Optimization method for safety rope anchor point layout in high-altitude anti-falling protection system

Abstract

The invention discloses an optimization method for safety rope anchor point layout in a high-altitude anti-falling protection system, and relates to the technical field of building construction research. The method comprises the following steps that a multi-objective optimization model is established, decision variables are determined, optimization objectives of the decision variables are established, and the optimization objectives comprise supported process number maximization, safety index maximization and falling swing risk minimization; carrying out simulation on the multi-objective optimization model; carrying out simulation calculation on the multi-objective optimization model by adopting a non-dominated sorting genetic algorithm, and determining an optimal safety rope anchor point layout scheme meeting an optimization objective; and adopting the optimal safety rope anchor point layout scheme to carry out safety rope anchor point layout of each process in the construction project. The invention provides a calculation method for optimizing the anchor point position of a safety rope of a high-altitude operation anti-falling protection system. The control of the safety risk of an operator and the improvement of the construction production efficiency are realized through an informatization method.

Description

Technical Field

[0001] The invention belongs to the technical field of building construction research, and in particular relates to an optimization method for the layout of safety rope anchor points in a high-altitude fall protection system. Background Art

[0002] As one of the most dangerous industries, the construction industry has a high risk of casualties among its employees. Among them, one of the main causes of accidents in construction projects is falling from heights. In order to reduce the accident rate of falling from heights, it is stipulated that workers working at heights must use or wear fall protection safety equipment when working. However, since workers need to repeatedly reposition and install the anchor end of the fall protection equipment during the operation, relevant personnel need to invest a lot of extra time and energy in the use of the fall protection equipment and the protection implementation process. In addition, the current determination of the anchor point of the fall protection equipment mainly relies on the subjective experience of the workers, and the spatial plan of the anchor point lacks a systematic method. It is impossible to comprehensively consider the location of all construction processes to determine the optimal anchor position, which leads to low labor productivity of the workers.

[0003] Therefore, in order to improve the safety and work efficiency of workers working at heights, it is necessary to use information technology to comprehensively plan and optimize the anchoring position of fall protection equipment. Formulating a systematic anchoring position planning system for workers working at heights is an important way to effectively prevent high-altitude fall accidents and improve the labor efficiency of workers. Therefore, it is of great practical significance to optimize the anchoring point position of fall protection equipment for workers working at heights based on building information technology.

[0004] The present invention proposes a method for optimizing the layout of safety rope anchor points in a high-altitude fall protection system. Aiming at the spatial planning problem of wearable fall protection equipment for high-altitude workers, the present invention conducts spatial research and analysis on the anchoring position of the equipment. Through information technology, the safety risks of workers are controlled and the construction production efficiency is improved. This method is of great significance for the optimization of construction safety plans and the improvement of high-altitude working efficiency. Summary of the invention

[0005] The purpose of the present invention is to provide a method for optimizing the layout of safety rope anchor points in a high-altitude fall protection system, so as to solve the problems raised in the above background technology that currently operators mainly rely on their own experience to anchor the equipment, but a single anchoring cannot support multiple processes, thereby reducing the working efficiency.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] The first aspect of the present invention provides a method for optimizing the layout of safety rope anchor points in a high-altitude fall protection system, comprising the following steps:

[0008] S1. Establish a multi-objective optimization model; determine decision variables and establish optimization objectives for the decision variables. The optimization objectives include maximizing the number of supported processes, maximizing safety indicators, and minimizing the risk of falling and swinging;

[0009] S2. Simulate the multi-objective optimization model; use a non-dominated sorting genetic algorithm to simulate the multi-objective optimization model and determine the optimal safety rope anchor point layout solution that meets the optimization objectives;

[0010] S3. Use the optimal safety rope anchor point layout plan to layout the safety rope anchor points for each process in the construction project.

[0011] Preferably, the decision variables in S1 include the coordinates of the anchor point j (x j ,y j ) and the total number of positioning times J of anchor points in the area.

[0012] Preferably, the number of processes supported in S1 is maximized, as follows:

[0013]

[0014] Among them, ST represents the total number of processes supported by the fall protection system; ST i represents the state index, indicating whether process i can be supported by any planned anchor point; x i The horizontal axis of process i; y i Represents the ordinate of process i; x j represents the horizontal coordinate of the anchor point j; y j represents the ordinate of the anchor point j; l0 represents the length of the safety rope of the fall protection system.

