Heat treatment ship plate production order combination optimization-oriented mother board optimization design method and system, computer equipment and storage medium

Abstract

The invention discloses a mother board optimization design method and system for heat treatment ship plate production order combinatorial optimization, computer equipment and a storage medium, and the method comprises the steps: accessing order information, obtaining a design rule, determining a mathematical model for combinatorial optimization, initializing a target function and a constraint condition, and carrying out the optimization of a heat treatment ship plate production order. Grouping all orders according to the widths of the order daughter boards; the number of the mother boards is calculated, and the minimum value of the number of the mother boards is calculated according to the total weight of all the orders in the group; performing paper composition on the order according to the width to obtain an initial scheme; adjusting the sub-orders on each mother board according to the 0-1 knapsack problem, and solving the 0-1 knapsack problem based on a genetic algorithm to obtain a final scheme; and outputting the final scheme to the data table, and reading data from the data table by the production system and displaying a result. According to delivery requirements, the size and the number of mother boards are designed, and orders of mother roll combination delivery are achieved, so that the blank length is maximized, and the remaining material amount is minimized.

Description

Technical Field

[0001] The present application belongs to the technical field of ship plate production, and specifically relates to a motherboard optimization design method, system, computer equipment and storage medium for combination optimization of heat treatment ship plate production orders. Background Art

[0002] At present, in the production of ship plates, since user orders are characterized by multiple varieties and small batches, in order to meet customer needs, multiple small-sized orders (same material, same thickness, different widths, different lengths) must be combined and fulfilled with one steel coil, which can greatly improve the cross-cutting production organization capacity while increasing the cross-cutting yield rate.

[0003] The order combination material design problem can be regarded as an extension of the classic cutting stock problem (CSP), that is, the cutting stock problem that considers the decision-making uncertainty of the mother roll and mother board specifications. Studying the optimization design method of this problem is of great significance to improving the operating efficiency of the system and reducing production costs.

[0004] The classic cutting problem mainly studies how to cut small-sized products required by users from a given large-sized parent material to achieve the optimal goal. In recent years, the main research in this area includes: Gilmore et al. established a linear programming model for the cutting problem and proposed an optimization solution algorithm framework based on column generation technology; Schetyhauer et al. studied the solution method for the cutting problem with only one parent material of a certain length and designed a cutting plane method that can effectively solve small-scale problems; Poldi et al. discussed a variety of heuristic algorithms for the cutting problem of parent materials with multiple optional lengths. These studies all assume that the length and width of the parent material are already determined, so they are suitable for the optimization design problem of material utilization with determined specifications.

[0005] However, the design specifications of the order combination material design problem are designed first and then produced. Before design, the quantity and specifications of the motherboards and mother rolls are uncertain. Obviously, the design method of the above-mentioned classic material cutting problem is difficult to adopt directly. Some scholars have conducted relevant research on this uncertain material cutting problem: Zheng Zhong and others numbered all the motherboard section specifications, encoded the motherboard section selection for each order, and sought the optimal solution for the production order combination optimization based on column generation technology and taboo search. However, the algorithm has a large computational scale and does not make good use of the constraint rules between the motherboard specifications and the order sub-boards.

[0006] Application Contents

[0007] In order to overcome the shortcomings of the prior art, the present application provides a motherboard optimization design method, system, computer equipment and storage medium for optimizing the combination of heat-treated shipboard production orders, so as to design the size and number of motherboards and the delivery orders of each mother roll combination based on the delivery requirements of the sales order and some given rules, so as to maximize the length of the blank and minimize the amount of waste material.

[0008] In order to achieve the above objectives, this application adopts the following technical solutions:

[0009] A motherboard optimization design method for heat-treated shipboard production order combination optimization, comprising:

[0010] Access order information, place an order from ERP, and the production system receives and saves the order information, which includes the thickness, width, length and quantity of the order sub-board;

[0011] Acquire design rules, wherein the design rules include motherboard design rules and motherboard-mother-roll-daughter-board conversion rules;

[0012] Determining a mathematical model for combinatorial optimization, wherein the mathematical model includes an objective function and constraints;

[0013] Initialize the parameters of the objective function and the constraint conditions, group all orders according to the width of the order sub-board according to the order information, and arrange all groups in descending order according to the width;

[0014] Calculate the number of motherboards and find the minimum number of motherboards based on the total weight of all orders in the group;

