Steel coil train and automobile combined stowage method, device and equipment and medium

Abstract

The invention provides a steel coil train and automobile combined stowage method, device, equipment and medium, and the method comprises the steps: firstly obtaining the information of a to-be-stowage steel coil, stowage limitation information and a set stowage target, building a steel coil stowage planning model based on the information, and determining the input parameters according to the specific information of the to-be-stowage steel coil, the constraint condition is generated according to the stowage limitation, the decision variable comprehensively considers the information of the steel coil to be stowage and the stowage target, then the optimal steel coil stowage scheme meeting the specific stowage requirement is obtained by solving the model, and finally, the scheme is issued to the corresponding end point of the logistics system for guiding the actual steel coil stowage and transportation operation. The method not only optimizes the resource allocation, but also improves the operation efficiency, and ensures the safety and economy of the transportation process.

Description

Technical Field

[0001] The present application relates to the field of intelligent transportation technology, and particularly to a combined loading method, device, equipment and medium for steel coil trains and trucks. Background Art

[0002] In the modern steel logistics industry, the efficient loading and transportation of steel coils is crucial for reducing operating costs and improving customer satisfaction. However, the current steel coil loading methods have various deficiencies, which limit the improvement of logistics efficiency. First of all, most of these methods focus on railway transportation (fire transportation), while ignoring the importance of truck transportation (motor transportation), resulting in particularly significant problems of low efficiency and increased costs in scenarios where fire transportation and motor transportation need to work together. In addition, the existing methods are difficult to handle complex multi-site loading requirements, making the transportation routes long and the time extended, further driving up the operating costs.

[0003] In addition to the limitations in transportation methods, the existing loading methods also have serious defects in loading balance. Traditional methods usually only focus on the loading quantity and sequence of steel coils, while ignoring the impact of loading balance on transportation safety. Unbalanced loading will lead to problems such as the center of gravity shift of the car body and overloading, which not only increases safety hazards but also may shorten the service life of railway tracks. Although some technologies have tried to solve these problems by digitally analyzing the loading rules of the railway administration or using optimization models to achieve automatic loading, they often fail to comprehensively consider the combined use of fire transportation and motor transportation, or the analysis of loading balance is not deep enough, thus failing to completely overcome the above challenges.

[0004] Generally speaking, the challenges faced in the current steel coil loading process include but are not limited to: complex and mutually restrictive loading rules, high transportation costs, and low loading efficiency. Manual loading is not only difficult to optimize the cooperation between fire transportation and motor transportation, but also prone to errors due to cumbersome operations, and it is difficult to meet the large-scale loading requirements. Summary of the Invention

[0005] In view of the above-mentioned disadvantages of the prior art, the present application provides a combined loading method, device, equipment and medium for steel coil trains and trucks to solve the above technical problems.

[0006] The present application provides a combined loading method for steel coils by train and truck. The method includes: obtaining the information of the steel coils to be loaded, the loading restriction information, and the loading objective; constructing a steel coil loading planning model based on the loading objective, wherein the input parameters of the steel coil loading model are determined based on the information of the steel coils to be loaded, the constraint conditions are generated based on the loading restriction information, and the decision variables are jointly determined based on the information of the steel coils to be loaded and the loading objective; solving the steel coil loading planning model to obtain a steel coil loading plan that meets the loading requirements; and sending the steel coil loading plan to the target end to implement the loading and transportation of the steel coils based on the steel coil loading plan.

[0007] In an embodiment of the present application, solving the steel coil loading planning model includes: obtaining the initial values of each model parameter based on the information of the steel coils to be loaded; inputting the initial values into the steel coil loading planning model to generate an initial loading plan, wherein an initial railway transportation loading plan is preferably generated first, and then a road transportation loading plan is generated based on the railway transportation plan; and optimizing the initial loading plan to obtain an updated loading plan that meets the loading objective.

[0008] In an embodiment of the present application, constructing the steel coil loading planning model further includes: encoding the vehicles used for loading, wherein in the railway transportation loading plan, a single freight car is used as the encoding unit, and in the road transportation loading plan, a single truck is used as the encoding unit. Each encoding element represents a steel coil to be loaded, and the road transportation encoding elements are a subset of the railway transportation encoding elements.

[0009] In an embodiment of the present application, optimizing the initial loading plan includes: removing the eliminated encodings in the initial railway transportation loading plan and the encodings in the initial road transportation loading plan, where the eliminated encodings include those that do not meet the loading objective and those that meet the loading objective and are selected based on a preset elimination probability; determining a loadable resource pool based on the initial railway transportation loading plan, screening target steel coils that meet the preset screening conditions from the loadable resource pool, and inserting the target steel coils into the initial railway transportation loading plan that has not been removed in pairs on the premise of meeting the freight car balance constraint condition to obtain an updated railway transportation loading plan; using the steel coils corresponding to the encoding elements in the updated railway transportation loading plan as the steel coils to be allocated, and allocating the steel coils to be allocated to different trucks, wherein the steel coils to be allocated that are in the same warehouse and transported to the same customer are preferably allocated to the same truck; and reinserting the removed encodings into the updated railway transportation loading plan through permutation and combination to generate a target railway transportation loading plan, and generating a target road transportation loading plan based on the target railway transportation loading plan.

[0010] In one embodiment of the present application, after obtaining an updated stowage plan that meets the stowage target, the method further includes: determining the rail transportation target stowage plan and the motor transportation target stowage plan as the target stowage plan, and calculating the value of the objective function of the target stowage plan in the steel coil stowage planning model; based on the acceptance criterion of the simulated annealing algorithm, accepting the eliminated code with a preset acceptance probability, and calculating the current objective function value of the eliminated code in the steel coil stowage planning model; if the current objective function value is better than the objective function value of the plan, then replacing the updated stowage plan with the stowage plan corresponding to the current objective function value as the target stowage plan.

