Intelligent layout method of concrete composite slab mold based on hybrid algorithm

Abstract

The present invention relates to a method for intelligently arranging molds of concrete composite panels based on a hybrid algorithm. The hybrid algorithm framework includes a mold platform and mold mathematical model generation part, a heuristic algorithm part based on a step-down algorithm and a maximum upper right corner distance heuristic rule, and a genetic algorithm part; a mathematical model is established, the mathematical model is input into the algorithm to calculate the mold arrangement mode, the placement sequence of different molds is evolved by a genetic algorithm, and then the arranged molds are placed one by one by a heuristic algorithm, and the optimal placement mode is obtained, and then the fitness function value is obtained through the placement mode, and the placement sequence of the molds is optimized through the fitness function value, and then the next placement and arrangement calculation is entered until the optimal solution is obtained, and the optimal solution is output to guide the arrangement of the mold on the mold platform. The present invention provides an intelligent arrangement method for the rational production of concrete composite panels, improves the utilization rate of molds, and belongs to a method for arranging prefabricated components in the construction industry.

Description

Technical Field

[0001] The invention relates to a method for arranging prefabricated components in the construction industry, and in particular to an intelligent method for arranging concrete composite slab molds based on a hybrid algorithm. Background Art

[0002] With my country's vigorous promotion of building industrialization and prefabricated buildings, prefabricated buildings as a new type of construction method have entered a golden period of development. Against this background, my country's prefabricated concrete component production companies have sprung up in large numbers, and the industry has gradually become mature and stable.

[0003] Although the emergence of a large number of production enterprises has promoted the development of the industry, most enterprises still face a lot of problems, such as the production process occupies a large amount of production land and mold amortization costs increase construction costs while improving efficiency, a large number of components are not scientific enough to waste time and cost, and the coordination of various production links is not perfect. These problems restrict the development of enterprises. Therefore, at this stage, for prefabricated construction enterprises, how to introduce scientific and reasonable production optimization methods, improve the production efficiency of production lines with high standards and high quality, meet the development needs of lean production of enterprises, and tap the potential of enterprises are common problems that today's prefabricated enterprises need to solve.

[0004] At present, most prefabricated component manufacturers use mobile mold table production lines. All process operations (cleaning, oiling, steel bar binding, maintenance and demolding) are carried out on a mold table. The mold table is loaded with different molds and continuously transferred from one process to another. The mold table, as a transfer tool, carries the mold to complete the entire process of prefabricated component production. Therefore, the utilization rate of the mold table has an important impact on the efficiency of the production line. However, there is a common problem in the utilization rate of the mold table in the prefabricated component production plant at present, that is, the molds are randomly arranged on the mold table by humans during the production process, and even one mold table carries one or two molds, and the utilization rate of the mold table is low. According to statistics, the utilization rate of the mold table is usually less than 50%, which leads to a small number of casting molds in each batch, resulting in a small number of components produced in a batch, which is only 30% to 50% of the designed production capacity. Therefore, using modern computer technology, introducing various packing problem algorithms, and studying how to improve the layout method of molds on the mold table and improve the utilization efficiency of the mold table play an important role in the optimization of the production line. Summary of the invention

[0005] In view of the technical problems existing in the prior art, the purpose of the present invention is to provide an intelligent arrangement method of concrete composite slab molds based on a hybrid algorithm, so as to improve the mold utilization rate in a concrete composite slab mobile mold table assembly line.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] An intelligent arrangement method for concrete composite slab molds based on a hybrid algorithm, the hybrid algorithm framework includes a part for generating mathematical models of the mold base and the mold, a heuristic algorithm part based on the step-down algorithm and the maximum upper right corner distance heuristic rule, and a genetic algorithm part; a mathematical model is established by manually inputting the size and number of the mold base and the mold, and the mathematical model is input into the heuristic algorithm and the genetic algorithm to calculate the mold arrangement method, the genetic algorithm is used to evolve the order of placing different molds, and then the heuristic algorithm is used to place the arranged molds one by one to obtain the optimal placement method, and then the fitness function value is obtained through the placement method, and the mold placement order is optimized through the fitness function value, and then the next placement arrangement calculation is entered until the optimal solution is obtained, and the optimal solution is output to guide the arrangement of the mold on the mold base.