[0015] The orders are grouped according to width to obtain an initial solution, where the width of each motherboard is equal to the longest width of the order sub-board of the sub-order on the motherboard; the sub-order on the motherboard is the order corresponding to the sub-board on the motherboard;

[0016] Based on the length, width and order information of the sub-orders of each motherboard in the initial solution, the sub-orders on each motherboard are adjusted according to the 0-1 knapsack problem, wherein the adjustment includes: if the motherboard is overweight or overlong, part of the order is allocated to the adjacent motherboard; if the motherboard is not long enough, part of the order is allocated from the adjacent motherboard;

[0017] Solve the 0-1 knapsack problem based on genetic algorithm to obtain the final solution;

[0018] The final solution is output to the data table, and the production system reads data from the data table and displays the results.

[0019] Further, the motherboard design rules include motherboard thickness, minimum and maximum length restrictions, and maximum weight constraints;

[0020] The conversion rules of motherboard, mother roll and daughter board are as follows: in is the length of the jth motherboard, T slab is the thickness of the motherboard, is the length of the jth mother roll, T coil is the thickness of the mother roll, λ1 is the feeding coefficient from the mother board to the mother roll, and λ1 is a real number not less than 1.

[0021] Furthermore, the objective function is:

[0022]

[0023] Among them, G order Represents the total weight of the order, G coil represents the total weight of the mother roll, j is the motherboard serial number, a total of p; i is the order serial number, a total of q; ρ represents the density of the motherboard, mother roll, and daughter board; n i Indicates that the number of sub-boards of each order combined on the mother roll meets the order requirements; T order Represents the thickness of the order; Represents the length of the sub-board of order i; Represents the width of the sub-board of order i; T coil Represents the thickness of the parent roll; Represents the length of the parent volume j; Represents the width of the parent volume j.

[0024] Furthermore, the constraint condition is:

[0025]

[0026] T coil =T order (11);

[0027]

[0028] λ1≥1,λ2≥1 (14);

[0029]

[0030] Combining constraints (6) and (12), for each motherboard with a certain width, the final maximum weight of the motherboard is:

[0031]

[0032] Among them, the superscript slab represents the parameters of the motherboard, j is the motherboard number, and there are p in total; represents the weight of motherboard j; represents the length of motherboard j; represents the width of motherboard j; T slab Represents the thickness of the motherboard; Represents the upper weight limit of the mother board j; Represents the upper weight limit of the mother board that the traveling crane can bear; And Represents the minimum and maximum length of the mother board;

[0033] The superscript "coil" represents the parameters of the master roll. j is the serial number of the mother board, with a total of p, which has a one-to-one correspondence with the mother board; G coil Represents the total weight of the master roll; Represents the weight of the master roll j; Represents the length of the master roll j; Represents the width of the master roll j; T coil Represents the thickness of the master roll;

[0034] The superscript "order" represents the parameters of the order. i is the order number, with a total of q; G order Represents the total weight of the order; Represents the total weight of order i; Represents the length of the sub-board of order i; Represents the width of the sub-board of order i; T order Represents the thickness of the order; n i Represents the number of sub-boards of order i;

[0035] ρ represents the density of the mother board, master roll, and sub-board; λ1 is the feeding coefficient from the mother board to the master roll; λ2 is the feeding coefficient from the master roll to the sub-board; x ij Is a 0-1 variable, which is 1 if the mother board j contains the sub-board of order i, otherwise it is 0.

[0036] Furthermore, the adjustment includes:

[0037] Mark the mother board of the separated order as out, and mark the mother board of the obtained order as in;

[0038] If out < in, then the items in the knapsack problem are all orders with the minimum width in out and all orders with the minimum width in in;

[0039] If out > in, then the items in the knapsack problem are all orders with the maximum width in out and all orders with the maximum width in in.

[0040] Furthermore, the adjustment includes:

[0041] Calculate the maximum capacity capacity of the knapsack. The calculation rule of the capacity is as follows:

[0042] When the length or weight of the mother board in is insufficient:

[0043] If and So And flag = 1;

[0044] like and So And flag = 1;

[0045] like and So And flag = 0;

[0046] like and So And flag = 0;

[0047] Among them, flag = 1 means that the orders put into the backpack in the solution of the above 0-1 backpack problem are the orders allocated from the out motherboard to the in motherboard, and flag = 0 means that the orders not put into the backpack in the solution of the above 0-1 backpack problem are the orders allocated from the out motherboard to the in motherboard;

[0048] in, The minimum order weight to be left for out; The maximum order weight that can be divided out; The minimum order weight that in must receive; The maximum order weight that can be left for out;

[0049] G sum The total weight of the order representing the items in the 0-1 knapsack problem above; Represents the upper limit of the motherboard out weight.