[0011] In one embodiment of the present application, before constructing the steel coil stowage planning model, the method further includes: screening the information categories of the steel coils to be stowed to obtain key items related to steel coil stowage, and determining the key items as model parameters; identifying the relationships between the model parameters and the stowage target to generate parameter combinations that affect the stowage target, and determining the parameter combinations as decision variables.

[0012] In one embodiment of the present application, constraint conditions are generated based on the stowage restriction information, and the constraint conditions at least include: each steel coil to be stowed is allocated to at most one loading position, and at most one steel coil to be stowed is allocated to any loading position; the weight difference between the steel coils on different layers or different sides of the same railway car is less than or equal to the corresponding preset weight difference threshold; the total weight of the steel coils loaded on any railway car or motor vehicle is less than or equal to the corresponding preset weight threshold.

[0013] The present application provides a combined rail and motor stowage device for steel coils, the device includes: an information acquisition module, configured to acquire information on steel coils to be stowed, stowage restriction information, and stowage targets; a model construction module, configured to construct a steel coil stowage planning model based on the stowage target, wherein the input parameters of the steel coil stowage model are determined based on the information on the steel coils to be stowed, the constraint conditions are generated based on the stowage restriction information, and the decision variables are jointly determined based on the information on the steel coils to be stowed and the stowage target; a model solution module, configured to solve the steel coil stowage planning model to obtain a steel coil stowage plan that meets the stowage requirements; a stowage plan execution module, configured to send the steel coil stowage plan to the target end to implement steel coil stowage and transportation based on the steel coil stowage plan.

[0014] The present application provides an electronic device, the electronic device includes: one or more processors; a storage device, configured to store one or more programs, when the one or more programs are executed by the one or more processors, enabling the electronic device to implement the combined rail and motor stowage method for steel coils as described above.

[0015] The present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor of a computer, the computer is caused to execute the combined loading method of steel coil trains and trucks as described above.

[0016] Advantages of the present application: The combined loading method of steel coil trains and trucks proposed in the present application aims to improve transportation efficiency and safety while reducing transportation costs. The method first obtains information on steel coils to be loaded, loading restriction information, and set loading objectives. Based on this information, a steel coil loading planning model is constructed, where the input parameters are determined according to the specific information of the steel coils to be loaded, the constraint conditions are generated based on the loading restrictions, and the decision variables comprehensively consider the information of the steel coils to be loaded and the loading objectives. By solving this model, the optimal steel coil loading plan that meets specific loading requirements can be obtained. Finally, this plan will be sent to the corresponding endpoints of the logistics system to guide the actual steel coil loading and transportation operations. The method not only optimizes resource allocation but also improves operation efficiency, ensuring the safety and economy of the transportation process, and is applicable to the logistics management of heavy industrial products such as steel.

[0017] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts. In the drawings:

[0019] Figure 1 is a schematic diagram of the implementation environment of the combined loading method of steel coil trains and trucks shown in an exemplary embodiment of the present application;

[0020] Figure 2 is a flowchart of the combined loading method of steel coil trains and trucks shown in an exemplary embodiment of the present application;

[0021] Figure 3 is a schematic flowchart of optimizing the initial loading plan shown in an exemplary embodiment of the present application;

[0022] Figure 4 is a block diagram of the combined loading device of steel coil trains and trucks shown in an exemplary embodiment of the present application;

[0023] Figure 5 shows a schematic diagram of the structure of a computer system of an electronic device suitable for implementing the embodiments of the present application. Detailed implementation manners

[0024] The following will describe the implementation manners of the present application with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for explaining the present application, rather than for limiting the protection scope of the present application.

[0025] It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present application in a schematic manner. Therefore, only the components related to the present application are shown in the diagrams, rather than being drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and ratio of each component in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0026] In the following description, a large number of details are explored to provide a more thorough explanation of the embodiments of the present application. However, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present application difficult to understand.

[0027] Figure 1 It is a schematic diagram of the implementation environment of the combined loading method of steel coil trains and automobiles shown in an exemplary embodiment of the present application.

[0028] As Figure 1 shown, the implementation environment of the combined loading method of steel coil trains and automobiles includes a data acquisition module 101 and a computer device 102.

[0029] Among them, the data acquisition module 101 is used to collect all necessary input information, which is the basis for constructing the steel coil loading planning model. Specifically, its input information includes, but is not limited to, information about the steel coils to be loaded (such as order number, steel coil number, warehouse number, weight, specification, etc.), loading limit information (including the upper and lower limits of train and truck loading), and set loading targets. This module can use modern information technology means such as sensor technology, RFID tags, and barcode scanners to automatically identify and record relevant information of the steel coils. In addition, through integration with the existing enterprise resource planning (ERP) system or warehouse management system, real-time data update and synchronization are achieved.

[0030] The computer device 102 serves as the core processing unit for the entire stowage process, mainly used to perform the construction, solution, and optimization of the steel coil stowage planning model. Based on the information received from the data acquisition module 101, the computing device will establish a mathematical model and use advanced algorithms such as the large neighborhood search algorithm to find the optimal stowage plan. In addition, to support complex computing requirements, a specially developed software program runs on the computer device 102, which can efficiently process large-scale data sets and quickly generate the best solutions that meet specific stowage requirements.

[0031] Generally speaking, in the process of generating the combined stowage plan for steel coils by train and truck, first, the data acquisition module 101 collects relevant data from different sources and transmits it to the computer device 102; then, in the computer device 102, a steel coil stowage planning model is constructed based on the received data, and advanced algorithms are used to solve the model to obtain the best stowage plan; finally, the obtained plan will be fed back to the logistics system to guide specific transportation and loading / unloading operations, thus realizing the automated and efficient management of the entire process. It can be understood that this configuration not only improves work efficiency but also ensures the safety and economy of stowage.

