A steel plate storage optimization method based on heuristic scheduling rules

Abstract

The present application relates to a kind of steel plate storage optimization method based on heuristic scheduling rule.The method is optimized for the steel plate in warehouse, set the scene of existing steel plate in yard, meet the actual yard scheduling scenario, for the steel plate needing to be stored in warehouse is reasonably selected, with the minimum additional blocking plate number as optimization goal, the purpose is to reduce the number of times of steel plate outbound required to dump pile operation.The present application designs three heuristic scheduling rules as optimization algorithm.First, obtain the yard pile and the existing steel plate and the data of the steel plate in warehouse, and the optimization result reduces the number of times of steel plate in warehouse to dump pile, and promotes the efficiency of steel plate scheduling in logistics yard.

Description

Technical Field

[0001] This invention relates to the field of steel plate scheduling in steel logistics park yards, and particularly to a method for optimizing steel plate storage based on heuristic scheduling rules. Background Technology

[0002] With the rapid development of the national economy, my country's steel production ranks first in the world, and the industry's scale has reached an advanced level globally. The increase in steel production capacity has provided enormous development space for steel logistics, while also placing higher demands on it. However, the overall level of my country's steel logistics remains relatively low, especially in steel plate warehousing scheduling, which plays a crucial role in logistics dispatching and lacks a mature and scientific methodology. With the development of IoT technology, effectively acquiring information related to stockyards and steel plates has become possible. In this context, it is important to utilize relevant data to optimize the scheduling mechanism to increase the throughput of steel plates in stockyards. Therefore, inventing a steel plate storage scheduling method that can improve the efficiency of steel plate outbound from stockyards is of paramount importance.

[0003] Steel plate scheduling in steel logistics parks is a crucial factor determining the park's logistics efficiency. Due to the large daily throughput and highly customized nature of steel plates in storage yards, improper scheduling can lead to extensive re-stacking operations during outbound processing. Re-stacking is one of the most critical factors affecting logistics efficiency, and how to rationally schedule steel plates to reduce re-stacking is a major challenge for improving the efficiency of logistics park storage yards. Traditional steel plate storage scheduling is generally carried out manually on-site, which is highly arbitrary and only considers stacking safety without addressing the efficiency of outbound steel plate processing.

[0004] Chinese patent application CN201910629130.4, entitled "Method, System, Equipment, and Storage Medium for Optimizing Raw Material Stacking Layout in Steel Plants," describes a method for allocating raw material locations in steel plants. First, raw material data is acquired, and a mathematical model for raw material stacking layout is established based on this data. The mathematical model is initialized by inputting attribute parameters and weight constraint parameters of the material strips to be arranged, generating a pre-configuration result for the raw material stacking locations. A genetic algorithm is then used to optimize and adjust the pre-configuration result, outputting an optimized raw material stacking layout scheme for the steel plant. This improves production efficiency and management level. However, this method does not consider the customized attributes of steel plates or the impact of outbound dates on storage location allocation; therefore, it is not suitable for solving the problem of steel plate inbound scheduling.

[0005] Chinese patent application CN202111179927.2, entitled "A Method for Allocating Steel Stacking Locations Based on Energy Consumption and Scheduling Time," relates to a method for allocating steel stacking locations. First, based on historical order data and stacking location information, the total energy consumption and total time for each steel product to be dispatched from different stacking locations are determined. Then, each data point in the total energy consumption and total time matrices is divided by its maximum element, and the two sets of data are added together with a certain weight. Finally, stacking locations are allocated based on the steel product corresponding to the maximum data point. This method can effectively balance the dispatching time and energy consumption of steel products. However, this method does not consider the impact of the steel plate's dispatch date on storage scheduling; therefore, it is not suitable for solving the steel plate inbound storage scheduling problem in scenarios where there are already steel plates in the yard. Summary of the Invention

[0006] The purpose of this invention is to provide a steel plate storage optimization method based on heuristic scheduling rules. This method optimizes the scheduling of incoming steel plates, setting up a scenario with existing steel plates in the yard while ensuring stacking safety. This scenario aligns with actual yard scheduling, allowing for reasonable stacking location selection for steel plates requiring storage. The optimization objective is to minimize the number of additional obstructing plates, thereby reducing the number of stacking operations required for steel plates to be retrieved from the yard. This method designs three heuristic scheduling rules as optimization algorithms. First, it acquires data on yard stacking locations, existing steel plates, and incoming steel plates. The optimization results reduce the number of stacking operations for steel plates in the logistics park yard, thus improving the scheduling efficiency of steel plates in the logistics park yard.