[0015] Preferably, the safety index in S1 is maximized, specifically as follows:

[0016]

[0017] Among them, SI represents the safety index of the process in the planned area; SI i It represents the safety performance index of the work group executing process i; J represents the total number of positioning times of the anchor point; I represents the total number of processes.

[0018] Furthermore, the safety index is calculated as follows:

[0019] By dividing the space where the construction project is located into two areas, a safe area far from the edge of the working platform and a dangerous area close to the edge of the working platform; checking whether the safety rope protection range of anchor point j covers the position of task i, the safety performance of process i is determined, and the fall risk index increases with the approach to the edge of the working platform; the details are as follows:

[0020] The work platform area is divided into nine areas, with area codes S1-S9; each process area is represented by the process coordinates (x i ,y i ) to determine; the calculation rule of the safety index SI is as follows, which is used to calculate the average safety level of all processes;

[0021] w i =k,if A i ∈S k

[0022] w Ai =p,if A Ai ∈S p

[0023] d imin =min{y i |,|x i |}

[0024]

[0025] Among them, A i represents the corresponding anchor point that can support process i; w Ai represents the partition to which process i belongs; α and β represent the fall risk index determined according to the working posture of the operator. The fall risk index β of the squatting posture is set to be 1.6 times the fall risk index α of the standing posture; l0 represents the length of the safety rope; P i represents the classification of the working posture of process i, where 1 represents the process being performed in a standing posture and 2 represents the process being performed in a squatting posture; d imin Represents the shortest distance from process i to the edge of the nearest platform.

[0026] Preferably, the fall swing risk in S1 is minimized by establishing a fall swing index to represent the average fall swing angle of an accidental fall when executing each process in the planning area, thereby converting potential injuries into a swing fall risk index; specifically, as follows:

[0027]

[0028] Among them, x Ai The horizontal coordinate x of the anchor point corresponding to process i; y Aj represents the ordinate y of the anchor point corresponding to process i; i The horizontal axis of process i; y j Represents the ordinate of process i; x max Indicates the maximum coordinate of the platform edge on the x-axis; y max Indicates the maximum coordinate of the platform edge on the y-axis; w iIndicates the corresponding area code to which task i belongs.

[0029] Preferably, in S2, a non-dominated sorting genetic algorithm is used to perform simulation calculation on the multi-objective optimization model, as follows:

[0030] The initial population of safety rope anchor point layout schemes is randomly generated; each scheme includes the spatial position of the safety rope anchor point, including the number of anchor point positioning times J, the coordinates of the anchor point position (x j ,y j ) and the anchor distribution of the scheme;

[0031] For each generated solution, calculate the corresponding objective function value, that is, the total number of processes ST, safety index SI and fall swing risk index SF supported by the solution;

[0032] According to the three objective function values, the safety rope anchor point layout scheme with high fitness is selected; all the safety rope anchor point layout schemes generated in the population are ranked to check whether the maximum number of iterations has been reached; if the maximum number of iterations has been reached, the calculation process will be terminated and the final result, i.e., the optimal safety rope anchor point layout scheme, will be output; if the maximum number of iterations has not been reached, the execution will continue;

[0033] The best solution of the previous generation will be selected as the base population for the next iteration;

[0034] Crossover and mutation operations are performed to generate new safety rope anchor point layout solutions for the next generation.

[0035] Preferably, the optimal safety rope anchor point layout solution includes: the total number of positioning times J of the safety rope anchor point of the anti-fall protection system; the optimal position of the anchor point of the anti-fall protection system (x j ,y j ); The index values ​​of each optimal safety rope anchor point layout scheme include the total number of supported processes ST, the safety index SI and the fall swing risk index SF.

[0036] The second aspect of the present invention proposes an optimization system for the layout of safety rope anchor points in a high-altitude fall protection system, including a multi-objective optimization model and a simulation-based optimization module;

[0037] The multi-objective optimization model includes an optimization function for the total number of supported processes, an optimization function for the safety index, and an optimization function for the fall and swing risk index; and is used to achieve the optimization goals of maximizing the number of supported processes, maximizing the safety index, and minimizing the fall and swing risk;