[0008] As a preferred method, the method of establishing a mathematical model is: based on the existing production system, all component information of the production batch is obtained, and the component footprint module required by the algorithm is expanded by adding working distances to each side of the component mold; the size and number of the mold platform in the production system are converted into placed rectangular blocks, and a rectangular coordinate system is established based on the lower left corner of the mold platform, with the lower left corner of the mold platform as the coordinate origin, and the position of the component footprint module on the mold platform is converted into a coordinate value.

[0009] As a preferred method, the method of arranging the molds by using a heuristic algorithm is as follows: (1) selecting the mold i to be placed; (2) filling the rectangular block according to the remaining space method and selecting a possible placement position; (3) placing the mold i in the proposed position according to the step-down algorithm; (4) calculating the DFRTC value according to the maximum upper right corner distance heuristic rule and by flipping the direction of the mold; repeating steps (2)-(4) to calculate the DFRTC values ​​of all possible placement positions and placement methods; (5) selecting the maximum DFRTC value as the optimal solution; (6) updating the remaining space linked list and repeating steps (2)-(5) to complete the placement of the next mold i+1 until all molds are placed.

[0010] As a preferred embodiment, in step (3), the step-down algorithm is a layout method based on the principle of "bottommost and leftmost". When arranging, components are avoided from overlapping and exceeding the orientation. The edge of the mold platform is used as the boundary. The concrete composite slab mold is first moved downward to the lower end until it does not interfere with other components, and then the mold is moved to the leftmost end until it can no longer move; and while moving downward and leftward, the downward movement method is preferably used.

[0011] As a preference, in step (4), the DFRTC value is the shortest distance from the upper right corner of the mold platform to the mold.

[0012] As a preferred embodiment, in step (2), the remaining space method is used for filling. Whenever the mold is placed on a remaining rectangle, several empty spaces will appear on the right and above the mold. The area is artificially divided into several new remaining spaces, and the remaining spaces are grouped into a remaining space linked list. The outermost remaining rectangle of the remaining space linked list is the current remaining rectangle. When a new remaining rectangle enters the remaining space linked list, it will be placed at the top of the remaining space linked list. At the same time, whenever a new remaining space enters, the top value will be deleted.

[0013] As a preferred embodiment, the initial value of the remaining space linked list includes a space for an initial mold platform, and when all the remaining spaces are deleted, a new mold platform space is automatically added.

[0014] As a preferred embodiment, each time a new mold is placed into the remaining space, new remaining space will be generated. In order to simplify the remaining space linked list, some unavailable spaces need to be deleted and a new remaining space linked list needs to be regenerated. The deletion rules include: when the width or length of the remaining space is smaller than the minimum size of the mold, consider deleting the remaining space from the remaining space linked list; calculate the area of ​​each remaining space, and when the area is smaller than the minimum area of ​​the mold, delete the remaining space from the remaining space linked list; if the remaining space is completely surrounded by other remaining spaces, the remaining space needs to be deleted from the remaining space linked list.

[0015] As a preferred embodiment, the fitness function uses the area utilization rate of the mold platform as an evaluation index, which is expressed as follows:

[0016]

[0017] Among them, P is the fitness function value, S 模具 is the area of ​​all molds, S 模台 is the total area of ​​all mold platforms.

[0018] As a preferred method, the basis of the genetic algorithm is chromosomes. The mold sorting method needs to be numbered, and each mold is fully arranged from 1 to m. The mold is used as a chromosome, and then the chromosome population is calculated to achieve combined optimization of multiple molds and multiple mold platforms.

[0019] The present invention has the following advantages:

[0020] 1. It provides an intelligent layout method for the rational production of concrete composite slabs and improves the utilization rate of molds.

[0021] 2. The production project order system is adopted, based on the B / S (browser / server) model, which greatly improves the efficiency of process nodes such as contract fulfillment, order scheduling, and production. From customer orders to customized production and precise delivery, it ensures the transparency of the refined production process.

[0022] 3. By adopting the production project analysis system, a mathematical model combining the factory production situation and actual projects was established, which simplified the complex production problems into a concrete model, laid the foundation for the subsequent introduction of algorithms, and provided great convenience for the subsequent rational arrangement of production and decision-making.

[0023] 4. Adopt the production sequencing calculation system based on genetic algorithm, use intelligent algorithm to arrange production reasonably, improve the production efficiency of the factory, reduce the workload of personnel, avoid some human errors, and realize the transparent management of people, machines, materials, methods and environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a hybrid algorithm framework diagram.

[0025] Figure 2 It is a schematic diagram of the mathematical model.

[0026] Figure 3 It is the layout diagram of the step-down algorithm.