[0007] To achieve the above objectives, the technical solution of the present invention is: a steel plate storage optimization method based on heuristic scheduling rules, comprising the following steps:

[0008] S1. Data Acquisition: Acquisition mainly includes yard stacking data, existing steel plate data in the stacks, and steel plate data in the warehouse; among which, yard stacking data mainly includes the stack set and the earliest outbound date of the steel plates in the stacks, and steel plate data mainly includes steel plate specifications and outbound date;

[0009] S2. Determine the optimization objective as minimizing the number of additional blocking plates, such as... Figure 1 As shown, the black steel plate is the earliest steel plate to leave the stack, defined as the target steel plate. The three shaded steel plates in the figure are the original baffles in the stack. Assuming that the gray steel plate currently stored has a later departure date than any steel plate in the stack, then this stored steel plate is defined as an additional baffle.

[0010] S3. The order of warehousing is specified as temporary stacking from top to bottom, with the top layer being the steel plate currently being warehoused.

[0011] S4. Select a stack location for the currently inbound steel plate according to the heuristic scheduling rules for steel plate storage;

[0012] S5. Set the order for the currently received steel plates as i, and the corresponding outbound date as D. i The earliest date for the steel plates to leave the warehouse in the stack is g. min The total number of steel plates in the stack whose outbound date is earlier than the outbound date of the currently received steel plates is R. s The number of baffles above the earliest steel plate to leave the stack is B. s If there are multiple steel plates with the earliest delivery date, the topmost plate will be used for calculation. R s and B s The calculation is as follows Figure 2 As shown, the horizontal axis represents the stack and the vertical axis represents the number of layers within the stack. Stack 0 is the temporary stack where the incoming steel plate is located. The number on each layer in the stack represents the outbound date of the steel plate at that location. The smaller the number, the earlier the outbound date. Steel plate 4 on stack 0 is the steel plate i that needs to be put into storage. The numbers on stacks 1, 2, 3, and 4 represent the steel plates that are already in the stack.

[0013] S6. Start storage scheduling. First, retrieve the currently inbound steel plate i and its outbound date D. i Determine if g exists min =D i If any of the stacks exist, select one for steel plate storage; otherwise, proceed to the next step.

[0014] S7. If g exists min >D i For stacking, choose g. min With D i Store the closest stack; otherwise, proceed to the next step.

[0015] S8. For heuristic scheduling rule H1, select R. s Store the smallest stack; if multiple identical smallest stacks exist, select the smallest one. min With D i Store in the nearest stack to minimize obstruction of existing steel plates within the stack; for heuristic scheduling rule H2, choose B. s Store the smallest stack; if multiple identical smallest stacks exist, select the smallest one. min With D i Store the closest stacks to minimize the number of stack repositioning steps required when the target steel plate is retrieved from the warehouse; for heuristic scheduling rule H3, directly select g. min With D i Store the closest stacks and delay necessary stacking operations as much as possible;

[0016] S9. Determine whether the specifications of the currently stored steel plate i meet the specifications of the selected stack. If the safety requirements are met, add the data of the stored steel plate to the corresponding stack data and delete it from the stored steel plate data, and then store the next steel plate. Otherwise, select a new stack for storage.

[0017] S10. When the data for the steel plates entering the warehouse is empty, the corresponding batch of steel plates entering the warehouse is completed and stored, and this result is used as the result of the optimized scheduling.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] 1. The scheduling method designed in this invention is applicable to scenarios where steel plates already exist in the yard. This method can flexibly store a batch of steel plates that need to be put into storage, which has practical significance and can be used in actual yard scheduling. Compared with traditional steel plate scheduling methods, it can reduce the stacking operations required for steel plates to be taken out of storage, thereby reducing the energy consumption of cranes, improving customer satisfaction, increasing the throughput of steel plates in the logistics park yard, and improving logistics efficiency.

