Transportation space optimization system for vulnerable columnar goods

Abstract

The invention discloses a transportation space optimization system for vulnerable columnar goods. The transportation space optimization system is composed of a database module, a Web interaction module, a rear-end module and a loading algorithm calculation module. According to the invention, the transportation space is divided into a plurality of bearing units according to the two-dimensional plane of the bottom surface of the transportation space under the overlooking view angle. Each bearing unit serves as a part of the bottom face area of the transportation space and provides a basis for loading and protective outer packing of the vulnerable columnar goods. The cargo loading position and direction are cooperatively calculated through multiple optimization algorithms such as grid and hexagon arrangement, a genetic algorithm and greedy subset exchange, the carrying capacity of the transportation space is maximized, gaps and unused space are effectively reduced, and the transportation frequency and cost caused by space waste are reduced.

Description

Technical Field

[0001] This invention belongs to the field of combinatorial optimization and heuristic algorithms, and specifically relates to a transportation space optimization system for fragile cylindrical cargo. Background Technology

[0002] Transportation space optimization refers to the planning, calculation, coordination, and improvement of cargo loading schemes within a transportation space to ensure efficient utilization and safe, stable operation of that space. Transportation space optimization must guarantee the optimal cargo layout and the accuracy of information generated and executed in the scheme. However, in reality, fragile cylindrical cargo, due to its shape (cylindrical) and characteristics (in some cases, it cannot be stacked and requires protective outer packaging), presents special requirements for loading. Loading fragile cylindrical cargo requires consideration of multiple constraints, including transportation space size limitations, cargo priority, and load distribution. Optimizing the loading process requires extensive computation while ensuring system response speed. Existing general-purpose cylindrical cargo loading optimization algorithms are not adapted to this special case and require customized design tailored to the characteristics of fragile cylindrical cargo. Summary of the Invention

[0003] The purpose of this invention is to provide a transportation space optimization system for fragile cylindrical goods, addressing their specific characteristics. In this invention, the transportation space is divided into several load-bearing units based on the two-dimensional plane of its bottom surface viewed from above. Each load-bearing unit, as part of the bottom area of ​​the transportation space, provides the foundation for loading and protective packaging of fragile cylindrical goods. The specifications of the load-bearing units are configured according to the dimensions of the bottom surface of the transportation space, achieving efficient utilization and orderly organization of the bottom area, thereby improving loading efficiency, reducing space waste, and lowering transportation costs.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A transportation space optimization system for fragile cylindrical cargo consists of a database module, a web interaction module, a backend module, and a loading algorithm calculation module. The database module is used to store the configuration items required for loading algorithm calculation, the calculation result data after the loading algorithm calculation module, and the PDF file of the transportation space loading plan; The web interaction module includes a configuration management platform and a 3D display platform for transportation space loading schemes. The configuration management platform is responsible for managing the configuration items used during loading calculations and starting the loading calculations. The 3D display platform for transportation space loading schemes is used to display the loading layout of goods in three dimensions and to export PDF files of transportation space loading schemes.

[0005] The backend modules include a data management module, a web communication module, a computing task module, and an export file generation module.

[0006] The loading algorithm calculation module is responsible for calculating the specific loading of goods based on the fragile columnar cargo data, configuration items, and rule items provided by the calculation task module of the backend module, and transmitting the calculated results to the backend module.

[0007] In one possible implementation, the data management module is responsible for managing the calculation configuration items, calculation result data, and PDF files of the transportation space loading scheme in the database, as well as providing the corresponding specification data based on the configuration items when the loading calculation starts. The web communication module is responsible for returning the 3D display coordinate data and indicator data from the calculation result data to the web interaction module. The calculation task module is responsible for scheduling the loading algorithm calculation module. The export file generation module is responsible for generating an exportable transportation space loading scheme PDF file based on the calculation result data.

[0008] In one possible implementation, the configuration items of the transportation space specifications and the configuration items of the carrier unit specifications to which the configuration items belong are configured through the configuration management platform of the Web interaction module, thus completing the initial setup of the system. The specification data of the configuration items will be used for subsequent loading scheme calculations.