[0027] Figure 4 This is the principle diagram of the maximum upper right corner distance heuristic rule.

[0028] Figure 5a-5e This is a schematic diagram of the remaining space linked list.

[0029] Figure 6a-6b is a schematic diagram for removing some thin remaining space.

[0030] Figure 7 It is a schematic diagram for deleting a small area of ​​remaining space.

[0031] Figure 8 It is a schematic diagram for deleting the remaining space that is wrapped.

[0032] Fig. 9 It is a schematic diagram of genetic algorithm encoding method.

[0033] Fig.10 It is a schematic diagram of the genetic algorithm crossover operator. DETAILED DESCRIPTION

[0034] The present invention will be further described in detail below in conjunction with specific implementation methods.

[0035] An intelligent layout method for concrete composite slab molds based on a hybrid algorithm is proposed. Based on the hybrid algorithm, the BLF step-down algorithm is used, combined with the proposed upper right corner distance maximum heuristic rule, to establish a set of rules for the layout of each mold. On this basis, a genetic algorithm is used to traverse the order of arrangement of different molds in sequence, and the fitness function (mold platform utilization rate) is used as the objective function to obtain the arrangement method of the mold on each mold platform.

[0036] Figure 1 As shown in FIG. 1 , the hybrid algorithm framework includes a die table and a die mathematical model generation part, a heuristic algorithm part based on a step-down algorithm and a maximum upper right corner distance heuristic rule, and a genetic algorithm part. The following is a detailed introduction.

[0037] 1. The part of generating the mathematical model of mold platform and mold

[0038] Based on the existing production system, all component information of the production batch is obtained, and by adding a 30cm working distance to each side of the component mold, it is expanded into the component footprint module required by the algorithm; then the size and number of the mold platform in the production system are converted into placed rectangular blocks, and a rectangular coordinate system is established based on the lower left corner of the mold platform. The lower left corner of the mold platform is the coordinate origin, and the position of the component footprint module on the mold platform is converted into a coordinate value. For the convenience of description, in the genetic algorithm part and the heuristic algorithm part, components and molds refer to the modeled component footprint module.

[0039] Figure 2 In the formula, p is the pth component; r is the placement direction of the component, r = 0 means the component is placed horizontally, r = 1 means the component is placed vertically; x p ——x coordinate value of the lower left corner of the component; y p ——The y coordinate value of the lower left corner of the component; L——represents the length of the mold platform; W——represents the width of the mold platform.

[0040] 2. Heuristic algorithm based on the step-down algorithm and the maximum upper right corner distance heuristic rule

[0041] The heuristic algorithm is mainly based on the bottom-left-first algorithm (BLF) and the maximum upper right corner distance heuristic rule, while considering the orientation of the concrete composite slab, and a new concrete composite slab placement strategy is proposed. Specifically, it includes the BLF algorithm, the maximum upper right corner distance heuristic rule, the remaining space filling method and the remaining space deletion rule, which will be explained one by one below.

[0042] 2.1 BLF Algorithm

[0043] The BLF algorithm is mainly an improved algorithm based on the BL (Bottom-Left) algorithm. The BLF algorithm uses the "bottom-left" principle to avoid overlapping and exceeding the orientation of components during layout. The edge of the mold platform is used as the boundary. The concrete composite slab mold is first moved downward to the lower end until it does not interfere with other components, and then the mold is moved to the leftmost end until it can no longer move; and while moving downward and left, the downward movement method is preferred, which improves the defect of utilization rate caused by the local vacant area that is easy to appear in the application of the BL algorithm. The specific layout method is as follows:

[0044] For each mold, b1, b2, b3, b4...bn, they are arranged one by one as follows.

[0045] (1) First, place b1 at the lower left corner of the mold platform;

[0046] (2) Next, place the next bi mold at the highest point in the upper right corner of the mold platform, move it downward until it cannot be moved, and then move it to the left; however, when the component moves to the left, if it encounters a space that can move downward, the mold will be moved downward immediately until it cannot be moved, and then continue to move to the left; until the mold bi cannot be moved.

[0047] (3) Repeat step (2) until all molds are placed.

[0048] The specific steps are as follows Figure 3 shown.