[0032] Figure 2 It is a flowchart of the combined stowage method for steel coils by train and truck shown in an exemplary embodiment of the present application.

[0033] As Figure 2 shown, in an exemplary embodiment, the combined stowage method for steel coils by train and truck at least includes steps S210 to S240, which are introduced in detail as follows:

[0034] Step S210, obtain the information of the steel coils to be stowed, the stowage restriction information, and the stowage objective.

[0035] In an embodiment of the present application, first, relevant information of the steel coils to be stowed needs to be obtained from the inventory management system within the enterprise. The relevant information includes but is not limited to the order number, steel coil number, warehouse number and specific location, as well as the weight and specifications of each steel coil (for example, the weight is 9.8 tons and the specifications are.9*1250). At the same time, stowage restriction information needs to be collected, mainly including the stowage rules for trains and trucks respectively. Then, based on the above data and rules, the stowage objective is further clarified, such as maximizing the train stowage rate, minimizing the number of trucks, and ensuring loading balance. Finally, after integrating the above three types of information, a mathematical model that accurately reflects the actual situation is constructed. This model not only provides a solid data foundation for the establishment of the subsequent integer programming model but also paves the way for the application of the large neighborhood search algorithm.

[0036] Step S220: Build a coil loading planning model based on the loading target. Among them, the input parameters of the coil loading model are determined based on the coil information to be loaded, the constraint conditions are generated based on the loading limit information, and the decision variables are jointly determined based on the coil information to be loaded and the loading target.

[0037] In an embodiment of the present application, before building the coil loading planning model, it further includes: screening the information categories of the coil information to be loaded to obtain key items related to coil loading, and determining the key items as model parameters; identifying the relationship between each model parameter and the loading target to generate a parameter combination that affects the loading target, and determining the parameter combination as the decision variable.

[0038] In an embodiment of the present application, first, after obtaining the coil information to be loaded, it is necessary to screen this information to extract data items directly related to coil loading as model parameters. For example, the original data obtained from the inventory management system may contain a large amount of unnecessary details, such as the historical transaction records and manufacturing processes of the coils. In this step, only the information crucial for the loading decision needs to be focused on, as follows:

[0039] Order number (such as "DH2309150021-001"): Used to associate a specific batch of coils with their destinations.

[0040] Coil number (such as "H3A239072651"): Uniquely identifies each coil of steel, facilitating tracking and management.

[0041] Warehouse number and location (such as warehouse category P8, warehouse number 25, area number 03A): Specifies the specific storage location of the coil, affecting the loading and unloading sequence and cost.

[0042] Weight and specification (such as weight 9.8 tons, specification.9*1250): Determines whether the coil can be loaded into a specific railway car or truck, and directly affects the loading balance.

[0043] Through the above screening process, relevant key items are determined as the basic parameters for building the loading planning model, ensuring that subsequent analysis focuses on the most relevant information.

[0044] Then, identify the relationship between each model parameter and the loading target. Taking the loading target as "maximizing the train loading rate, minimizing the number of trucks, and ensuring loading balance" as an example, it is necessary to analyze which parameter combinations can most effectively achieve these goals. The specific analysis process is as follows:

[0045] Maximizing the train loading rate: It is required to give priority to considering the weight and specification of the coils to fill each railway car as much as possible without overloading. Therefore, the coil number, weight, and specification become one of the main decision variables.

[0046] Minimize the number of trucks: It is necessary to not only focus on the weight of a single steel coil but also consider how to reasonably match multiple steel coils to reduce the number of required trucks. Therefore, in addition to weight and specifications, the storage location number and position also become important because steel coils within the same storage are usually easier to load simultaneously.

[0047] Ensure loading balance: To ensure the stability of the vehicle during transportation, the weight difference between the steel coils on the left and right sides cannot exceed a certain range. This means that when selecting which steel coils to load into the same wagon, it is also necessary to comprehensively consider their position distribution and weight ratio.

[0048] Based on the above analysis, a set of parameter combinations can be generated as decision variables. For example, in a specific scenario, if the total weight of a batch of steel coils is close to the maximum load capacity of a train, the system may recommend allocating all these steel coils to the train and simultaneously optimizing their arrangement within the carriage to maintain balance. On the contrary, if the total weight is small, the most suitable truck combination plan will be recommended, and steel coils from the same storage will be selected for loading together as much as possible to reduce the loading and unloading costs.

[0049] It can be understood that through the information preprocessing steps proposed in this embodiment, not only can the model parameters and decision variables be more precisely defined, but also the final generated loading plan can meet the actual operation requirements and achieve the predetermined loading objectives to the greatest extent. It can significantly improve the efficiency and effectiveness of logistics management and save a large amount of time and resources for the enterprise.

[0050] In a specific embodiment of this application, first, the input parameters are determined according to the information of the steel coils to be loaded. This information includes but is not limited to detailed data such as order number, steel coil number, storage location number and position, weight, and specifications. For example, for a specific steel coil with the number "H3A239072651", located in storage P8, storage number 25, area code 03A, with a weight of 9.8 tons and a specification of.9*1250. This specific data is incorporated into the model as input parameters to ensure that the model can accurately reflect the actual attributes of each steel coil.

[0051] Next, constraint conditions of the model are generated based on the collected stowage limit information. These limit information mainly include the stowage rules for trains and trucks. For example, the upper stowage limit of a train is 55 tons, the lower limit is 70 tons, and there are specific location numbers B1 / C1 / D1; the upper stowage limit of a truck is 90 tons, and the lower limit is 50 tons. In addition, it also includes the penalty scores for the combination of steel coils in different warehouses (the low penalty score for the same warehouse is 0, and the high penalty score for different warehouses is 1), and the specific requirements for loading balance (for example, the weight difference of steel coils on the left and right sides of any car body does not exceed 1 ton). It can be understood that these constraint conditions are used to ensure that the stowage plan can meet the actual operation requirements and ensure the safety and stability of transportation.