[0009] In one possible implementation, the user initiates the loading calculation through the configuration management platform of the web interaction module. First, the user imports data on fragile cylindrical goods, including the specifications and quantity of each type of fragile cylindrical goods. Then, the user selects the required configuration items from the configured transportation space, and then selects the required configuration items from the configuration items of the carrier unit to which the transportation space belongs. Finally, the user configures the rules for the current calculation, including whether multiple goods can be combined and placed, whether assembled carrier units can be merged, and whether the remaining space can be utilized.

[0010] In one possible implementation, the entire system is built on a microservice framework, and the backend computing task module and the loading algorithm computing module communicate with each other via RocketMQ in the form of a message queue.

[0011] In one possible implementation, the backend module's computation task module encapsulates the fragile columnar cargo data, along with its configuration items and rule items, passed from the Web interaction module into a computation task and publishes it to the corresponding message queue.

[0012] In one possible implementation, the loading algorithm operates as follows: First, the loading of fragile columnar goods in the carrying unit is optimized using a grid and hexagonal arrangement algorithm. Then, the already assembled carrying units are optimized for loading in the transportation space using a greedy subset exchange algorithm. If the rules allow for multiple combinations of goods, then dissimilar fragile columnar goods that cannot fill a carrying unit after the grid and hexagonal arrangement algorithm are optimized for multi-specification loading using a genetic algorithm. If the rules allow for merging of assembled carrying units, then the assembled carrying unit merging process is added. If there are still remaining spaces after the assembled carrying units are loaded and the rules allow for the use of remaining space, the module will extract the remaining space in the transportation space and calculate whether there is a suitable horizontal placement position. Finally, the calculation result data is returned, which includes 3D display coordinate data, indicator data, the number of carrying units, and specification data.

[0013] In one possible implementation, after the backend module receives the calculation result data transmitted by the loading algorithm calculation module, the export file generation module generates an exportable PDF format transportation space loading scheme file based on the required number of carrier units and specification data in the calculation result data.

[0014] In one possible implementation, the backend module transmits the 3D display coordinate data and indicator data from the calculation results to the web interaction module through the web communication module. The backend module and the web interaction module communicate via WebSocket.

[0015] In one possible implementation, the 3D display platform for the loading scheme of the transportation space in the Web interactive module uses Three.js to model and display the loading layout of the cargo in three dimensions, including the specifications and coordinates of each carrying unit and the specifications and coordinates of the fragile columnar cargo on each carrying unit.

[0016] The beneficial effects of this invention are as follows: This invention provides a highly intelligent transportation space optimization system for fragile cylindrical cargo. The entire process, from cargo data import to scheme generation, 3D visualization, and scheme export, is completed with a single click on a web platform. This replaces traditional manual layout and record-keeping, avoiding scheme deviations caused by insufficient experience and ensuring the consistency and accuracy of loading plans. Through the collaborative calculation of cargo loading positions and orientations using various optimization algorithms such as grid and hexagonal arrangements, genetic algorithms, and greedy subset swapping, the system maximizes the carrying capacity of the transportation space, effectively reducing gaps and unused space, and lowering the number of transportation trips and costs caused by wasted space. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0018] Figure 1 This is a schematic diagram of the system structure according to an embodiment of the present invention.

[0019] Figure 2 This is a flowchart of the grid and hexagon arrangement algorithm according to an embodiment of the present invention.

[0020] Figure 3 This is a flowchart of the basin jump genetic algorithm according to an embodiment of the present invention.

[0021] Figure 4 This is a flowchart of the greedy subset exchange algorithm according to an embodiment of the present invention.

[0022] Figure 5 This is a three-dimensional loading layout diagram of the transportation space in the system of this embodiment of the invention. Detailed Implementation

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of this application.