[0050] Furthermore, the adjustment includes:

[0051] When the motherboard out length or weight exceeds the standard;

[0052] like and So And flag = 0;

[0053] like and So And flag = 0;

[0054] like and So And flag = 1;

[0055] like and So And flag = 1;

[0056] in, The maximum order weight to be left for out; out is the minimum order weight to be distributed; The maximum order weight that in can get; The minimum order weight to be left for out.

[0057] In addition, a motherboard optimization design system for heat-treated shipboard production order combination optimization is also provided, including:

[0058] The entry module is used to access the order information, to place the order from the ERP, and the production system receives and saves the order information, wherein the order information includes the thickness, width, length and quantity of the order sub-board;

[0059] An acquisition module, used for acquiring design rules, wherein the design rules include motherboard design rules and motherboard-mother-roll-daughter-board conversion rules;

[0060] A determination module, used to determine a mathematical model for combinatorial optimization, wherein the mathematical model includes an objective function and constraint conditions;

[0061] An initialization module, used to initialize the parameters of the objective function and the constraint conditions, group all orders according to the width of the order sub-board according to the order information, and arrange all groups in descending order according to the width;

[0062] A calculation module is used to calculate the number of motherboards and calculate the minimum number of motherboards according to the total weight of all orders in the group;

[0063] The roll assembly module is used to assemble the orders according to the width to obtain an initial plan, wherein the width of each motherboard is equal to the longest width of the order subboard of the suborder on the motherboard; the suborder on the motherboard is the order corresponding to the subboard on the motherboard;

[0064] An adjustment module is used to adjust the sub-orders on each motherboard according to the 0-1 knapsack problem based on the length and width of each motherboard and the order information of the sub-orders in the initial solution, wherein the adjustment includes: if the motherboard is overweight or overlong, part of the order is allocated to the adjacent motherboard; if the motherboard is not long enough, part of the order is allocated from the adjacent motherboard;

[0065] The final solution acquisition module is used to solve the 0-1 knapsack problem based on the genetic algorithm to obtain the final solution;

[0066] The output module is used to output the final solution to the data table. The production system reads data from the data table and displays the results.

[0067] In addition, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0068] In addition, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0069] Compared with the prior art, this application has the following advantages:

[0070] This application combines the needs of enterprises to design rolls for order-oriented production of heat-treated ship plates. According to order characteristics, production processes, equipment and other constraints, an optimization control model is established with the goal of minimizing the number of mother rolls and maximizing the yield rate, and decisions are made on the combination of sub-orders, the length and width of mother plates and mother rolls. After receiving the order information, a rough initial plan is generated according to the order characteristics and the objective function, and then each mother plate is analyzed, and the mother plates that do not meet the constraints are adjusted, which are converted into a 0-1 knapsack problem, and the "items" of the knapsack problem and the "maximum capacity" of the knapsack are determined, and the solution is adjusted using a genetic algorithm-based solution. After all mother plates are analyzed, the final solution is output. This application can reduce the mother plate waste and material loss, and can better meet production needs. Moreover, compared with the method of searching for the optimal solution globally, this local fine-tuning method can reduce a large amount of calculation and search while ensuring a better solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application but do not constitute an improper limitation on the present application. In the drawings:

[0072] Figure 1 A flow chart of the method of this application;

[0073] Figure 2 A schematic diagram of the structure of the computer device of the present application;

[0074] Figure 3 This is a schematic diagram of the structure of another computer device of the present application. DETAILED DESCRIPTION

[0075] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0076] In the description of the present application, it should be understood that the orientation or positional relationship indicated by the terms and the like is based on the orientation or positional relationship shown in the accompanying drawings, which is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device, element, module, system, platform or device referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. The following description of the present application is only understood as a description of individual embodiments of the technical solution of the present application. Other embodiments are not reflected in the following description, but it does not mean that the present application excludes these other embodiments, and the technical solution of the present application is not limited to the specific implementation methods described below, and the protection scope of the present application is not limited to only the specific implementation methods described below. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present application.