[0052] In addition, the decision variables are jointly determined based on the steel coil information to be stowed and the stowage objectives. For example, under the guidance of the objective of maximizing the train stowage rate while minimizing the number of trucks, the decision variables may involve which steel coils should be allocated to which train car or which truck, and how to arrange their specific positions in the car body to achieve the best loading balance. Suppose our goal is to load as many steel coils onto the train as possible while reducing the use of trucks. Then the decision variables need to consider the actual weight of each steel coil and its combined effect with other steel coils to ensure that there is no overloading and a good center of gravity distribution is maintained.

[0053] In an embodiment of the present application, constraint conditions are generated based on the stowage limit information, and the constraint conditions at least include: each steel coil to be stowed is allocated to at most one loading position, and at most one steel coil to be stowed is allocated to any loading position; the weight difference between the steel coils on different layers or different sides of the same train car body is less than or equal to the corresponding preset weight difference threshold; the total weight of the steel coils loaded on any train car or vehicle is less than or equal to the corresponding preset weight threshold.

[0054] In a specific embodiment of the present application, first, to ensure that each steel coil to be loaded is reasonably allocated, it is stipulated that each steel coil to be loaded can be allocated to at most one loading position, and any loading position can only be allocated one steel coil to be loaded. For example, for the steel coil numbered "H3A239072651", the system will determine the most suitable loading position according to its weight and specifications to ensure that it will not be wrongly allocated to multiple positions or cause a certain position to be occupied by multiple steel coils. Second, to ensure safety during transportation, especially for the loading balance of railway wagons, it is set that the weight difference between the steel coils on different layers or different sides of the same railway wagon must be less than or equal to the corresponding preset weight difference threshold. Specifically, assume that a group of steel coils with a total weight of 45 tons is placed on the left side of a certain railway wagon, then the total weight of the steel coils placed on the right side should be controlled between 44 and 46 tons (assuming the preset weight difference threshold is 1 ton). In addition, considering the safe load-bearing capacity of the vehicle, it is also stipulated that the total weight of the steel coils loaded on any railway wagon or truck must be less than or equal to the corresponding preset weight threshold. For example, the maximum load limit of a railway wagon may be set at 55 tons, and the maximum load limit of a truck is 90 tons. This means that during loading, the system needs to accurately calculate and control the total weight of the steel coils on each wagon or truck to ensure that these limits are not exceeded. For example, if an order contains multiple steel coils with a total weight close to 55 tons, the system may recommend reallocating some steel coils to other wagons or trucks to meet the specified maximum load capacity.

[0055] In a specific embodiment, assume that we have a batch of steel coils to be loaded, including three steel coils with weights of 9.8 tons, 10.2 tons, and 9.5 tons respectively. According to the above constraints, the system will perform the following steps: First, determine the specific loading position of each steel coil to ensure no overlap or vacancy; then, calculate the weight difference between the two sides to ensure that the gap between them does not exceed 1 ton. For example, place the 9.8-ton and 10.2-ton steel coils on the left and right sides of the wagon respectively, so that the weight difference between the two sides is 0.4 tons, meeting the balance requirement; finally, check whether the total weight of the entire wagon exceeds 55 tons. If it exceeds, the system will adjust the plan, such as transferring the lighter 9.5-ton steel coil to another wagon until the total weight of all wagons is within the safe range.

[0056] It can be understood that through the constraints proposed in this embodiment, not only the scientificity and rationality of the loading decision-making are improved, but also the overall efficiency of logistics management is significantly enhanced, the transportation cost is reduced, and the market competitiveness of the enterprise is strengthened. At the same time, the strict constraints ensure the safety of the transportation process, save costs for the enterprise in the long term, and improve the service quality.

[0057] Step S230, solve the steel coil loading planning model to obtain a steel coil loading plan that meets the loading requirements.

[0058] In an embodiment of the present application, solving the coil stowage planning model includes: obtaining initial values of each model parameter based on the coil information to be stowed; inputting the initial values into the coil stowage planning model to generate an initial stowage plan, where preferably, an initial rail stowage plan is generated first, and then a road stowage plan is generated based on the rail plan; optimizing the initial stowage plan to obtain an updated stowage plan that meets the stowage target.

[0059] In an embodiment of the present application, constructing the coil stowage planning model further includes: encoding the vehicles for stowage, where in the rail stowage plan, a single railway car body is used as the encoding unit, and in the road stowage plan, a single vehicle is used as the encoding unit. Each encoding element represents a coil to be stowed, and the road encoding elements are a subset of the rail encoding elements. Therefore, optimizing the initial stowage plan includes: removing the eliminated encodings in the initial rail stowage plan and the encodings in the initial road stowage plan, where the eliminated encodings include those that do not meet the stowage target and those that meet the stowage target selected based on a preset elimination probability; determining a stowable resource pool based on the initial rail stowage plan, screening target coils that meet the preset screening conditions from the stowable resource pool, and inserting the target coils in pairs into the initial rail stowage plan that has not been removed on the premise of meeting the railway car balance constraint condition to obtain an updated rail stowage plan; using the coils corresponding to the encoding elements in the updated rail stowage plan as the coils to be allocated, and allocating the coils to be allocated to different vehicles, where preferably, the coils to be allocated that are in the same warehouse and transported to the same customer are allocated to the same vehicle; reinserting the removed encodings into the updated rail stowage plan through permutation and combination to generate a target rail stowage plan, and generating a target road stowage plan based on the target rail stowage plan.