[0038] The simulation-based optimization module is constructed using a non-dominated sorting genetic algorithm to explore the layout scheme of the safety rope anchor points in the overall working area and find the optimal layout scheme of the safety rope anchor points that meets the optimization objectives.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] (1) The present invention provides a calculation method for optimizing the anchor point position of a fall protection system for aerial work, including establishing a multi-objective optimization model for spatial analysis and constructing an optimization module based on simulation. First, a multi-objective model based on spatial analysis is established to determine the relationship between the anchor point position of the fall protection system of a high-rise building project and safety and work efficiency, and to establish the optimization function and optimization target of the decision variables. Based on the multi-objective model, a simulation-based optimization module is further developed to explore the safety planning scheme of the overall working area and find the optimal solution for the anchor position of the fall protection system that meets multiple goals such as construction safety, labor productivity and cost. In the simulation-based optimization, multiple optimization indicators are incorporated into the developed model. The control of safety risks of operators and the improvement of construction production efficiency are achieved through information technology methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a schematic diagram of the structure of the high altitude fall protection system in Embodiment 1 of the present invention;

[0042] Figure 2 It is a schematic diagram of the spatial partitioning of the working platform in Example 1 of the present invention;

[0043] Figure 3 is a schematic diagram of a change rule of a fall risk index in Embodiment 1 of the present invention;

[0044] Figure 4 This is a schematic diagram of the partitions of a rectangular work platform in Example 1 of the present invention;

[0045] Figure 5 It is a schematic plan view of the working floor in Embodiment 2 of the present invention;

[0046] Figure 6 This is a spatial layout diagram of the optimal anchor point solution selected in Example 2 of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Embodiment 1:

[0049] The optimization method of safety rope anchor point layout in high altitude fall protection system is mainly based on the optimization system of safety rope anchor point layout. The optimization system of safety rope anchor point layout includes two parts: multi-objective optimization model based on spatial analysis and optimization module based on simulation.

[0050] The optimization method of the safety rope anchor point layout in the high altitude fall protection system includes the following steps:

[0051] Step 1: Construct a multi-objective optimization model;

[0052] This step aims to establish a multi-objective optimization model based on spatial analysis to optimize the spatial position of the safety rope anchorage of the fall protection system, minimize the labor cost consumed during the repeated installation of the anchor points, and maximize the safety performance of the operators and improve the construction labor efficiency.

[0053] (1) Determine the decision variables of the mathematical model;

[0054] First, determine the decision variables related to the safety performance and work efficiency of the construction project. In the present invention, the high-altitude fall protection system includes an anchoring device, a safety belt (belt and shoulder strap) and a safety rope connecting the safety belt and the anchoring device, such as Figure 1 As shown. The relevant decision variables include: ① The coordinates of the fall protection anchor point j (x j ,y j ), ②The total number of anchor points in the area (J).

[0055] (2) Establish a multi-objective optimization model;

[0056] In order to achieve a balance between different optimization objectives, a multi-objective optimization model is established. The optimization objectives constructed include: ① maximizing the number of supported processes (ST); ② maximizing the safety index (SI); and ③ minimizing the risk of falling and swinging (SF).

[0057] Goal ①: Maximize the number of tasks that can be supported;

[0058] The first objective function aims to maximize the number of processes that the fall protection system can support. ST represents the number of tasks that the fall protection system can support.

[0059]

[0060] Among them, ST represents the total number of tasks supported by the fall protection system; ST i represents the state index, indicating whether task i can be supported by any planned anchor point; x i represents the horizontal axis of task i; y i represents the ordinate of task i; x j represents the horizontal coordinate of anchor point j; yj represents the ordinate of the anchor point j; l0 represents the length of the safety rope of the fall protection system.

[0061] Goal ②: Maximize safety indicators;

[0062] The second optimization goal is to maximize the safety of operators. The safety of operators using fall protection equipment is maximized by analyzing the spatial relationship between the anchor point location, process location, and work platform.

[0063]

[0064] Among them, SI represents the safety performance index of the process in the planned area; SI i represents the safety performance index of the work group performing activity i; J represents the total number of anchor positions; I represents the total number of activities.