[0077] It should be noted that if the terms "first", "second", etc. appear in the specification and claims of the present application and the above-mentioned drawings, the description is only used to distinguish similar objects, and is not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0078] In some embodiments, Figure 1 As shown, the present application provides a motherboard optimization design method for heat-treated shipboard production order combination optimization, and the specific steps include:

[0079] Step 1: Access order information.

[0080] Specifically, the sales department issues an order from ERP, and the production system receives and saves the order information. The order information includes the thickness, width, length and quantity of the order sub-board.

[0081] Step 2: Get the design rules.

[0082] Specifically, the design rules input by the on-site personnel may be obtained from a designated page, including motherboard design rules and motherboard, mother-roll and daughter-board conversion rules.

[0083] Motherboard design rules include: motherboard thickness, minimum and maximum length limits, and maximum weight constraints;

[0084] The conversion rules of mother board, mother roll and daughter board include the feeding coefficient. The conversion method is: in is the length of the jth motherboard, T slab is the thickness of the motherboard, is the length of the jth mother roll, T coil is the thickness of the mother coil, λ1 is the feeding coefficient from the mother plate to the steel coil, which is generally a real number not less than 1.

[0085] The above data can be adjusted according to actual conditions.

[0086] Step 3: Determine the mathematical model of the combined optimization design, including the objective function and constraints.

[0087] The objective function is:

[0088]

[0089] in

[0090]

[0091] The objective function (1) represents the maximization of the yield rate. According to the formula: yield rate = order delivery quantity / steel coil feed weight × 100%, it can be seen that the yield rate is inversely proportional to the motherboard feed quantity, while the motherboard quantity and the mother coil quantity are linearly positively correlated. The sub-board delivery quantity is the sum of the total quantity of each order.

[0092] Therefore, the problem of maximizing the yield rate is transformed into the problem of minimizing the total weight of the parent roll as described in formula (4).

[0093] min G coil (4)

[0094] The constraints are:

[0095]

[0096]

[0097] T coil =T order (11)

[0098]

[0099] λ1≥1,λ2≥1 (14)

[0100]

[0101] Constraint (5) represents the number of sub-boards of each order combined on the mother roll to meet the requirements of the sales order;

[0102] Constraints (6) to (8) describe the conversion rules between the weight and length of the motherboard and the length, width and thickness of the mother roll;

[0103] Constraints (9) to (11) express the conversion relationship between the length, width and thickness of the mother roll and the total length, width and thickness of the orders combined on the mother roll. Considering factors such as material loss during rolling and trimming, the weight of the mother plate should be greater than the weight of the mother roll. Under the condition of the same density, the mass relationship between the two is shown in constraint (6); similarly, considering the processing of cutting and trimming, the length of the mother roll should be greater than the sum of the lengths of each sub-order, the width should be the maximum width of each sub-order, and the thickness should be the same as the thickness of the order;

[0104] Constraint (12) represents the maximum weight constraint of the motherboard. Since the load-bearing capacity of the trolley is limited, the weight of the motherboard cannot be greater than the maximum load-bearing capacity of the trolley.

[0105] Constraint (13) represents the minimum and maximum length constraints of the motherboard. On the one hand, if the motherboard is too short, the production efficiency will be reduced and it will be difficult to achieve economic benefits. On the other hand, if the motherboard is too long, it will increase the difficulty of production and increase the burden on the equipment. Therefore, the length of the motherboard must be controlled within an appropriate range.

[0106] Combining constraints (6) and (12), we can see that for each motherboard with a certain width, its final maximum weight is:

[0107]

[0108] Constraints (14) to (15) represent the value ranges of several parameters.

[0109] The specific meanings of the parameters in the above formula are:

[0110] Motherboard parameters:

[0111] The superscript slab represents the parameters of the motherboard, j is the motherboard number, and there are p motherboards in total;

[0112] represents the weight of motherboard j;

[0113] represents the length of motherboard j;

[0114] represents the width of motherboard j;

[0115] Tslab Represents the thickness of the motherboard;

[0116] represents the upper weight limit of motherboard j;

[0117] Represents the upper limit of the motherboard weight that the vehicle can bear;

[0118] and Represents the minimum and maximum length of the motherboard.

[0119] Parent volume parameters:

[0120] The superscript "coil" represents the parameters of the mother coil, j is the motherboard serial number, there are p of them in total, and they have a one-to-one correspondence with the motherboard;

[0121] G coil Represents the total weight of the parent roll;

[0122] represents the weight of the parent roll j;

[0123] Represents the length of the parent volume j;

[0124] Represents the width of the parent roll j;

[0125] T coil Represents the thickness of the parent roll.

