attributes of the packages and the remaining maximum weight limit of the storage space, hard constraints including specification matching constraints, space limit constraints and remaining capacity constraints are constructed. Based on the hard constraints, a candidate set of unsealed shipping boxes is selected and generated.
[0009] Preferably, S2 specifically includes: In the implementation of the dynamic priority matching and adaptive new box allocation algorithm, when the candidate unsealed shipping box set is not empty, a two-dimensional adaptive scoring mechanism is introduced to evaluate the priority.
[0010] Preferably, S2 specifically includes: In the implementation of the dual-dimensional adaptive scoring mechanism, the first part is based on the remaining upper limit of the qualified weight of the warehouse space to which the candidate unsealed shipping box belongs, combined with the actual weight of the package in the physical attributes of the package, to reflect the filling efficiency; the second part is based on the dynamic demand data of the warehouse space to which the candidate unsealed shipping box belongs, combined with the remaining actual weight of the warehouse space to which the candidate unsealed shipping box belongs, to reflect the urgency of the space and the priority of light goods; the two parts are added together to obtain the total priority score, and the candidate unsealed shipping box with the highest total priority score is used as the recommended shipping box.
[0011] Preferably, S2 specifically includes: In the implementation of the dynamic priority matching and adaptive new box allocation algorithm, when the candidate unsealed shipping box set is empty, a new shipping box is created and a unique identifier is generated for the new shipping box; all warehouse locations, all intervals, and all allowed carton specification sets are traversed, and the same hard constraints as above are used for filtering to obtain the candidate warehouse location-interval-carton specification set; based on the candidate warehouse location-interval-carton specification set, a two-dimensional adaptive scoring mechanism is adopted to select the optimal warehouse location and interval. After determining the optimal interval, the carton with the smallest volume is selected as the recommended shipping box from the allowed carton specification set of the selected warehouse location and interval.
[0012] Preferably, S2 specifically includes: Based on the unique identifier of the recommended shipping box, combined with the unique identifier of the package, it is verified whether it is the current recommended shipping box. After successful verification, the association between the current package and the recommended shipping box is established, and the cumulative actual weight inside the recommended shipping box and the remaining compliant weight limit of the storage space are updated.
[0013] The beneficial effects of the technical solution of the present invention are: 1. It enables real-time dynamic management and precise control of remaining capacity in air cargo space, avoiding overloading, underloading, or failure to meet the throw ratio caused by traditional static allocation, and significantly improving space utilization and overall loading efficiency.
[0014] 2. By collecting the physical attributes of packages in real time and linking them with the dynamic demand data of air cargo space, the remaining actual weight and the remaining upper limit of the standard weight can be accurately calculated. This effectively prevents the continued allocation of packages to areas that are already saturated or whose weight ratio is about to fall short of the standard, reducing the risk of rejection, fines and operational risks for airlines due to overweight or non-compliance with weight ratio standards.
[0015] 3. The dynamic priority matching and adaptive new box allocation algorithm realizes intelligent and real-time optimal packing decision for the current package. It prioritizes unsealed or newly opened packing solutions that contribute the most to the interval's compliance, have the highest space utilization, and the highest interval urgency, making the combination of light and heavy goods more scientific and significantly improving the overall load ratio compliance rate.
[0016] 4. The dual-dimensional adaptive scoring mechanism takes into account both filling efficiency and interval urgency, giving higher priority to tight intervals and light cargo, and realizing the tilting of resources towards the "most needed" warehouse intervals. This effectively solves the imbalance problem caused by the traditional "first-come, first-served" or manual allocation, and ensures that the overall cargo throughput ratio meets the standard. Attached Figure Description
[0017] Figure 1 This is a flowchart of an air cargo container matching optimization method based on dynamic cargo volume analysis, as described in this invention. Detailed Implementation
[0018] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0020] The following description, in conjunction with the accompanying drawings, details a specific scheme for an aviation container matching optimization method based on dynamic cargo volume analysis provided by this invention.