[0065] In order to maximize the safety performance index (SI), a rule-based algorithm was established. The algorithm can consider the dangerous and safe areas within the working platform, analyze the impact of the safety rope anchor position on safety performance, assign a reasonable anchor position to each process in the planned area, and consider the risk level of danger based on spatial relationships, process types and ergonomics. The specific steps of the algorithm are as follows:

[0066] First, establish the partitioning rules of the platform;

[0067] like Figure 2-Figure 3 As shown in the figure, the space near the edge of the aerial platform is divided into two areas: the safe area and the dangerous area. For anchor point j and task i, the algorithm can analyze their relative spatial positions and check whether the safety rope protection range of anchor point j covers the position of task i, thereby determining the safety performance of process i. During process execution, the position of the anchor point can be optimized to keep the operators away from the dangerous area of ​​the platform as much as possible while ensuring construction efficiency. The fall risk indexes α and β are calculated based on the risk of possible fall of operators performing processes at the edge of the platform. The working postures of workers during welding can be divided into standing posture and squatting posture. Because the stability of the squatting posture is about 1.6 times that of the standing posture, the value of the squatting posture fall risk index β is set to be 1.6 times that of the standing posture fall risk index α.

[0068] Secondly, calculate the safety index;

[0069] like Figure 4 As shown in the figure, the platform area is divided into nine areas according to the distance between the process location and the dangerous edge of the platform. The area to which each process belongs is represented by the process coordinates (x i ,y i) is used to determine the safety index (SI). The calculation rules of the safety index (SI) are shown in formulas (4)-(7), thereby calculating the average safety level of operators performing all processes.

[0070] w i =k, if A i ∈S k (4)

[0071] w Ai =p, if A Ai ∈S p (5)

[0072] d imin =min{y i |,|x i |} (6)

[0073]

[0074] Among them, A i represents the corresponding anchor point that can support process i; w Ai represents the partition to which process i belongs; S5 represents the safe area of ​​the working platform; α and β represent the fall risk index determined according to the working posture of the operator; l0 represents the length of the safety rope; P i represents the classification of the working posture of process i, where 1 represents the process being performed in a standing posture and 2 represents the process being performed in a squatting posture; d imin represents the shortest distance from process i to the edge of the nearest platform; S k , S p express Figure 4 The partitions shown in .

[0075] Objective ③: Minimize the risk of falling and swinging;

[0076] Workers on the edge of the platform may fall accidentally, and during the fall they will swing like a pendulum, causing more serious injuries. Therefore, in order to reduce the risk of swing injuries caused by workers falling, a fall swing index was established to represent the average fall swing angle when an accidental fall occurs during each process in the planning area, converting potential injuries into a swing fall risk index. The specific calculation process is as follows:

[0077]

[0078]

[0079] Among them, x Ai The horizontal coordinate x of the anchor point corresponding to process i; y Aj represents the ordinate y of the anchor point corresponding to process i; i The horizontal axis of process i; yj Represents the ordinate of process i; x max Indicates the maximum coordinate of the platform edge on the x-axis; y max Indicates the maximum coordinate of the platform edge on the y-axis; w i express Figure 3 The corresponding area code to which task i belongs.

[0080] Step 2: Simulation-based optimization module;

[0081] Based on the established multi-objective mathematical optimization model, the spatial optimization model is simulated by constructing a module of non-dominated sorting genetic algorithm (NSGA-II). The optimization process can execute the established objective function and constraints and output the Pareto optimal solution. This module can search and determine the optimal anchor position (x j ,y j ), and generate the Pareto optimal solution. The optimization calculation is simulated by MATLAB R2020b, including processing relevant input data, initialization of simulation, execution and optimization of simulation, and output of data.

[0082] Enter the data as follows:

[0083] This module includes the following input data: project data, configuration data and process execution data. Among them, project data includes relevant information of all processes in the planned area, including the coordinates and type of the process; configuration data includes the type of selected fall protection safety equipment, the size of the safety rope and the maximum strength that the fall protection safety equipment can withstand; process execution data includes the working posture of the operator to complete each process.

[0084] The optimized calculation is as follows:

[0085] Matlab is used to establish a simulation optimization module based on genetic algorithm. The steps of optimization calculation are as follows:

[0086] Step 1: Read and process project data to complete initialization;

[0087] Step 2: Randomly generate an initial population of safety planning solutions. In this step, each solution contains the spatial position of the anchor point of the safety rope of the fall protection equipment, including the number of anchor point positioning times (J), the coordinates of the anchor point position (x j ,y j ) and the anchor point distribution of the scheme.

[0088] Step 3: For each generated solution, calculate the corresponding objective function value, that is, the total number of processes (ST), safety index (SI) and fall swing risk index (SF) supported by the solution;

[0089] Step 4: According to the three objective function values, select the safety planning scheme with high fitness. Rank all the safety planning schemes generated in the population and check whether the maximum number of iterations has been reached. If the maximum number of iterations has been reached, the module will end the calculation process and output the final result; if the maximum number of iterations has not been reached, the module will continue to execute steps 5 and 6.