[0024] This application provides a transportation space optimization system for fragile cylindrical cargo, comprising a database module, a web interaction module, a backend module, and a loading algorithm calculation module. The database module is used to store the configuration items required for loading algorithm calculation, the calculation result data after the loading algorithm calculation module, and the PDF file of the transportation space loading plan; The web interaction module includes a configuration management platform and a 3D display platform for transportation space loading schemes. The configuration management platform is responsible for managing the configuration items used during loading calculations and starting the loading calculations. The 3D display platform for transportation space loading schemes is used to display the loading layout of goods in three dimensions and to export PDF files of transportation space loading schemes.

[0025] The backend module includes a data management module, a web communication module, a computation task module, and an export file generation module. The data management module is responsible for managing the computation configuration items, computation result data, and PDF files of the transportation space loading scheme in the database, as well as providing the corresponding specification data based on the configuration items when the loading computation starts. The web communication module is responsible for returning the 3D display coordinate data and indicator data from the computation result data to the web interaction module. The computation task module is responsible for scheduling the loading algorithm computation module. The export file generation module is responsible for generating exportable transportation space loading scheme PDF files based on the computation result data.

[0026] The loading algorithm calculation module is responsible for calculating the specific loading of goods based on the fragile columnar cargo data, configuration items, and rule items provided by the calculation task module of the backend module, and transmitting the calculated results to the backend module.

[0027] The entire system is built on a microservice framework, and the backend computing task module and the loading algorithm computing module communicate with each other via RocketMQ in the form of a message queue.

[0028] This application also provides a method for using a transportation space optimization system for fragile cylindrical goods, including: Step (1) System setup.

[0029] First, the configuration management platform of the Web interaction module is used to configure the configuration items of the transportation space specifications and the configuration items of the carrying unit specifications to which the configuration items belong, thus completing the initial setup of the system. The specification data of the configuration items will be used for subsequent loading scheme calculations.

[0030] Step (2) Upload cargo data, configuration items and rule items.

[0031] Then, the user initiates the loading calculation through the configuration management platform of the web interaction module. First, the user imports the data of fragile cylindrical goods, including the specifications and quantity of each type of fragile cylindrical goods. Next, the user selects the configuration items to be used from the configuration items of the configured transportation space, and then selects the configuration items to be used from the configuration items of the carrier unit to which the transportation space belongs. Finally, the user configures the rules for the current calculation, including whether multiple goods can be combined and placed, whether assembled carrier units can be merged, and whether the remaining space can be utilized.

[0032] Step (3) Task release.

[0033] The backend module's computation task module encapsulates the fragile columnar cargo data, along with its configuration and rule items, passed from the Web interaction module into a computation task and publishes it to the corresponding message queue.

[0034] Step (4) The loading algorithm calculation module uses the loading algorithm to calculate the specific loading of the goods.

[0035] The loading algorithm operates as follows: First, it optimizes the loading of fragile columnar goods in the carrying unit using a grid and hexagonal arrangement algorithm. Then, it optimizes the loading of assembled carrying units in the transportation space using a greedy subset exchange algorithm. If the rules allow for multiple combinations of goods, then dissimilar fragile columnar goods that cannot fill a carrying unit after the grid and hexagonal arrangement algorithm are optimized for multi-specification loading using a genetic algorithm. If the rules allow for merging assembled carrying units, then the assembled carrying unit merging process is added. If there are still remaining spaces after the assembled carrying units are loaded and the rules allow for the use of remaining space, the module will extract the remaining space in the transportation space and calculate whether there is a suitable horizontal placement position. Finally, the calculation result data is returned, including 3D display coordinate data, indicator data, number of carrying units, and specification data; the calculated result data is then transmitted to the backend module.

[0036] Step (5) Generation of transport space loading plan documents.

[0037] After the backend module receives the calculation results data transmitted by the loading algorithm calculation module, the export file generation module generates an exportable PDF format transportation space loading scheme file based on the required number of carrier units and specification data in the calculation results data.

[0038] Step (6) 3D display of the cargo loading layout.

[0039] The backend module transmits the 3D display coordinate data and indicator data from the calculation results to the web interaction module through the web communication module. The backend module and the web interaction module communicate via WebSocket.

[0040] The 3D display platform for the transportation space loading scheme of the web interactive module uses Three.js to create a 3D model of the loading layout of the transportation space and display the loading layout of the goods. This model includes the specifications and coordinates of each carrying unit and the specifications and coordinates of the fragile columnar goods on each carrying unit.