[0126] Order parameters:

[0127] The superscript "order" represents the order parameter, i is the motherboard serial number, and there are q motherboards in total;

[0128] G order Represents the total weight of the order;

[0129] Represents the total weight of order i;

[0130] Represents the length of the sub-board of order i;

[0131] W i order Represents the width of the sub-board of order i;

[0132] T order Represents the thickness of the order;

[0133] n i Represents the number of sub-boards for order i.

[0134] coefficient:

[0135] ρ represents the density of the motherboard, steel coil and daughterboard;

[0136] λ1 is the feeding coefficient from motherboard to mother roll;

[0137] λ2 is the feeding coefficient of the steel coil after taking into account material losses such as cutting heads and tails. If not taken into account, the value can be 1.

[0138] Decision variables:

[0139] x ij is a 0-1 variable, which is 1 if the parent volume j of order contains the sub-board of order i, otherwise it is 0;

[0140] Step 4: Initialize the model and algorithm parameters, group all orders by width based on the order information, and sort all groups in descending order of width.

[0141] It can be assumed here that there is no situation where a certain width alone will exceed the maximum weight of the motherboard. If there is, some orders can be rolled separately and then these orders can be removed from the grouping.

[0142] Step 5: Calculate the number of motherboards and find the minimum number of motherboards based on the total weight of all orders in the group.

[0143] Step 6: Group the orders by width to get the initial plan. The width of each motherboard is equal to the longest width of the sub-orders on the motherboard.

[0144] According to the calculation formula of the yield rate, it can be known that the yield rate of orders with a smaller width span combined on the same motherboard is higher than that of orders with a larger width span combined on the same motherboard. Based on this feature, the patent first assembles orders with similar widths and labels the motherboards (starting from 0). When assembling, try to ensure that each motherboard does not exceed the maximum weight, or if it exceeds the maximum weight, it means that the motherboard has been assembled.

[0145] Step 7: Analyze the length, width and sub-order design of each motherboard in the solution.

[0146] It is mainly aimed at the situation that the motherboard is overweight or not long enough. If the motherboard is overweight or too long, part of the order can be allocated to the adjacent motherboards, and the orders can be allocated to the adjacent motherboards with larger width first. This will not affect the width of the motherboard receiving the order, and the impact on the yield rate will be smaller. If the motherboard is not long enough, some orders can be allocated from the adjacent motherboards, and the orders can be allocated to the adjacent motherboards with smaller width first. This will not affect the width of the current motherboard, and the impact on the yield rate will be smaller.

[0147] In the embodiments of the present application, the order reallocation problem during the scheme adjustment process is regarded as a 0-1 knapsack problem. Therefore, first, it is necessary to know what "items" exist in this 0-1 knapsack problem. In the present application, the motherboard number of the split order is marked as out, and the motherboard number of the received order is marked as in. Obviously, there is no case where out = in. If out < in, then the "items" in the knapsack problem are all the orders with the minimum width (set as W) in out and all the orders with width W in in. If out > in, then the "items" in the knapsack problem are all the orders with the maximum width (set as W) in out and all the orders with width W in in.

[0148] Another important key point in converting the above scheme adjustment problem into a 0-1 knapsack problem is to calculate the maximum capacity capacity of the "knapsack". In this embodiment, the calculation rule of capacity is as follows:

[0149] (1) The length or weight of motherboard in is insufficient

[0150] If and then and flag = 1;

[0151] If and then and flag = 1;

[0152] If and then and flag = 0;

[0153] If and then and flag = 0.

[0154] (2) The length or weight of motherboard out exceeds the standard

[0155] If and then and flag = 0;

[0156] If and then and flag = 0;

[0157] If and then and flag = 1;

[0158] If and So And flag=1.

[0159] Among them, flag = 1 means that the orders put into the "backpack" in the solution of the above 0-1 backpack problem are orders allocated from the out motherboard to the in motherboard, and flag = 0 means that the orders not put into the "backpack" in the solution of the above 0-1 backpack problem are orders allocated from the out motherboard to the in motherboard. Assume that the total weight of the orders representing the "items" in the above 0-1 backpack problem is G sum , Represents the upper weight limit of the motherboard out. The meanings of the other variables are shown in the following table.