[0090] Step 5: The best solution of the previous generation will be selected as the base population for the next iteration.

[0091] Step 6: Perform crossover and mutation operations to generate new security planning solutions for the next generation.

[0092] The model output is as follows:

[0093] This step can determine the optimal safety planning scheme, including: ① the total number of positioning times of the safety rope anchor point of the fall protection system (J); ② the optimal position of the anchor point of the fall protection system (x j ,y j ) ; ③ The index values ​​of each optimal safety planning scheme, including the total number of supported processes (ST), safety index (SI) and fall and swing risk (SF) index values.

[0094] Step 3: Implement the developed model directly in the multi-storey building project and carry out the layout construction of the safety rope anchor points according to the optimal safety planning solution.

[0095] Embodiment 2:

[0096] The safety rope anchor point layout optimization system is used to optimize the anchor point position of the safety rope in the fall protection equipment during the construction process of one floor of a high-rise building. The floor plan is as follows: Figure 5 shown.

[0097] The process of this floor includes 184 process activities, involving masonry, concrete, steel bars, and electricity. In this case, the following assumptions are considered: (1) The anchor installation height of the fall protection system in each process is the same; (2) The installation and use of the fall protection equipment will not be affected by the structural layout of the building; (3) The order of the processes will not affect the installation and location optimization of the fall protection system.

[0098] Table 1 summarizes the input data of 184 activities on a sample floor (23rd floor). The process-related input data include the position coordinates (x i ,y i ), process type and the working posture when completing each process. Among them, the process execution posture is 1 for standing posture and 2 for squatting posture.

[0099] Table 1 Process-related simulation input information

[0100]

[0101] The established multi-objective GA non-dominated sorting genetic algorithm (NSGA-II) is applied to perform the optimization process and output the results. The Pareto optimal solution and the corresponding decision variable results are generated through NSGA-II.

[0102] In the simulation, by inputting different total numbers of anchor points (N), different optimal solution results can be output. Each optimal solution represents a Pareto optimal solution and can achieve the best balance between ST, SI and SF objectives, thereby effectively improving labor productivity and reducing safety risks for operators.

[0103] Figure 6 represents the optimal safety planning scheme selected in the case. The optimal anchor position coordinates and spatial layout generated by this scheme are shown in Figure 6 At this time, the corresponding index values ​​of ST, SI and SF are 144, 1.306 and 0.077 respectively.

[0104] The above description is only used to help understand the method of the present invention and its core essence, but the protection scope of the present invention is not limited thereto. For those skilled in the art in the art, equivalent replacement or change according to the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for optimizing the layout of safety rope anchor points in a high-altitude fall protection system, characterized in that: The following steps are involved: S1. Establish a multi-objective optimization model; Determine the decision variables and establish the optimization objectives of the decision variables. The optimization objectives include maximizing the number of supported processes, maximizing the safety index, and minimizing the risk of falling and swinging; S2. Simulate the multi-objective optimization model; use a non-dominated sorting genetic algorithm to simulate the multi-objective optimization model and determine the optimal safety rope anchor point layout solution that meets the optimization objectives; S3. Use the optimal safety rope anchor point layout plan to layout the safety rope anchor points for each process in the construction project.

2. The method for optimizing the layout of safety rope anchor points in a high-altitude fall protection system according to claim 1, characterized in that: The decision variables in S1 include the coordinates of the anchor point j (x j ,y j ) and the total number of positioning times J of anchor points in the area.

3. The method for optimizing the layout of safety rope anchor points in a high-altitude fall protection system according to claim 2, characterized in that: The number of processes supported in S1 is maximized, as follows: Among them, ST represents the total number of processes supported by the fall protection system; ST i represents the state index, indicating whether process i can be supported by any planned anchor point; x i The horizontal axis of process i; y i Represents the ordinate of process i; x j represents the horizontal coordinate of the anchor point j; y j represents the ordinate of the anchor point j; l0 represents the length of the safety rope of the fall protection system.

4. The method for optimizing the layout of safety rope anchor points in a high-altitude fall protection system according to claim 2, characterized in that: The safety index in S1 is maximized as follows: Among them, SI represents the safety index of the process in the planned area; SI i It represents the safety performance index of the work group executing process i; J represents the total number of positioning times of the anchor point; I represents the total number of processes.