[0041] In one possible implementation, the loading scheme data generation of the loading algorithm calculation module includes: Step 1, as follows Figure 1 As shown, the grid and hexagonal arrangement algorithm is used to calculate the loading position on the load-bearing unit for fragile cylindrical goods of the same specifications: 1-1. Input parameters are as follows: available length L of the bearing unit, available width W, and diameter d of the bottom circle of the fragile cylindrical cargo.

[0042] 1-2. Using a grid layout algorithm, calculate the maximum number of goods per row in each carrying unit. Calculate the maximum number of rows for the carrying unit. Calculate the total number of components in a single load-bearing unit. Record the total number of single-bearing units and the two-dimensional coordinates of the center of each fragile cylindrical cargo with the bearing unit as the base.

[0043] 1-3. Use the hexagonal arrangement algorithm to calculate the vertical spacing between rows. Calculate the total number of rows that can be placed. .

[0044] 1-4. Iterate through the number of fragile items in the first row. : Calculate the horizontal width occupied by the first row Calculate the number of fragile columnar goods that can be placed in the second row. Calculate the total number of components in a single load-bearing unit. Continue iterating. Find the maximum value. Record the total number of single-bearing units and the two-dimensional coordinates of the center of each fragile cylindrical cargo with the bearing unit as the base.

[0045] 1-5. Take the maximum value of the total number of components in a single load-bearing unit from the two methods. If the two are the same, a grid arrangement is used. Calculate the number of assembled load-bearing units after loading and the number of remaining vulnerable cylindrical goods of this specification based on the total number of components in a single load-bearing unit.

[0046] Step 2: Process according to the rule regarding "Can multiple goods be placed together?". If allowed, such as... Figure 2 As shown, the basin-jumping genetic algorithm is used to calculate the loading position on the bearing unit for remaining vulnerable cylindrical cargo of different sizes: 2-1. Treat the remaining fragile columnar cargo of different specifications as several chromosomes. Each chromosome is represented by a one-dimensional sequence. The order of each chromosome corresponds to the loading order or position index of the fragile columnar cargo.

[0047] 2-2. Generating according to heuristic rules We have 10 feasible chromosomes to form an initial population. For each chromosome, we use a greedy algorithm to quickly construct a set of carrier unit layouts.

[0048] 2-3. For each chromosome, calculate the space utilization rate, stability score, and number of carrier units of its corresponding carrier unit group as indicators, and sum them according to the corresponding weights to obtain a comprehensive score, with space utilization rate as the main factor (the higher the comprehensive score, the better the mixed packing scheme represented by the chromosome).

[0049] 2-4. Based on the comprehensive score, select several superior chromosomes to enter the next generation. Pair the selected chromosomes together according to the crossover probability. They are crossbred to produce new offspring. After crossbringing, the offspring are repaired to ensure no duplicate or omitted vulnerable columnar cargoes appear. For the chromosomes of the new offspring, they are determined according to the probability of mutation. One or more chromosomes are randomly selected for swapping or insertion to expand the solution space. After mutation, the offspring are also repaired. If the overall score does not change significantly after several generations (i.e., the set minimum improvement is not achieved), a portion of chromosomes are randomly selected for skipping, and the loading of some of the current carrying units is randomly rearranged. The overall score is recalculated, and the randomly rearranged chromosomes replace the worst-performing parts of the original population to escape local optima.

[0050] 2-5. Merge the new individuals obtained after crossover, mutation, and skipping with the superior individuals of the previous generation according to the strategy, and truncate the previous generation. The species formed a new population.

[0051] 2-6. When the maximum algebra is reached Or the population's optimal comprehensive score is continuously in If there is no significant change within a generation, stop the iteration; otherwise, return to step 2-3. Record and return the individual with the highest overall score in the final population; its corresponding carrier unit layout is the optimized solution, and add it to the list of assembled carrier units.