[0160] Table 1 Meaning of variables

[0161]

[0162]

[0163] Step 8: Determine whether the "maximum capacity" of the backpack is greater than the minimum weight of all orders representing "items". If so, it means that the order can be directly regarded as a complete individual, and the solution can be adjusted by selecting the "item". The genetic algorithm can be selected to solve the above 0-1 backpack problem. Since a set of candidate solutions is used instead of one candidate solution, the genetic algorithm is more likely to find the global optimal solution; if not, if the order is still regarded as a complete individual, then the solution to the above 0-1 backpack problem must not contain items placed in the backpack, and the solution cannot be adjusted. Therefore, this application splits the above order into 1 sub-order, recalculates the weight and length of each sub-order, and screens out the sub-orders with a weight less than the "maximum capacity" as the "items" of the new 0-1 backpack problem. Compared with the previous 0-1 backpack, this new 0-1 backpack problem is smaller in scale and has higher precision requirements. Therefore, dynamic programming is used to solve it and obtain the optimal solution for adjusting the solution.

[0164] Step 9: Output the final solution to the specified data table. The production system reads data from the table and displays the results.

[0165] In the implementation of the scheme of this application, the heat-treated ship plate production of a domestic enterprise was used as the experimental object. The mother plate / steel coil / daughter plate density of the experimental input data is ρ = 7.85×10 -9 t / mm 3 , motherboard thickness T slab =240mm, the maximum weight of the motherboard is The minimum and maximum lengths of the motherboard are The feeding coefficient λ1=1.013, λ2=1.013. The main information of the production order is shown in Table 2. The length range is 6000mm-14000mm, the width range is 1600mm-2000mm, and the quantity range is 1-5. The algorithm is programmed in Python and runs on a computer with Windows 10 operating system. The units of width, length, and thickness are all millimeters (mm), and the units of weight are all tons (t). I will not go into details later.

[0166] Table 2 Production Order

[0167] ID thickness width length quantity weight 1 6 1600 6000 20 9.043 2 6 1600 6050 18 8.207 3 6 1700 6100 25 12.211 4 6 1800 6150 24 12.514 5 6 1900 6250 23 12.864 6 6 2000 6300 23 13.650

[0168] The total weight of the above orders is 68.488, and each one cannot be rolled separately. If the orders are not split, the above production orders need to be merged into at least 3 slabs for production to be fulfilled, but a lot of waste materials will be generated. If the implementation plan of this application is adopted, only 2 slabs are needed, and the specific slab production specifications are as follows:

[0169] Table 3 Slab information

[0170] Slab number Slab width Slab length Order Weight Slab weight Coil weight 0 2000 9676 34.856 36.46 35.992 1 1800 10765 33.632 36.506 36.038

[0171] The specific order merging information is as follows:

[0172] Table 4 Order consolidation information

[0173] ID width quantity weight Slab number 1 1.6 20 9.043 1 2 1.6 18 8.207 1 3 1.7 25 12.211 1 4 1.8 8 4.171 1 4 1.8 16 8.342 0 5 1.9 23 12.864 0 6 2 23 13.650 0

[0174] Obviously, the implementation scheme of the present application splits order No. 4, a part of which is merged and generated on slab No. 1, and the remaining part is merged and produced on slab No. 0, with a final yield rate of 95.08%.

[0175] In some embodiments, a motherboard optimization design system for heat-treated shipboard production order combination optimization includes:

[0176] The entry module is used to access the order information, to place the order from the ERP, and the production system receives and saves the order information, wherein the order information includes the thickness, width, length and quantity of the order sub-board;

[0177] An acquisition module, used for acquiring design rules, wherein the design rules include motherboard design rules and motherboard-mother-roll-daughter-board conversion rules;

[0178] A determination module, used to determine a mathematical model for combinatorial optimization, wherein the mathematical model includes an objective function and constraint conditions;

[0179] An initialization module, used to initialize the parameters of the objective function and the constraint conditions, group all orders according to the width of the order sub-board according to the order information, and arrange all groups in descending order according to the width;

[0180] A calculation module is used to calculate the number of motherboards and calculate the minimum number of motherboards according to the total weight of all orders in the group;

[0181] The roll assembly module is used to assemble the orders according to the width to obtain an initial plan, wherein the width of each motherboard is equal to the longest width of the order subboard of the suborder on the motherboard; the suborder on the motherboard is the order corresponding to the subboard on the motherboard;

[0182] An adjustment module is used to adjust the sub-orders on each motherboard according to the 0-1 knapsack problem based on the length and width of each motherboard and the order information of the sub-orders in the initial solution, wherein the adjustment includes: if the motherboard is overweight or overlong, part of the order is allocated to the adjacent motherboard; if the motherboard is not long enough, part of the order is allocated from the adjacent motherboard;

[0183] The final solution acquisition module is used to solve the 0-1 knapsack problem based on the genetic algorithm to obtain the final solution;

[0184] The output module is used to output the final solution to the data table. The production system reads data from the data table and displays the results.