[0020] 2. This invention designs three heuristic scheduling rules for selecting the storage location of incoming steel plates. Based on the customized attributes of steel plate height and scheduling characteristics, the algorithm selects the storage location of incoming steel plates from three different perspectives: minimizing the number of existing steel plates blocking the stack, minimizing the number of stacking operations required to remove the target steel plate from the stack, and delaying the necessary stacking operations as much as possible. Compared with actual scheduling, all of these methods effectively improve scheduling efficiency.

[0021] 3. The three heuristic scheduling algorithms proposed in this invention address the storage scheduling optimization problem of steel plates in the yard under the scenario of existing steel plates. A mixed integer linear programming model is established with the goal of minimizing additional obstruction plates, which determines the operation plan for steel plates that need to be stored in the warehouse at any time in the logistics park yard.

[0022] The advantages of this invention are as follows:

[0023] Compared to the patent for "Optimization Method, System, Equipment, and Storage Medium for Raw Material Stacking Layout in Steel Plants," this invention considers the scenario of existing steel plates in steel logistics park yards. It selects storage locations for a batch of steel plates requiring storage based on attributes such as their outbound time. This not only reduces the need for subsequent stacking operations for steel plate outbound but also improves the scheduling efficiency of the logistics park yard. Compared to the patent for "A Steel Stacking Allocation Method Based on Energy Consumption and Scheduling Time," this invention proposes three heuristic scheduling rules to solve the steel plate storage scheduling scheme in logistics park yards. This method not only reduces crane energy consumption and scheduling time by decreasing the number of stacking operations but also helps increase the throughput of logistics in the yard. Furthermore, this method is applicable to steel plate storage scheduling at any time in the logistics park and has practical significance. Attached Figure Description

[0024] Figure 1 This is a schematic diagram illustrating the optimization target of the present invention.

[0025] Figure 2 This is an example diagram illustrating the parameter calculations designed in this invention.

[0026] Figure 3 This is a flowchart of the algorithm proposed in this invention. Detailed Implementation

[0027] The technical solution of the present invention will now be described in detail with reference to the accompanying drawings.

[0028] This invention provides a steel plate storage optimization method based on heuristic scheduling rules. It optimizes the scheduling of incoming steel plates, setting up a scenario with existing steel plates in the yard while ensuring stacking safety. This scenario aligns with actual yard scheduling, allowing for reasonable stacking location selection for steel plates requiring storage. The optimization objective is to minimize the number of additional obstructing plates, thereby reducing the number of stacking operations required for steel plates to be retrieved from the yard. This method designs three heuristic scheduling rules as optimization algorithms. First, it acquires data on yard stacking locations, existing steel plates, and incoming steel plates. The optimization results reduce the number of stacking operations for steel plates in the logistics park yard, thus improving the scheduling efficiency of steel plates in the logistics park yard.

[0029] like Figure 3 As shown, the implementation process of the steel plate storage optimization method based on heuristic scheduling rules of the present invention is as follows:

[0030] (1) Obtaining Stockyard Data: There are 4 stacks available for storage in the stockyard, set S = [1, 2, 3, 4]. Each stack already contains some steel plates, as shown in Table 1. The minimum outbound date g for the 4 stacks can be determined. min =[2,2,3,2].

[0031] Table 1

[0032] <![CDATA[j1]]> 2 1 1 <![CDATA[j2]]> 5 1 2 <![CDATA[j3]]> 2 1 3 <![CDATA[j4]]> 4 1 4 <![CDATA[j5]]> 5 1 1 <![CDATA[j6]]> 3 2 2 <![CDATA[j7]]> 2 2 3 <![CDATA[j8]]> 2 2 4 <![CDATA[j9]]> 3 3 1 <![CDATA[j 10 ]]> 4 3 2 <![CDATA[j 11 ]]> 3 4 1 <![CDATA[j 12 ]]> 5 4 2 <![CDATA[j 13 ]]> 2 4 3 <![CDATA[j 14 ]]> 5 4 4

[0033] (2) Obtain the data of steel plates entering the warehouse. The temporary stack is defined as S=0. There are a total of 4 steel plates in the stack that need to be put into the warehouse. The specific data is shown in Table 2.

[0034] Table 2

[0035] <![CDATA[i1]]> 3 0 1 <![CDATA[i2]]> 3 0 2 <![CDATA[i3]]> 3 0 3 <![CDATA[i4]]> 4 0 4

[0036] (3) Determine that the current steel plate entering the warehouse is i4, D i =4.