[0049] 2.2 Maximum distance heuristic rule for the upper right corner

[0050] The core of the maximum upper right corner distance heuristic rule is based on the BLF algorithm. In order to optimize the algorithm problem, a new heuristic rule is developed, that is, to solve the shortest distance from the upper right corner of the mold platform to the mold, which is DFRTC (Distance to Front-Top-Right Corner), that is, the distance from the upper right corner of the mold to the upper right corner of the mold platform after the mold is placed. The optimal mold layout method is not only the shortest distance that is the largest among all kinds of layout methods, but also the orientation needs to be considered for the same position. The one with the largest distance among all layout methods is the optimal solution, and the mold layout is also the most compact. For details, see Figure 4 , the mathematical expression is as follows:

[0051] DRFTRC 2 =(Ll p -x p ) 2 +(Ww p -y p ) 2

[0052] Among them, DRFTRC——indicates the distance from the upper right corner of the mold base to the upper right corner of the component after it is placed; x p ——x coordinate value of the lower left corner of the component; y p ——y coordinate value of the lower left corner of the component; l p ——The x-direction length of the pth component after it is placed; w p ——The width of the pth component in the y direction after it is placed.

[0053] Figure 4 In the figure, the DFRTC at point C is the farthest away, which is the most compact arrangement.

[0054] 2.3 Filling the remaining space

[0055] The remaining space filling method (EMS) is based on the principle of the BLF algorithm. Whenever a mold is placed on a certain remaining rectangle, several spaces will appear on the right and above the mold. The area is artificially divided into several new remaining spaces, and the remaining spaces are grouped into a remaining space list. The remaining rectangle on the outermost layer of the remaining space list is the current remaining rectangle. When a new remaining rectangle enters the remaining space list, it will be placed at the top of the remaining space list. At the same time, whenever a new remaining space enters, the top value must be deleted. The initial value of the remaining space list includes the space of an initial mold platform. When all the remaining spaces are deleted, a new mold platform space is automatically added, denoted as S. new The mathematical expression of the remaining space is represented by its minimum and maximum coordinates ([x1, y2], [X1, Y1]). The specific operations are as follows: Figure 5a-5e shown.

[0056] Figure 5a-5e As the components are put in, the original mold space S new is divided into several parts, each space part is denoted by S in , and the mathematical expression of the space is expressed in terms of the coordinates of the diagonal points of the space (the lower left corner and the upper right corner). [x i ,y n ]——indicates the coordinate value of the corner point, where i=1,2,3…,n=1,2,3…; [x0,y0]——indicates the coordinate value of the lower left corner of the mold platform when no components are placed; [L,W]——indicates the coordinate value of the upper right corner of the mold platform when no components are placed, L, W are the length and width of the mold platform respectively; [x i ,y i ]——x i Indicates the upper right corner horizontal coordinate of the newly generated coordinate component i after the i-th component is placed, y i It represents the upper right corner ordinate of the newly generated coordinate component i after the i-th component is placed, where x i=x0+l i ,y i =y0+w i ,i=1,2,3…。

[0057] Therefore, each space is expressed as a 2*2 matrix, containing the coordinates of the lower left corner and the upper right corner. Each time a new component is placed, the component is placed in the lower left corner of each space based on the BL algorithm, and the maximum value placed in each space is calculated using the DFRTC rule. The maximum value space is taken as the placement space, and after placing the component in the space, the space needs to be split, with the lower right corner of the component position after the component is placed as the base point, and the space is divided upward and rightward, and the space in the remaining space list is deleted and replaced with several newly generated spaces, recorded as S in . S in ——Indicates the nth space added after the i-th component is placed, where n=1, 2, 3,; S new ——Indicates the mold space where no components are placed. Then continue to put new components in. When the remaining space is insufficient, a new mold space is added. S new , and then place components in the new space until all components have been placed.

[0058] 2.4 Remaining space deletion

[0059] Every time a new mold is placed into the remaining space, new remaining space will be generated. In order to simplify the remaining space list, some unavailable spaces need to be deleted and a new remaining space list needs to be regenerated. The deletion rules include:

[0060] (1) Delete some thin remaining spaces. That is, when the width or length of the remaining space is less than the minimum size of the mold, consider deleting this remaining space from the remaining space linked list, such as Figure 6a and 6b .

[0061] Figure 6a and 6b Before placing a component each time, it is necessary to check whether the length and width of each space in the remaining space list are less than the smallest length or width of all components. If so, delete the space from the remaining space list.

[0062] Its mathematical expression is as follows:

[0063]

[0064] Among them, l k ——represents the length of the remaining component k; w k ——Indicates the width of the remaining component k; (x i -x n )——indicates the width of the space in the remaining space; (yi -y n )——Indicates the length of the space in the remaining space.