[0185] Each module in the motherboard optimization design system for heat-treated shipboard production order combination optimization can be implemented in whole or in part by software, hardware and their combination. Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0186] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 2As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a motherboard optimization design system method for combination optimization of heat-treated ship plate production orders is implemented.

[0187] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless method can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a motherboard optimization design system method for optimizing the combination of production orders for heat-treated ship plates is implemented. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse, etc.

[0188] Those skilled in the art will understand that Figure 2 and Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0189] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0190] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0191] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0192] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0193] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in any type of volatile or non-volatile storage device, or a combination thereof. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache.By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDR AM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), direct RAM bus random access memory (DRRAM). The storage medium described in the embodiments of the present application is intended to include but is not limited to these and any other suitable types of memory.

[0194] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0195] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A motherboard optimization design method for heat-treated shipboard production order combination optimization, characterized in that: Including: Access the order information, issue the order from the ERP, and the production system receives and saves the order information. The order information includes the thickness, width, length, and quantity of the order sub-boards; Obtain the design rules, where the design rules include the motherboard design rules and the motherboard-mother roll-sub-board conversion rules; Determine the mathematical model for combinatorial optimization, where the mathematical model includes the objective function and the constraints; Initialize the parameters of the objective function and the constraints. Group all the orders according to the width of the order sub-boards according to the order information, and arrange all the groups in descending order of width; Calculate the number of motherboards, and calculate the minimum value of the number of motherboards according to the total weight of all the orders in the group; Group the orders by width to obtain the initial plan. The width of each motherboard is equal to the longest width of the order sub-boards of the sub-orders on that motherboard; The sub-orders on the motherboard are the orders corresponding to the sub-boards on that motherboard; Based on the length, width, and order information of the sub-orders on each motherboard in the initial plan, adjust the sub-orders on each motherboard according to the 0-1 knapsack problem. The adjustments include: if the motherboard is overweight or overlong, allocate some orders to the adjacent motherboard; if the length of the motherboard is insufficient, allocate some orders from the adjacent motherboard; Solve the 0-1 knapsack problem based on the genetic algorithm to obtain the final plan; Output the final plan to the data table, and the production system reads the data from the data table and displays the results.

2. The method for optimizing the design of the motherboard for the combinatorial optimization of the heat treatment ship plate production order according to claim 1, characterized in that: The motherboard design rules include the motherboard thickness, the minimum and maximum length limits, and the maximum weight constraint; The conversion rules of motherboard, mother roll and daughter board are as follows: in is the length of the jth motherboard, T slab is the thickness of the motherboard, is the length of the jth mother roll, T coil is the thickness of the mother roll, λ1 is the feeding coefficient from the mother board to the mother roll, and λ1 is a real number not less than 1.

3. The motherboard optimization design method for heat-treated shipboard production order combination optimization according to claim 1 is characterized in that: The objective function is: Among them, G order Represents the total weight of the order, G coil represents the total weight of the mother roll, j is the motherboard serial number, a total of p; i is the order serial number, a total of q; ρ represents the density of the motherboard, mother roll, and daughter board; n i Indicates that the number of sub-boards of each order combined on the mother roll meets the order requirements; T order Represents the thickness of the order; Represents the length of the sub-board of order i; Represents the width of the sub-board of order i; T coil Represents the thickness of the parent roll; Represents the length of the parent volume j; Represents the width of the parent volume j.