[0037] (4) Determine if there exists a stack S that satisfies g min =Di Unsatisfied stacking.

[0038] (5) Determine if there exists a stack S that satisfies g min >D i Unsatisfied stacking.

[0039] (6) The steel plates currently being stored will become additional blocking steel plates. The storage location will be selected based on the differences between the three heuristic scheduling rules. For heuristic scheduling rule H1, the R of the four stacks will be calculated. s =[2,3,1,2], therefore stack 3 is chosen as the storage stack. For heuristic scheduling rule H2, the B of the four stacks is obtained. s =[2,1,2,2], therefore stack 2 is chosen as the storage stack. For heuristic scheduling rule H3, g is obtained. min With D i The differences are [2,2,1,2], so stack 3 is selected as the storage stack.

[0040] (7) Update the data of all stacks, add the data of the steel plate to the selected stack, and delete the steel plate data in the data of the steel plate to be stored.

[0041] (8) Determine the inbound set I r If the set is not empty, then continue with the next steel plate's entry into the warehouse, that is, determine i3 as the steel plate to be entered into the warehouse in the second stage, and repeat the above scheduling operation.

[0042] (9) When determining the inbound set I r When the set is empty, all steel plates are put into storage, and this is taken as the optimal scheduling result.

[0043] The above are preferred embodiments of the present invention. Any changes made to the technical solution of the present invention that do not exceed the scope of the technical solution of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for optimizing steel plate storage based on heuristic scheduling rules, characterized in that, Includes the following steps: S1. Data Acquisition: Acquire data including stockpile data, existing steel plate data in stockpiles, and steel plate data in warehouse; among which, stockpile data includes the stockpile set and the earliest outbound date of the steel plates in the stockpile, and steel plate data includes steel plate specifications and outbound date; S2. The optimization objective is to minimize the number of additional baffles. The target steel plate is the steel plate that leaves the stack earliest. The additional baffles are steel plates that have entered the warehouse and whose departure date is later than any other steel plate in the stack. S3. The order of warehousing is specified as temporary stacking from top to bottom, with the top layer being the steel plate currently being warehoused. S4. Select a stack location for the currently inbound steel plate according to the heuristic scheduling rules for steel plate storage; S5. Set the order for the currently received steel plates as i, and the corresponding outbound date as D. i The earliest date for the steel plates to leave the warehouse in the stack is g. min The total number of steel plates in the stack whose outbound date is earlier than the outbound date of the currently received steel plates is R. s The number of baffles above the earliest steel plate to leave the stack is B. s If there are multiple steel plates with the earliest delivery date, the topmost plate will be used for calculation. R s and B s The calculation method is as follows: the horizontal axis represents the stack and the vertical axis represents the number of layers in the stack. Stack 0 is the temporary stack where the steel plate is stored. The size of the number of each layer in the stack represents the outbound date of the steel plate for that location. The smaller the number, the earlier the outbound date. S6. Start storage scheduling. First, retrieve the currently inbound steel plate i and its outbound date D. i Determine if g exists min =D i If any of the stacks exist, select one for steel plate storage; otherwise, proceed to the next step. S7. If g exists min >D i For stacking, choose g. min With D i Store the closest stack; otherwise, proceed to the next step. S8. For heuristic scheduling rule H1, select R. s Store the smallest stack; if multiple identical smallest stacks exist, select the smallest one. min With D i Store in the nearest stack to minimize obstruction of existing steel plates within the stack; for heuristic scheduling rule H2, choose B. s Store the smallest stack; if multiple identical smallest stacks exist, select the smallest one. min With D i Store the closest stacks to minimize the number of stack repositioning steps required when the target steel plate is retrieved from the warehouse; for heuristic scheduling rule H3, directly select g. min With D i Store the closest stacks and delay necessary stacking operations as much as possible; S9. Determine whether the specifications of the currently stored steel plate i meet the specifications of the selected stack. If the safety requirements are met, add the data of the stored steel plate to the corresponding stack data and delete it from the stored steel plate data, and then store the next steel plate. Otherwise, select a new stack for storage. S10. When the data for the steel plates entering the warehouse is empty, the corresponding batch of steel plates entering the warehouse is completed and stored, and this result is used as the result of the optimized scheduling.

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