[0060] In a specific embodiment of the present application, first, relevant information of the coils to be stowed is obtained from the inventory management system, including but not limited to order number, coil number, warehouse number and location, weight, and specifications. For example, for a specific coil, its number is "H3A239072651", located in warehouse P8, warehouse number 25, zone number 03A, with a weight of 9.8 tons and a specification of.9*1250. Using the above data as input parameters and incorporating them into the model ensures that the model can accurately reflect the actual attributes of each coil.

[0061] Next, input the initial values obtained above into the coil stowage planning model to generate a preliminary stowage plan. At this stage, since train transportation usually involves a larger capacity and longer distances, which has a greater impact on the overall stowage plan, the initial plan for train stowage is preferably generated first, and then the truck stowage plan is generated. Suppose there is a batch of coils with a total weight close to the maximum carrying capacity of a train (e.g., 55 tons), then the system will try to find the most suitable combination to fill the train while ensuring a balanced load. Once the train stowage plan is determined, the system will further plan the truck stowage plan based on this plan. For example, if the remaining total weight of the coils is small and not enough to fill another train carriage, the system will recommend the most suitable truck combination plan and try to select the coils from the same warehouse for loading together to reduce the loading and unloading costs.

[0062] After that, after the initial plan is generated, it needs to be optimized to ensure that the final plan can meet the preset stowage goals to the greatest extent, such as maximizing the train stowage rate, minimizing the number of trucks, and ensuring a balanced load, etc. This process is achieved through a large neighborhood search algorithm, which consists of two parts: a destruction operator and a repair operator, as follows:

[0063] Destruction operator: For the train stowage plan, first remove the codes that do not conform to the stowage rules, and then remove the codes that conform to the stowage rules but may cause imbalance or inefficiency with a certain probability; for the truck stowage plan, all are re-evaluated.

[0064] Repair operator: When reinserting the removed codes, refer to the train stowage plan, consider the requirement that the weight difference of the coils on the left and right sides of the car body does not exceed 1 ton, and ensure that the up, down, left, and right are balanced each time a coil is inserted. For the truck stowage plan, preferably arrange the coils from the same warehouse and the same customer in the same vehicle to reduce the number of loading and unloading times.

[0065] Finally, after multiple iterations of optimization until the optimal solution or an approximate optimal solution is found. For example, in a certain optimization iteration, it is found that adjusting the positions of some coils can better utilize the space without overloading, and at the same time maintain a good center of gravity distribution, then update the current best plan. The finally obtained updated stowage plan not only improves the stowage rate, but also reduces the use of unnecessary transportation tools, reduces the transportation cost, and ensures the safety of transportation.

[0066] Figure 3 is a schematic flow chart showing the process of optimizing the initial stowage plan in an exemplary embodiment of the present application.

[0067] As Figure 3As shown, first, collect all relevant information of the steel coils to be stowed, including weight, size, type, etc. At the same time, obtain the stowage limit information, such as the maximum load and volume limit of the railway wagon and the truck; and based on this information and the stowage objective (such as maximizing the loading rate and minimizing the transportation cost), construct a steel coil stowage planning model. Then, use the constructed steel coil stowage planning model to generate a preliminary stowage plan, and adopt a large-scale neighborhood algorithm to iteratively optimize the model, so as to continuously adjust the stowage plan through the algorithm to find a better solution until the current number of iterations reaches the preset maximum number of iterations; when the maximum number of iterations is reached, output the current optimal stowage plan, and submit the generated best stowage plan to an experienced stowage operator for review. If the review is passed, issue the final stowage plan to the target end for actual operation.

[0068] In an embodiment of the present application, after obtaining an updated stowage plan that meets the stowage objective, it further includes: determining the railway transportation target stowage plan and the truck transportation target stowage plan as the target stowage plan, and calculating the objective function value of the plan in the steel coil stowage planning model; based on the acceptance criterion of the simulated annealing algorithm, receive the eliminated code with a preset acceptance probability, and calculate the current objective function value of the eliminated code in the steel coil stowage planning model; if the current objective function value is better than the objective function value of the plan, then replace the updated stowage plan with the stowage plan corresponding to the current objective function value as the target stowage plan.

[0069] In a specific embodiment of the present application, during a certain optimization process, the system identified a set of steel coil allocation plans that were eliminated in previous iterations. Although they initially did not fully meet all the constraints, through recalculation, it was found that this allocation method could significantly improve the loading efficiency of a certain railway wagon without violating the key limitations. Based on this, the system calculated the objective function value of this new plan and compared it with the objective function value of the existing plan.

[0070] If the current objective function value is better than the objective function value of the plan, automatically adopt this new stowage plan to replace the original updated stowage plan as the new target stowage plan. For example, although the new plan slightly increases the load of a certain truck, it significantly reduces the total number of trucks used, thereby reducing the overall transportation cost. In this way, the system continuously iterates and optimizes until an optimal or near-optimal stowage plan is found, ensuring that the final plan meets the actual operation requirements and can maximize the predetermined stowage objective.

[0071] Step S240, issue the steel coil stowage plan to the target end to implement steel coil stowage and transportation based on the steel coil stowage plan.

[0072] In one embodiment of the present application, after determining the optimized steel coil loading scheme, the system automatically synchronizes the scheme to each target end of the logistics management system. The specific operation includes sending detailed loading instructions to the relevant parties, such as the specific number, weight, specification and corresponding loading position of each steel coil, to ensure that each steel coil is accurately allocated to the designated train car or truck position. Next, an experienced loader logs in to the front page of the system to review the loading scheme generated by the system. It is necessary to check every detail to confirm that the total weight of the steel coil does not exceed the maximum load limit of the vehicle, the weight difference of the steel coils on the left and right sides is controlled within the allowable range, and to evaluate whether there is a better combination that can further improve the loading efficiency or reduce the difficulty of loading and unloading. If any problems that may affect transportation safety or efficiency are found, such as the weight distribution of some steel coils may cause the center of gravity to shift, or the actual available space of a certain car is not enough to accommodate the predetermined number of steel coils, the loader will make corresponding adjustments in the system. After the adjustment is completed, the system recalculates and updates the objective function value of the loading scheme to ensure that all constraints are met. Once the loading plan is reviewed and confirmed to be correct, the loaders formally approve the plan and send it to the driver and warehouse manager responsible for the specific operation. The driver drives the vehicle to the designated location according to the loading plan, and the warehouse manager loads and unloads the steel coils according to the instructions of the plan.