5. The method for optimizing the layout of safety rope anchor points in a high-altitude fall protection system according to claim 4, characterized in that: The calculation of the safety index in S1 is as follows: By dividing the space where the construction project is located into two areas, a safe area far from the edge of the working platform and a dangerous area close to the edge of the working platform; checking whether the safety rope protection range of anchor point j covers the position of task i, the safety performance of process i is determined, and the fall risk index increases with the approach to the edge of the working platform; the details are as follows: The work platform area is divided into nine areas, with area codes S1-S9; each process area is represented by the process coordinates (x i ,y i ) to determine; the calculation rule of the safety index SI is as follows, which is used to calculate the average safety level of all processes; w i =k,if A i ∈S k w Ai =p,if A Ai ∈S p d imin =min{y i |,|x i |} Among them, A i represents the corresponding anchor point that can support process i; w Ai represents the partition to which process i belongs; α and β represent the fall risk index determined according to the working posture of the operator. The fall risk index β of the squatting posture is set to be 1.6 times the fall risk index α of the standing posture; l0 represents the length of the safety rope; P i represents the classification of the working posture of process i, where 1 represents the process being performed in a standing posture, and 2 represents the process being performed in a squatting posture; d imin Represents the shortest distance from process i to the edge of the nearest platform.

6. The method for optimizing the layout of safety rope anchor points in a high altitude fall protection system according to claim 2, characterized in that: The fall swing risk in S1 is minimized by establishing a fall swing index to represent the average fall swing angle of an accidental fall when executing each process in the planning area, and converting potential injuries into a swing fall risk index; specifically, as follows: Among them, x Ai The horizontal coordinate x of the anchor point corresponding to process i; y Aj represents the ordinate y of the anchor point corresponding to process i; i The horizontal axis of process i; y j Represents the ordinate of process i; x max Indicates the maximum coordinate of the platform edge on the x-axis; y max Indicates the maximum coordinate of the platform edge on the y-axis; w i Indicates the corresponding area code to which task i belongs.

7. The method for optimizing the layout of safety rope anchor points in a high-altitude fall protection system according to claim 1, characterized in that: In S2, a non-dominated sorting genetic algorithm is used to simulate and calculate the multi-objective optimization model, as follows: The initial population of safety rope anchor point layout schemes is randomly generated; each scheme includes the spatial position of the safety rope anchor point, including the number of anchor point positioning times J, the coordinates of the anchor point position (x j ,y j ) and the anchor distribution of the scheme; For each generated solution, calculate the corresponding objective function value, that is, the total number of processes ST, safety index SI and fall swing risk index SF supported by the solution; According to the three objective function values, a safety rope anchor point layout scheme with high fitness is selected; all safety rope anchor point layout schemes generated in the population are ranked to check whether the maximum number of iterations has been reached; If the maximum number of iterations is reached, the calculation process will end and the final result, i.e. the optimal safety rope anchor point layout solution, will be output; if the maximum number of iterations is not reached, the execution will continue; The best solution of the previous generation will be selected as the base population for the next iteration; Crossover and mutation operations are performed to generate new safety rope anchor point layout solutions for the next generation.

8. The method for optimizing the layout of safety rope anchor points in a high altitude fall protection system according to claim 7, characterized in that: The optimal safety rope anchor point layout scheme includes: the total number of positioning times J of the safety rope anchor point of the anti-fall protection system; the optimal position of the anchor point of the anti-fall protection system (x j ,y j ); The index values ​​of each optimal safety rope anchor point layout scheme include the total number of supported processes ST, the safety index SI and the fall swing risk index SF.

9. An optimization system for the layout of safety rope anchor points in a high-altitude fall protection system used in the optimization method described in any one of claims 1 to 8, characterized in that: Includes multi-objective optimization models and simulation-based optimization modules; The multi-objective optimization model includes an optimization function for the total number of supported processes, an optimization function for a safety index, and an optimization function for a fall and swing risk index; It is used to achieve the optimization goals of maximizing the number of supported processes, maximizing safety indicators, and minimizing the risk of falling and swinging; The simulation-based optimization module is constructed using a non-dominated sorting genetic algorithm to explore the layout scheme of the safety rope anchor points in the overall working area and find the optimal layout scheme of the safety rope anchor points that meets the optimization objectives.

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