[0052] Step 3, as follows Figure 3 As shown, a greedy subset swapping algorithm is used to calculate the loading position in the transport space for all assembled carrier units: 3-1. Input parameters are as follows: list of assembled carrier units, transportation space specifications and quantity.

[0053] 3-2. Process according to the rule "Can assembled load-bearing units be merged?". If merging is allowed, find adjacent assembled load-bearing unit pairs of the same specifications and merge them according to the height of the transport space, that is, stack multiple assembled load-bearing units of the same specifications vertically and retain only the bottom load-bearing unit. If merging is not allowed, skip this step.

[0054] 3-3. Following the order of the assembled carrier units in the list, perform a greedy filling operation, placing the assembled carrier units into the remaining space of the freight car in sequence until there is no more space, and then proceed to subset optimization.

[0055] 3-4. In the subset optimization phase, iterate through all the assembled carrier unit pairs (i,j) that have been placed, and calculate whether the overall space utilization is improved after the swap. If it is improved, then perform the swap.

[0056] 3-5. If the space utilization rate is improved in the subset optimization stage of 3-4, return to 3-4 to continue the traversal. If there is no improvement, continue to execute downwards.

[0057] 3-6. Process according to the rule "Can the remaining space be used?". If it can be used, collect all fragile cylindrical goods that could not be placed in the transportation space, extract the remaining space in the transportation space, divide the remaining space into rectangular spaces in the side view, and try to add circles with the same diameter as the goods into the rectangular spaces. The first position is selected as the lower left corner, and subsequent positions are prioritized to be tangent to the bottom surface or to any circle already placed. If no position can be found, try positions tangent to any two circles. If it cannot be placed, skip the fragile cylindrical goods. Continue until all remaining fragile cylindrical goods have been traversed or there is insufficient space. If it cannot be used, skip this step.

[0058] 3-7. Calculate the total volume of the carrying units in each transport space and the total volume of goods on all carrying units, and calculate the space utilization rate of the transport space according to its specifications.

[0059] 3-8. Obtain the center-of-gravity coordinates of all carrier units in each transport space based on the list of assembled carrier units to which the carrier unit belongs and their serial numbers. Obtain the coordinates of the center of each fragile cylindrical cargo in the carrier unit on the carrier unit, as well as the specifications of the fragile cylindrical cargo, based on steps 1 and 2. Obtain the coordinates of the horizontally placed fragile cylindrical cargo in each transport space based on the coordinates of the corresponding circle in the side view of the remaining space and the specifications of the fragile cylindrical cargo. Return the calculation results data, including: the center-of-gravity coordinates of all carrier units in each transport space, the coordinates of the center of each fragile cylindrical cargo in the carrier unit on the carrier unit, the coordinates of the horizontally placed fragile cylindrical cargo in each transport space, the specifications of each carrier unit, the specifications of the fragile cylindrical cargo in each carrier unit, the number of fragile cylindrical cargoes not loaded, the space utilization rate calculated in this case, and the number of carrier units used.

[0060] Taking the data of fragile columnar goods in the table below as an example, the configuration items are: bearing unit (length 1.3m, width 1.1m, height 0.15m) and transportation space (length 11.89m, width 2.32m, height 2.5m). The specifications are: multiple goods can be combined and placed, bearing units can be merged, and the remaining space cannot be used. The three-dimensional loading layout diagram of the transportation space calculated by the system is as follows: Figure 4 As shown, the space utilization rate is 84.4%, and all goods have been loaded.

[0061] The above embodiments are only used to illustrate the principles and effects of the present invention and are not intended to limit the invention. Those skilled in the art, upon reading this, will be able to make equivalent substitutions or further improvements to the various embodiments without departing from the core concept of the present invention. The scope of protection of the present invention should be determined by the appended claims and their equivalents.