[0073] It can be understood that the loading plan review method proposed in this embodiment not only ensures the professionalism and accuracy of the plan, but also enhances the flexibility and adaptability in actual operation, so that each transportation can achieve the best effect.

[0074] In view of the fact that the above-mentioned embodiments only show part of the contents of the method for combined loading of steel coils by train and automobile proposed in this application, in order to fully demonstrate the overall superiority of this method, a complete embodiment is provided below, covering the whole process from data acquisition, model construction, scheme optimization to practical application, as shown below.

[0075] Step 1, obtain the steel coil inventory resource data, order information data, rail transport loading rules, and truck transport loading rules. The steel coil inventory resource information includes order number, steel coil number, warehouse number, weight, and specification, as shown in Table 1 below.

[0076] Table 1

[0077]

[0078] Its order data includes customer name, order number, and flow direction, as shown in Table 2 below.

[0079] Table 2

[0080]

[0081]

[0082] The train loading rules include the upper loading limit, the lower loading limit, and the position number, as shown in Table 3 below.

[0083] Table 3

[0084]

[0085] In addition, the truck loading rules include the upper loading limit and the lower loading limit, as shown in Table 4 below.

[0086] Table 4

[0087]

[0088] Step 2: Taking the rail transportation loading rules and the road transportation loading rules of steel coils as constraint conditions, with the goal of maximizing the train loading rate and minimizing the number of trucks, the factors considered in the combined rail and road transportation loading are described by establishing an integer programming model. The establishment process of its mathematical model is as follows:

[0089] Step 2-1: Set the parameters of the mathematical model:

[0090] I represents the set of steel coils to be loaded, I = {1, 2,...};

[0091] F represents the set of loading plans, F = {1, 2,...};

[0092] K f represents the set of virtual carriages of plan f, K f = {1, 2,...};

[0093] w i represents the actual weight of steel i;

[0094] P j represents the set of positions of carriage j, P j = {1, 2,...};

[0095] represents the set of positions to the left of carriage j

[0096] represents the set of positions to the right of carriage j

[0097] W t represents the maximum load limit of the carriage;

[0098] r j represents the number of positions of carriage j;

[0099] In addition, for the road transportation loading part, it also includes:

[0100] C represents the set of virtual vehicles C = {1, 2, …};

[0101] e i represents the warehouse number where the steel coil i is located;

[0102] W c represents the maximum load limit of the vehicle;

[0103] represents the score for loading steel i1 and i2 on the same vehicle (penalty score is 0 for the same warehouse and 1 for different warehouses).

[0104] Step 2-2: Set the decision variables of the mathematical model as follows:

[0105]

[0106] Step 2-3: Set the constraint conditions of the mathematical model as follows:

[0107] (1) Any steel coil i can be assigned to at most one position of one wagon:

[0108]

[0109] (2) At most one steel coil can be assigned to any position k of any wagon j:

[0110]

[0111] (3) Any wagon j cannot exceed the maximum load limit:

[0112]

[0113] (4) The weight difference between the steel coils on the left and right sides of any wagon j does not exceed 1 ton:

[0114]

[0115] (5) The weight difference between the steel coils in any upper and lower position of any wagon j does not exceed 1 ton:

[0116]

[0117] (6) Once any wagon j is used, each position needs to be assigned a steel coil:

[0118]

[0119] (7) If any steel coil i is loaded onto a wagon, it must be transported by a vehicle:

[0120]

[0121] (8) Any steel coil i can be assigned to at most one vehicle:

[0122]

[0123] (9) The load of any vehicle c cannot exceed the maximum load limit:

[0124]

[0125] Step 2-4: Set the optimization objective of the mathematical model to obtain its corresponding mathematical model formula as follows:

[0126]

[0127] Step 3, solve the model through the large-scale neighborhood search algorithm to obtain the optimal rail and truck loading and unloading plan, which is specifically as follows:

[0128] Step 3-1: Set data initialization, including the following input data and algorithm parameters. Inventory data: order number, steel coil number, warehouse number, weight, specification, etc. Order data: order number, customer name, flow direction, order quantity, etc.

[0129] Step 3-2: Model encoding. This algorithm model is a two-layer knapsack problem. The encoding method of the rail loading and unloading plan is to use each wagon to be loaded as the encoding, and each encoding element represents a steel coil. The encoding method of the truck loading and unloading plan is the same, using each truck to be loaded as the encoding, and each encoding element represents a steel coil, where the encoding elements of the truck transportation must be included in the rail encoding.

[0130] Step 3-3: Generate the initial solution. This algorithm is mainly divided into generating the rail loading and unloading plan and the truck loading and unloading plan, and the latter loading and unloading must depend on the former's loading and unloading plan. Therefore, the algorithm model needs to first construct the initial rail loading and unloading plan, and then generate the truck loading and unloading plan on this basis. The specific generation steps are as follows:

[0131] Step 3-4: Neighborhood search operator design. The large-scale neighborhood search algorithm includes a destruction operator and a repair operator. The destruction operator removes some elements from the original encoding result, and then the repair operator reinserts the removed elements into the encoding structure to update the solution. The specific steps of the operator design in the present invention are as follows:

[0132] Step 3-4-1: Destruction operator. For the rail loading and unloading plan, first remove all encodings that do not conform to the loading and unloading plan, and secondly remove the encodings that conform to the loading and unloading plan with a certain probability. The higher the loading rate, the lower the removal probability, to retain a better loading and unloading plan. For the truck loading and unloading plan, all encodings are removed.