[0021] See attached document Figure 1 The diagram illustrates a flowchart of an air cargo container matching optimization method based on dynamic cargo volume analysis, provided by an embodiment of the present invention. The method includes the following steps: S1. Real-time acquisition of dynamic demand data for air cargo space, collection of physical attributes of packages, calculation of the remaining actual weight of cargo space intervals and the remaining upper limit of the compliant weight of cargo space intervals. Real-time acquisition of dynamic demand data for current air cargo space and collection of package physical attributes; specifically, real-time acquisition or maintenance of zone demand tables for each cargo space from airline or freight forwarder systems, including the zone division of cargo space, the set of carton specifications allowed for use within each zone, and carton specifications including fixed lengths. ,width ,high The current accumulated actual weight (i.e., the initial weight) of the storage range. Target cutoff weight And the threshold for the sell ratio within the position range. ,in, Indicates position index. Indicates the first The interval index for each warehouse location; simultaneously, for the current package entering the packing process, the actual weight of the package is obtained using weighing equipment. The length of the package can be obtained using a 3D scanner or camera. ,width ,high and read the package's unique identifier. The original volume of the package is obtained by multiplying its length, width, and height in three dimensions. , This indicates the package index.
[0022] For each interval of each position, set the target cutoff weight. Subtract the starting weight This yields the remaining actual weight for each interval of each warehouse. If the remaining actual weight is zero, the storage area is marked as full, and no new cartons will be allocated to the full storage area to avoid overloading. If the remaining actual weight is greater than zero, the volume of the shipping box is calculated by multiplying the length, width, and height of each type of carton. The volumetric weight of all cartons (including sealed and unsealed) allocated to the storage area is accumulated. The accumulated volumetric weight is divided by the storage area's throughput threshold to obtain the maximum allowable actual weight to meet the threshold. The accumulated actual weight in the current storage area is then subtracted from the maximum allowable actual weight. When the difference is greater than 0, this difference is the upper limit of the remaining throughput threshold for the current storage area. When the difference is less than or equal to 0, the upper limit of the remaining throughput threshold for the current storage area is zero, indicating that loading any weight in the current state will cause the throughput to fall below the throughput threshold. The formula is expressed as follows: in Indicates position interval The remaining maximum weight limit for compliance; This indicates that the calculated value within the parentheses is taken as the maximum value between 0 and 0, to prevent negative values and ensure that the remaining upper limit of the target weight is always non-negative; This is the standard volumetric weight factor for aviation, set according to aviation transport standards, such as... ; This indicates all positions that have been allocated. interval The total volume of the shipping boxes (including sealed and unsealed boxes); Indicates allocation to positions interval The The volume of each shipping box; Indicates position interval All shipping boxes (including sealed and unsealed boxes); This indicates the maximum permissible actual weight to be exactly in line with the standard; If the remaining maximum weight limit is zero, the storage area is marked as full, and no new cartons will be allocated to the full storage area to avoid overloading caused by continuing to allocate to saturated storage areas.
[0023] S2. Based on the physical attributes of the package and combined with the remaining weight limit of the warehouse space, a dynamic priority matching and adaptive new box allocation algorithm is introduced to determine the optimal packing strategy for the currently processed single package in real time, obtain the recommended shipping box, and verify the packing. After the verification is successful, the association between the current package and the recommended shipping box is established.
[0024] When the remaining maximum weight limit is greater than 0, meaning the shipping box is not full, a dynamic priority matching and adaptive new box allocation algorithm is introduced to determine the optimal packing strategy for the currently processed single package in real time: It prioritizes placing the package into an existing unsealed shipping box; if no suitable unsealed shipping box can be found, a new shipping box is opened, and the optimal storage space and carton size are selected simultaneously. Specifically: Iterate through all the current unsealed shipping boxes and check whether each one meets the three hard constraints, including specification matching constraint, range compliance constraint, and remaining capacity constraint. Only unsealed shipping boxes that meet all three constraints are included in the candidate unsealed shipping box set. The specification matching constraint is based on the length, width, and height of the existing packages in the shipping box and the length, width, and height of the current package. It uses existing 3D packing algorithms to make a 3D packing feasibility judgment to verify whether the current package can fit into the remaining space of the shipping box, rather than simply comparing the original dimensions of the shipping box. The aforementioned range compliance constraint means that after the current package is added, the remaining compliance weight limit of the warehouse space to which the unsealed shipping box belongs cannot be exceeded. The remaining capacity constraint means that after adding the current package, the cumulative weight of the unsealed shipping boxes plus the cumulative weight of the sealed shipping boxes in the storage area cannot exceed the target cutoff weight of the area.