4. The motherboard optimization design method for heat-treated shipboard production order combination optimization according to claim 3 is characterized in that: The constraints are: T coil =T order (11); λ1≥1, λ2≥1 (14); Combined with constraints (6) and (12), for each motherboard with a determined width, the final maximum weight of the motherboard is: Among them, the superscript slab represents the parameters of the motherboard, j is the motherboard number, and there are p in total; represents the weight of motherboard j; represents the length of motherboard j; represents the width of motherboard j; T slab Represents the thickness of the motherboard; represents the upper weight limit of motherboard j; Represents the upper limit of the motherboard weight that the vehicle can bear; and Represents the minimum and maximum length of the motherboard; The superscript "coil" represents the parameters of the mother coil, j is the motherboard serial number, there are p of them in total, and they have a one-to-one correspondence with the motherboard; G coil Represents the total weight of the parent roll; represents the weight of the parent roll j; Represents the length of the parent volume j; Represents the width of the mother roll j; T coil Represents the thickness of the parent roll; The superscript "order" represents the order parameter, i is the order number, and there are q orders in total; G order Represents the total weight of the order; Represents the total weight of order i; Represents the length of the sub-board of order i; Represents the width of the sub-board of order i; T order Represents the thickness of the order; n i Represents the number of sub-boards for order i; ρ represents the density of the motherboard, mother roll, and daughter board; λ1 is the feeding coefficient from motherboard to mother roll; λ2 is the feeding coefficient from mother roll to daughter board; x ij It is a 0-1 variable, which is 1 if the motherboard j contains the sub-board of order i, otherwise it is 0.

5. The motherboard optimization design method for heat-treated shipboard production order combination optimization according to claim 4 is characterized in that: The adjustments include: Mark the motherboard that allocates the order as out, and mark the motherboard that receives the order as in; If out < in, then the items in the knapsack problem are all the orders with the minimum width in out and all the orders with the minimum width in in; If out > in, then the items in the knapsack problem are all the orders with the maximum width in out and all the orders with the maximum width in in.

6. The motherboard optimization design method for heat-treated shipboard production order combination optimization according to claim 5 is characterized in that: The adjustments include: Calculate the maximum capacity capacity of the knapsack, and the calculation rule of the capacity is as follows: When the length or weight of the motherboard in is insufficient: like and So And flag = 1; like and So And flag = 1; like and So And flag = 0; like and So And flag = 0; where flag = 1 represents that the orders placed in the knapsack in the solution of the above 0-1 knapsack problem are the orders allocated from the out motherboard to the in motherboard, and flag = 0 represents that the orders not placed in the knapsack in the solution of the above 0-1 knapsack problem are the orders allocated from the out motherboard to the in motherboard; in, The minimum order weight to be left for out; The maximum order weight that can be divided out; The minimum order weight that in must receive; The maximum order weight that can be left for out; G sum The total weight of the order representing the items in the 0-1 knapsack problem above; Represents the upper limit of the motherboard out weight.

7. A motherboard optimization design method for heat-treated shipboard production order combination optimization according to claim 6, characterized in that: The adjustments include: When the length or weight of the motherboard out exceeds the standard; like and So And flag = 0; like and So And flag = 0; like and So And flag = 1; like and So And flag = 1; in, The maximum order weight to be left for out; out is the minimum order weight to be distributed; The maximum order weight that in can get; The minimum order weight to be left for out.

8. A motherboard optimization design system for heat-treated shipboard production order combination optimization, characterized in that: Including: The access module is used to access the order information, issue the order from the ERP, and the production system receives and saves the order information. The order information includes the thickness, width, length, and quantity of the order sub-boards; An acquisition module, used for acquiring design rules, wherein the design rules include motherboard design rules and motherboard-mother-roll-daughter-board conversion rules; A determination module, used to determine a mathematical model for combinatorial optimization, wherein the mathematical model includes an objective function and constraint conditions; An initialization module, used to initialize the parameters of the objective function and the constraint conditions, group all orders according to the width of the order sub-board according to the order information, and arrange all groups in descending order according to the width; A calculation module is used to calculate the number of motherboards and calculate the minimum number of motherboards according to the total weight of all orders in the group; The roll assembly module is used to assemble the orders according to the width to obtain an initial plan, and the width of each motherboard is equal to the longest width of the order sub-boards of the sub-orders on the motherboard; The sub-order on the motherboard is the order corresponding to the sub-board on the motherboard; An adjustment module is used to adjust the sub-orders on each motherboard according to the 0-1 knapsack problem based on the length and width of each motherboard and the order information of the sub-orders in the initial solution, wherein the adjustment includes: if the motherboard is overweight or overlong, part of the order is allocated to the adjacent motherboard; if the motherboard is not long enough, part of the order is allocated from the adjacent motherboard; The final solution acquisition module is used to solve the 0-1 knapsack problem based on the genetic algorithm to obtain the final solution; The output module is used to output the final solution to the data table. The production system reads data from the data table and displays the results.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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