[0133] Step 3-4-2: Repair operator. For the railway transportation loading plan, it is crucial to re-insert the removed codes into the wagons. If inserted randomly, a large number of infeasible solutions may be generated, affecting the convergence effect of the model. Therefore, the process of inserting steel coils needs to refer to the railway transportation loading plan, rather than evaluating the feasibility according to the loading plan after insertion.

[0134] First, divide the resource pool. For different railway transportation loading schemes, there are requirements for the specifications and weights of the steel coils that can be loaded. Therefore, first sort out the corresponding loadable steel coils based on the loading scheme. Secondly, the specifications of single-row and side-by-side are also restricted in the loading scheme, which also needs to be divided. Since railway transportation has high requirements for safe transportation and the balance factor of the wagons needs to be considered, it is necessary to consider whether it is balanced up, down, left, and right every time a steel coil is inserted, and the insertion of steel coils needs to be processed in pairs. Then, for the road transportation loading plan, based on the steel coils involved in the railway transportation loading plan, load them preferentially with the steel coils from the same warehouse, the same customer, and the same wagon into one vehicle.

[0135] Step 3-5: Recombination operator. For the railway transportation loading plan, by removing some unreasonable loading plans and then inserting them back into the railway transportation loading plan in the way of permutation and combination to generate multiple results.

[0136] Step 3-6: Acceptance criterion. Use the simulated annealing algorithm to ensure that the model solution does not fall into a local optimum and accept solutions that are worse than the current solution with a certain probability. Among them, T>0 is the temperature, f(w) is the objective value calculation function, w i and w b are the current solution and the current global optimum solution.

[0137] Step 3-7: Update the global optimum solution. If the current solution is better than the current global optimum solution, update the current solution to the current global optimum solution.

[0138] Step 3-8: Return to Step 3-5, and re-conduct the neighborhood search for the road transportation loading plan, and iterate until the maximum number of iterations is reached.

[0139] Step 3-9: Return to Step 3-4 to re-conduct the neighborhood search for the railway transportation loading plan, and iterate until the maximum number of iterations is reached. The global optimum solution corresponding to the end of the iteration is the railway transportation loading plan and the road transportation loading plan.

[0140] In summary, the combined loading method of steel coil trains and trucks proposed in this application significantly improves the railway transportation loading rate and overall logistics efficiency by optimizing the loading process of steel coil transportation. When formulating the loading plan, various factors such as the loading rules of trains and trucks within the steel plant area and the storage locations of steel coils are comprehensively considered to achieve efficient coordination between the two. This method not only refines resource allocation but also provides a more scientific and reasonable transportation strategy. Through this overall optimization method, enterprises can achieve more refined logistics management, which is thus transformed into significant economic benefits.

[0141] Figure 4 is a block diagram of a combined loading device for steel coil trains and trucks shown in an exemplary embodiment of this application. This device can be applied to Figure 1 the implementation environment shown. This device can also be applicable to other exemplary implementation environments and can be specifically configured in other devices. This embodiment does not limit the implementation environment applicable to this device.

[0142] As Figure 4 shown, this exemplary combined loading device for steel coil trains and trucks includes: an information acquisition module 410, a model construction module 420, a model solution module 430, and a loading plan execution module 440.

[0143] Among them, the information acquisition module 410 is used to obtain the information of the steel coils to be loaded, the loading restriction information, and the loading target; the model construction module 420 is used to construct a steel coil loading planning model based on the loading target. Among them, the input parameters of the steel coil loading model are determined based on the information of the steel coils to be loaded, the constraint conditions are generated based on the loading restriction information, and the decision variables are jointly determined based on the information of the steel coils to be loaded and the loading target; the model solution module 430 is used to solve the steel coil loading planning model to obtain a steel coil loading plan that meets the loading requirements; the loading plan execution module 440 is used to send the steel coil loading plan to the target end to realize steel coil loading and transportation based on the steel coil loading plan.

[0144] It should be noted that the combined loading device for steel coil trains and trucks provided in the above embodiment belongs to the same concept as the combined loading method of steel coil trains and trucks provided in the above embodiment. The specific ways in which each module and unit perform operations have been described in detail in the method embodiment and will not be repeated here. In actual application, the combined loading device for steel coil trains and trucks provided in the above embodiment can, according to needs, allocate the above functions to different functional modules, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above. This is not limited here either.

[0145] Embodiments of the present application also provide an electronic device, including: one or more processors; a storage device for storing one or more programs, which, when executed by the one or more processors, cause the electronic device to implement the coil train and vehicle combined loading method provided in each of the above embodiments.

[0146] Figure 5 FIG. shows a schematic structural diagram of a computer system of an electronic device suitable for implementing embodiments of the present application. It should be noted that, Figure 5 The computer system 500 of the electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0147] As Figure 5 shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 502 or the program loaded from the storage section 508 into the random access memory (RAM) 503, such as executing the method described in the above embodiments. In the RAM 503, various programs and data required for system operation are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. The input / output (I / O) interface 505 is also connected to the bus 504.

[0148] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed so that the computer program read from it can be installed into the storage section 508 as needed.

[0149] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, various functions defined in the system of the present application are executed.

[0150] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0151] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. In these, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, as well as combinations of blocks in the block diagram or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0152] The units involved in the embodiments described in the present application can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not, in some cases, constitute a limitation on the units themselves.