[0025] Furthermore, if the candidate set of unsealed shipping boxes is not empty, it will directly proceed to the priority evaluation stage: The priority evaluation process employs a two-dimensional adaptive scoring mechanism: The first part reflects the filling efficiency, which is calculated by dividing the actual weight of the current package by the remaining maximum weight of the unsealed shipping box in the storage space. The larger the value, the greater the contribution of the current package to filling the remaining maximum weight of the storage space, and the more worthy it is to be prioritized. The second part reflects the urgency of the interval and the priority of light cargo. That is, the sell ratio threshold of the warehouse interval is multiplied by an inverse amplification factor based on the proportion of remaining capacity. The inverse amplification factor is calculated by the ratio of the remaining actual weight of the warehouse interval to the target cut-off weight. When the proportion of remaining actual weight is smaller, that is, the more urgent the interval is, the larger the inverse amplification factor is, so that the interval with a higher sell ratio threshold and more urgent remaining capacity will receive higher priority score. The total priority score is obtained by adding the two parts. The candidate unsealed shipping box with the highest total priority score is selected as the best candidate unsealed shipping box. The calculation formula is as follows: in, This indicates the selected best candidate unsealed shipping box; This means selecting the candidate unsealed shipping box that maximizes the value of the expression within the parentheses from all candidate unsealed shipping boxes. ; Indicates the first The actual weight of the package; Indicates candidate unsealed shipping box Position interval The current remaining maximum weight limit for meeting the standard; It is a very small positive number, used to prevent division by zero, and can take values of... ; Indicates candidate unsealed shipping box Position interval The threshold for achieving the target throw ratio; Indicates candidate unsealed shipping box Position interval The current remaining actual weight; Indicates candidate unsealed shipping box Position interval Target cutoff weight; Indicates the reciprocal amplification factor; If the best candidate unsealed shipping box is found If so, the best candidate unsealed shipping box will be used directly as the recommended shipping box; If the candidate unsealed shipping box set is empty, proceed directly to the new shipping box development stage. Generate a unique identifier for the new shipping box, traverse all warehouse locations, all zones, and all allowed carton specification sets, and filter them using the same three hard constraints to obtain the candidate warehouse location-zone-carton specification set. Again, use a two-dimensional adaptive scoring mechanism to select the optimal warehouse location and zone to ensure that the newly developed shipping box can not only accommodate the current package, but also bring the greatest subsequent filling potential and target achievement efficiency to the selected warehouse location and zone. After determining the optimal range, the next step is to select the carton size. From the set of allowed carton sizes in the selected warehouse range, the carton with the smallest volume is selected as the recommended shipping carton, which helps to improve the flexibility of subsequent loading. The unique identifier and carton specifications of the currently recommended shipping box are displayed on the employee's PDA or packing table. The employee scans the unique identifier of the currently recommended shipping box and then scans the unique identifier of the package to verify in real time whether it is the currently recommended shipping box. If it does not meet the requirements, the operation is locked and the supervisor is required to confirm, thus implementing a mandatory restriction. After successful verification, the association between the current package and the recommended shipping box is automatically established to ensure full traceability, and the cumulative actual weight inside the recommended shipping box and the remaining compliant weight limit of the storage space are updated.
[0026] In the above scheme, all measurement data involving length (such as length, width, etc.) are uniformly converted to meters, and all measurement data involving weight (such as the actual weight of the package, etc.) are uniformly converted to kilograms. This aims to eliminate multidimensional problems and ensure that all physical quantities have a consistent numerical scale in subsequent analysis.
[0027] In summary, a method for optimizing air cargo container configuration based on dynamic cargo volume analysis has been developed.
[0028] The order of the embodiments is for illustrative purposes only and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.
[0029] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
[0030] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.
Claims
1. A method for optimizing air cargo container configuration based on dynamic cargo volume analysis, characterized in that, Includes the following steps: S1. Real-time acquisition of dynamic demand data for air cargo space, collection of physical attributes of packages, calculation of the remaining actual weight of cargo space intervals and the remaining upper limit of the standard weight of cargo space intervals. S2. Based on the physical attributes of the package and combined with the remaining weight limit of the warehouse space, a dynamic priority matching and adaptive new box allocation algorithm is introduced to determine the optimal packing strategy for the currently processed single package in real time, obtain the recommended shipping box, and verify the packing. After the verification is successful, the association between the current package and the recommended shipping box is established.