[0065] (2) Calculate the area of ​​each remaining space. When the area is smaller than the minimum area of ​​the mold, delete the remaining space from the remaining space list. Figure 7 Before placing a component each time, it is necessary to check whether the area of ​​each space in the remaining space list is smaller than the area of ​​the remaining components. If so, it needs to be deleted.

[0066] Its mathematical expression is as follows:

[0067]

[0068] Among them, l k ——represents the length of the remaining component k; w k ——Indicates the width of the remaining component k; (x i -x n )——indicates the width of the space in the remaining space; (y i -y n )——Indicates the length of the space in the remaining space.

[0069] (3) If the remaining space is completely surrounded by other remaining spaces, the remaining space needs to be deleted from the remaining space list. Mathematically, the minimum coordinate of the lower left corner of the remaining space in the remaining space list ([x k ,y k ]), where the x and y coordinates cannot be less than the x and y values ​​of the lower left corner of other spaces at the same time. The mathematical expression is as follows:

[0070] x k <x m P k <y m

[0071] Among them, x k ——The x value of the lower left corner coordinate of the remaining space k; y k ——represents the y value of the lower left corner coordinate of the remaining space k; x m ——The x value of the lower left corner coordinate of the remaining space m; y m ——Indicates the y value of the lower left corner coordinate of the remaining space m.

[0072] Figure 8 The remaining space S 22 The x coordinate of the lower left corner m and m Both are greater than the remaining space S 12 The x coordinate of the lower left corner k and x k, that is, the coordinate x k <x m And y k <y m .

[0073] 3. Genetic algorithm part

[0074] Different molds have different sizes, and the sizes of most molds are not very different. Therefore, when arranging various molds, the impact of the order of arranging the molds on the final result should be considered. Therefore, a genetic algorithm is used to optimize the mold arrangement order.

[0075] 3.1 Parameter setting of genetic algorithm

[0076] The parameter settings of the genetic algorithm include the population number M, the number of generations T, the crossover probability Pc, the mutation probability Pm, etc. The size of the population number M and the number of generations T affects the degree of optimization of the final solution. Ideally, the larger the M and the larger the T, the greater the probability of obtaining the global optimal solution. Of course, the genetic algorithm is likely to fall into the local optimal solution halfway and cannot jump out. The crossover probability Pc affects the inheritance of the good genes of the parents by the next generation of populations, and the mutation probability Pm affects the diversity of solutions. When the genetic algorithm falls into the local optimal solution, it relies on the crossover operation to jump out of the local optimum. These parameters have recommended value ranges in various documents. The present invention tentatively sets the population number M=50, the number of generations T=100, the crossover probability Pc=0.85; the mutation probability Pm=0.15.

[0077] 3.2 Encoding

[0078] The basis of genetic algorithm is chromosome. The present invention considers the combination optimization problem of multiple molds and multiple mold stations. Therefore, it is necessary to number the mold sorting method. Each mold is fully arranged from 1 to m and used as a chromosome. Then, the chromosome group is calculated. For details, see Fig. 9 .

[0079] 3.3 Fitness Function

[0080] For each individual in the population, an improved residual space filling algorithm is used to obtain the utilization rate of the individual. The fitness function mainly uses the area utilization rate of the mold platform as an evaluation indicator. Its specific mathematical expression is as follows:

[0081]

[0082] Among them, P is the fitness function value, S 模具 is the area of ​​all molds, S 模台 is the total area of ​​all mold platforms.

[0083] 3.4 Crossover Operator

[0084] The crossover of chromosomes adopts a single-point crossover strategy, using random functions to form the chromosomes into an initial population, using the global solution of dispersion, continuous iteration, using crossover mutation and other operations to form new populations, and constantly seeking the optimal solution, such as Fig.10 .

[0085] 3.5 Mutation Operator

[0086] Mutation, then the mutation strategy is exchange mutation, randomly determine two mutation positions on the individual chromosome code, and exchange the genes at these two positions in the individual chromosome code.