[0153] On the other hand, the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor of a computer, the computer is caused to execute the combined loading method of steel coils by train and automobile as described above. The computer-readable storage medium may be included in the electronic device described in the above embodiments, or may exist separately without being assembled into the electronic device.

[0154] On the other hand, the present application also provides a computer program product or a computer program. The computer program product or the computer program includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to execute the combined loading method of steel coils by train and automobile provided in the above various embodiments.

[0155] The above embodiments are only illustrative of the principles and effects of the present application and are not intended to limit the present application. Any person familiar with this technology can make modifications or changes to the above embodiments without departing from the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed in the present application should still be covered by the claims of the present application.

Claims

1. A combined loading method for steel coils by train and truck, characterized in that, The method includes: Obtaining the information of coils to be stowed, stowage restriction information, and stowage objectives; Constructing a coil stowage planning model based on the stowage objectives, where the input parameters of the coil stowage model are determined based on the information of coils to be stowed, the constraint conditions are generated based on the stowage restriction information, and the decision variables are jointly determined based on the information of coils to be stowed and the stowage objectives; Solving the coil stowage planning model to obtain a coil stowage plan that meets the stowage requirements; Sending the coil stowage plan to the target end to implement coil stowage and transportation based on the coil stowage plan.

2. The combined loading method of steel coils by train and car according to claim 1, characterized in that Solving the coil stowage planning model includes: Obtaining the initial values of each model parameter based on the information of coils to be stowed; Inputting the initial values into the coil stowage planning model to generate an initial stowage plan, where an initial rail transportation stowage plan is preferably generated first, and then a road transportation stowage plan is generated based on the rail transportation plan; Optimizing the initial stowage plan to obtain an updated stowage plan that meets the stowage objectives.

3. The combined loading method of steel coils by train and car according to claim 2, characterized in that, Constructing the coil stowage planning model further includes: Encoding the vehicles for stowage, where in the rail transportation stowage plan, a single car body is used as the encoding unit, and in the road transportation stowage plan, a single vehicle is used as the encoding unit. Each encoding element represents a coil to be stowed, and the road transportation encoding elements are a subset of the rail transportation encoding elements.

4. The combined loading method of steel coils by train and automobile according to claim 3, characterized in that Optimizing the initial stowage plan includes: Removing the eliminated encodings in the initial rail transportation stowage plan and the encodings in the initial road transportation stowage plan. The eliminated encodings include those that do not meet the stowage objectives and those that meet the stowage objectives selected based on a preset elimination probability; Determining a stowable resource pool based on the initial rail transportation stowage plan, screening target coils that meet the preset screening conditions from the stowable resource pool, and inserting the target coils in pairs into the non-removed initial rail transportation stowage plan on the premise of meeting the car body balance constraint conditions to obtain an updated rail transportation stowage plan; Taking the coils corresponding to the encoding elements in the updated rail transportation stowage plan as the coils to be allocated, and allocating the coils to be allocated to different vehicles, where the coils to be allocated in the same warehouse and transported to the same customer are preferably allocated to the same vehicle; Reinserting the removed encodings into the updated rail transportation stowage plan through permutation and combination to generate a target rail transportation stowage plan, and generating a target road transportation stowage plan based on the target rail transportation stowage plan.

5. The combined loading method of steel coils by train and car according to claim 4, characterized in that, After obtaining the updated stowage plan that meets the stowage objectives, it further includes: Determining the target rail transportation stowage plan and the target road transportation stowage plan as the target stowage plan, and calculating the objective function value of the plan in the coil stowage planning model; Receiving the eliminated encodings with a preset acceptance probability based on the acceptance criterion of the simulated annealing algorithm, and calculating the current objective function value of the eliminated encodings in the coil stowage planning model; If the current objective function value is better than the objective function value of the plan, replacing the updated stowage plan with the stowage plan corresponding to the current objective function value as the target stowage plan.

6. The combined loading method of steel coil trains and trucks according to any one of claims 1-5, characterized in that Before constructing the coil stowage planning model, it further includes: Screen the information categories of the steel coil information to be stowed to obtain key items related to steel coil stowage, and determine the key items as model parameters; Identify the relationships between the model parameters and the stowage target to generate parameter combinations that affect the stowage target, and determine the parameter combinations as decision variables.

7. The combined loading method of steel coils by train and automobile according to claim 6, characterized in that, Generate constraint conditions based on the stowage restriction information, where the constraint conditions at least include: Each steel coil to be stowed is allocated to at most one stowage position, and at most one steel coil to be stowed is allocated to any stowage position; The weight difference between steel coils on different layers or different sides of the same railcar is less than or equal to the corresponding preset weight difference threshold; The total weight of the steel coils stowed on any railcar or truck is less than or equal to the corresponding preset weight threshold.

8. A combined loading device for steel coils on trains and trucks, characterized in that, The device includes: An information acquisition module, configured to obtain steel coil information to be stowed, stowage restriction information, and a stowage target; A model construction module, configured to construct a steel coil stowage planning model based on the stowage target, where the input parameters of the steel coil stowage model are determined based on the steel coil information to be stowed, the constraint conditions are generated based on the stowage restriction information, and the decision variables are jointly determined based on the steel coil information to be stowed and the stowage target; A model solving module, configured to solve the steel coil stowage planning model to obtain a steel coil stowage plan that meets the stowage requirements; A stowage plan execution module, configured to send the steel coil stowage plan to the target end to implement steel coil stowage and transportation based on the steel coil stowage plan.

9. An electronic device, characterized in that, The electronic device includes: One or more processors; A storage device, configured to store one or more programs, and when the one or more programs are executed by the one or more processors, enable the electronic device to implement the combined railcar and truck stowage method for steel coils according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, A computer program is stored thereon, and when the computer program is executed by a processor of the computer, enable the computer to execute the combined railcar and truck stowage method for steel coils according to any one of claims 1 to 7.

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