2. The method for optimizing air cargo container configuration based on dynamic cargo volume analysis according to claim 1, characterized in that, S1 specifically includes: The dynamic demand data for air cargo space includes the division of cargo space into zones, the set of carton specifications that can be used in the zone, the current cumulative actual weight of the cargo space zone, the target cutoff weight, and the cargo space zone's throughput threshold; the physical attributes of the parcels include the parcel's actual weight, length, width, and height, and the parcel's unique identification code.
3. The method for optimizing air cargo container configuration based on dynamic cargo volume analysis according to claim 2, characterized in that, S1 specifically includes: Based on the target cutoff weight and the current accumulated actual weight of the storage area, calculate the remaining actual weight of the storage area; when the remaining actual weight is equal to zero, mark the storage area as full; when the remaining actual weight is greater than zero, introduce the aviation standard volumetric weight coefficient, calculate and accumulate the volumetric weight of all cartons allocated to the storage area, and combine it with the storage area's load-bearing ratio threshold to calculate the upper limit of the remaining compliant weight of the storage area.
4. The method for optimizing air cargo container configuration based on dynamic cargo volume analysis according to claim 1, characterized in that, S2 specifically includes: When the remaining maximum weight limit of the storage space is greater than 0, it indicates that the shipping box is not full. In the implementation of the dynamic priority matching and adaptive new box allocation algorithm, all current unsealed shipping boxes are traversed. Combining the dynamic demand data of air cargo space, the physical attributes of the packages and the remaining maximum weight limit of the storage space, hard constraints including specification matching constraints, space limit constraints and remaining capacity constraints are constructed. Based on the hard constraints, a candidate set of unsealed shipping boxes is selected and generated.
5. The method for optimizing air cargo container configuration based on dynamic cargo volume analysis according to claim 4, characterized in that, S2 specifically includes: In the implementation of the dynamic priority matching and adaptive new box allocation algorithm, when the candidate unsealed shipping box set is not empty, a two-dimensional adaptive scoring mechanism is introduced to evaluate the priority.
6. The method for optimizing air cargo container configuration based on dynamic cargo volume analysis according to claim 5, characterized in that, S2 specifically includes: In the implementation of the dual-dimensional adaptive scoring mechanism, the first part is based on the remaining upper limit of the qualified weight of the warehouse space to which the candidate unsealed shipping box belongs, combined with the actual weight of the package in the physical attributes of the package, to reflect the filling efficiency; the second part is based on the dynamic demand data of the warehouse space to which the candidate unsealed shipping box belongs, combined with the remaining actual weight of the warehouse space to which the candidate unsealed shipping box belongs, to reflect the urgency of the space and the priority of light goods; the two parts are added together to obtain the total priority score, and the candidate unsealed shipping box with the highest total priority score is used as the recommended shipping box.
7. The method for optimizing air cargo container configuration based on dynamic cargo volume analysis according to claim 5, characterized in that, S2 specifically includes: In the implementation of the dynamic priority matching and adaptive new box allocation algorithm, when the candidate unsealed shipping box set is empty, a new shipping box is created and a unique identifier is generated for the new shipping box; all warehouse locations, all intervals, and all allowed carton specification sets are traversed, and the same hard constraints as above are used for filtering to obtain the candidate warehouse location-interval-carton specification set; based on the candidate warehouse location-interval-carton specification set, a two-dimensional adaptive scoring mechanism is adopted to select the optimal warehouse location and interval. After determining the optimal interval, the carton with the smallest volume is selected as the recommended shipping box from the allowed carton specification set of the selected warehouse location and interval.
8. The method for optimizing air cargo container configuration based on dynamic cargo volume analysis according to claim 7, characterized in that, S2 specifically includes: Based on the unique identifier of the recommended shipping box, combined with the unique identifier of the package, it is verified whether it is the current recommended shipping box. After successful verification, the association between the current package and the recommended shipping box is established, and the cumulative actual weight inside the recommended shipping box and the remaining compliant weight limit of the storage space are updated.