[0087] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. A method for intelligently arranging molds for concrete composite slabs based on a hybrid algorithm, characterized in that: The hybrid algorithm framework includes a part for generating mathematical models of mold bases and molds, a part for heuristic algorithms based on the step-down algorithm and the maximum heuristic rule of the upper right corner distance, and a genetic algorithm. The mathematical model is established by manually inputting the size and number of mold bases and molds, and the mathematical model is input into the heuristic algorithm and the genetic algorithm to calculate the mold arrangement method. The genetic algorithm is used to evolve the order of placement of different molds, and then the arranged molds are placed one by one by the heuristic algorithm to obtain the optimal placement method. Then the fitness function value is obtained through the placement method, and the mold placement order is optimized through the fitness function value. Then, the next placement arrangement calculation is entered until the optimal solution is obtained, and the optimal solution is output to guide the arrangement of the mold on the mold base. The method for establishing the mathematical model is as follows: on the basis of the existing production system, all component information of the production batch to be produced is obtained, and the component footprint module required by the algorithm is expanded by adding the working distance to each side of the component mold; then the size and number of the mold base in the production system are converted into a placed rectangular block, and a rectangular coordinate system is established based on the lower left corner of the mold base, the lower left corner of the mold base is the coordinate origin, and the position of the component footprint module on the mold base is converted into a coordinate value; The method of arranging the mold by heuristic algorithm is: (1) Select the mold i to be placed; (2) Fill the rectangular blocks according to the remaining space method and select possible placement positions; (3) Place mold i into the proposed position according to the step-down algorithm; (4) Calculate the DFRTC value based on the maximum upper right corner distance heuristic rule and by flipping the direction of the mold; repeat steps (2)-(4) to calculate the DFRTC values ​​of all possible placement positions and placement methods; (5) Select the maximum DFRTC value as the optimal solution; (6) Update the remaining space linked list and repeat steps (2)-(5) to complete the placement of the next mold i+1 until all molds are placed.

2. The method for intelligently arranging molds for composite concrete slabs based on a hybrid algorithm according to claim 1, characterized in that: In step (3), the step-down algorithm is a layout method based on the principle of "bottom and left". When arranging, components are prevented from overlapping and exceeding the orientation. The edge of the mold platform is used as the boundary. The concrete composite slab mold is first moved downward to the lower end until it does not interfere with other components, and then the mold is moved to the leftmost end until it cannot move any further. In addition, while moving downward and left, the downward movement method is preferred.

3. The method for intelligently arranging molds for composite concrete slabs based on a hybrid algorithm according to claim 1, characterized in that: In step (4), the DFRTC value is the shortest distance from the upper right corner of the mold platform to the mold.

4. The method for intelligently arranging molds for composite concrete slabs based on a hybrid algorithm according to claim 1, characterized in that: In step (2), the remaining space method is used for filling. Whenever the mold is placed on a remaining rectangle, several available spaces will appear on the right and above the mold. The available spaces are artificially divided into several new remaining spaces, and the remaining spaces are grouped into a remaining space linked list. The outermost remaining rectangle of the remaining space linked list is the current remaining rectangle. When a new remaining rectangle enters the remaining space linked list, it will be placed at the top of the remaining space linked list. At the same time, whenever a new remaining space enters, the value of the top layer will be deleted.

5. The method for intelligently arranging molds for composite concrete slabs based on a hybrid algorithm according to claim 4, characterized in that: The initial value of the remaining space linked list includes a space for an initial template. When all the remaining space is deleted, a new template space is automatically added.

6. The method for intelligently arranging molds for composite concrete slabs based on a hybrid algorithm according to claim 4, characterized in that: Every time a new mold is placed in the remaining space, new remaining space will be generated. In order to simplify the remaining space linked list, some unavailable spaces need to be deleted and a new remaining space linked list needs to be regenerated. The deletion rules include: when the width or length of the remaining space is less than the minimum size of the mold, consider deleting this remaining space from the remaining space linked list; calculate the area of ​​each remaining space, and when the area is less than the minimum area of ​​the mold, delete this remaining space from the remaining space linked list; if the remaining space is completely surrounded by other remaining spaces, the remaining space needs to be deleted from the remaining space linked list.

7. The method for intelligently arranging molds for composite concrete slabs based on a hybrid algorithm according to claim 1, characterized in that: The fitness function uses the area utilization of the die as an evaluation index and is expressed as follows: Among them, P is the fitness function value, S 模具 is the area of ​​all molds, S 模台 is the total area of ​​all mold platforms.

8. The method for intelligently arranging molds for composite concrete slabs based on a hybrid algorithm according to claim 1, characterized in that: The basis of genetic algorithm is chromosome. The mold sorting method needs to be numbered. Each mold is fully arranged from 1 to m. The mold is used as a chromosome, and then the chromosome population is calculated to achieve combined optimization of multiple molds and multiple mold platforms.

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