Claims

1. A transportation space optimization system for fragile cylindrical goods, characterized in that, It consists of a database module, a web interaction module, a backend module, and a loading algorithm calculation module. The database module is used to store the configuration items required for loading algorithm calculation, the calculation result data after the loading algorithm calculation module, and the PDF file of the transportation space loading plan; The web interaction module includes a configuration management platform and a 3D display platform for loading solutions in transportation space. The configuration management platform is responsible for managing the configuration items used during loading calculation and starting the loading calculation. The 3D display platform for loading solutions in transportation space is used to display the loading layout of goods in three dimensions and to export PDF files of the loading solutions in transportation space. The backend module includes a data management module, a web communication module, a computing task module, and an export file generation module. The data management module is responsible for managing the computing configuration items, computing result data, and PDF files of the transportation space loading scheme in the database, as well as providing the corresponding specification data based on the configuration items when the loading calculation starts. The web communication module is responsible for returning the 3D display coordinate data and indicator data from the computing result data to the web interaction module. The computing task module is responsible for scheduling the loading algorithm computing module. The export file generation module is responsible for generating exportable transportation space loading scheme PDF files based on the computing result data. The loading algorithm calculation module is responsible for calculating the specific loading of goods based on the fragile columnar cargo data, configuration items, and rule items provided by the calculation task module of the backend module, and transmitting the calculated results to the backend module.

2. The transportation space optimization system for fragile cylindrical goods according to claim 1, characterized in that, The configuration management platform of the web interaction module configures the configuration items of the transportation space specifications and the configuration items of the carrying unit specifications to which the configuration items belong, completing the initial setup of the system. The specification data of the configuration items will be used for subsequent loading scheme calculations.

3. The transportation space optimization system for fragile cylindrical goods according to claim 1, characterized in that, Users initiate loading calculations through the configuration management platform of the Web interaction module. First, they import data on fragile cylindrical goods, including the specifications and quantity of each type of fragile cylindrical goods. Then, they select the configuration items to be used from the configuration items of the configured transportation space, and then select the configuration items to be used from the configuration items of the carrier unit to which the transportation space belongs. Finally, they configure the rules for the current calculation, including whether multiple goods can be combined and placed, whether assembled carrier units can be merged, and whether the remaining space can be utilized.

4. The transportation space optimization system for fragile cylindrical goods according to claim 1, characterized in that, The entire system is built on a microservice framework, and the backend computing task module and the loading algorithm computing module communicate with each other via RocketMQ in the form of a message queue.

5. A transportation space optimization system for fragile cylindrical goods according to claim 1, characterized in that, The backend module's computation task module encapsulates the fragile columnar cargo data, along with its configuration and rule items, passed from the Web interaction module into a computation task and publishes it to the corresponding message queue.

6. The transportation space optimization system for fragile cylindrical goods according to claim 1, characterized in that, The loading algorithm operates as follows: First, it optimizes the loading of fragile columnar goods in the carrying unit using a grid and hexagonal arrangement algorithm. Then, it optimizes the loading of assembled carrying units in the transportation space using a greedy subset exchange algorithm. If the rules allow for multiple combinations of goods, then the non-similar fragile columnar goods that cannot fill a carrying unit after the grid and hexagonal arrangement algorithm are optimized for multi-specification loading using a genetic algorithm. If the rules allow for merging assembled carrying units, then the assembled carrying unit merging process is added. If there are still remaining spaces after the assembled carrying units are loaded and the rules allow for the use of remaining space, the module will extract the remaining space in the transportation space to calculate whether there is a suitable horizontal placement position. Finally, the calculation result data is returned, which includes 3D display coordinate data, indicator data, the number of carrying units, and specification data.

7. A transportation space optimization system for fragile cylindrical goods according to claim 1, characterized in that, After the backend module receives the calculation results data transmitted by the loading algorithm calculation module, the export file generation module generates an exportable PDF format transportation space loading scheme file based on the required number of carrier units and specification data in the calculation results data.

8. A transportation space optimization system for fragile cylindrical goods according to claim 1, characterized in that, The backend module and the web interaction module communicate via WebSocket.

9. A transportation space optimization system for fragile cylindrical goods according to claim 1, characterized in that, The 3D display platform for the transportation space loading scheme of the web interactive module uses Three.js to create a 3D model of the loading layout of the transportation space and display the loading layout of the goods. This model includes the specifications and coordinates of each carrying unit and the specifications and coordinates of the fragile columnar goods on each carrying unit.

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