Optimization method for the layout of safety rope anchor points in high-altitude fall protection systems

Abstract

The present invention discloses an optimization method for the layout of safety rope anchor points in a high-altitude fall protection system, and relates to the technical field of building construction research; the method comprises the following steps: establishing a multi-objective optimization model: determining decision variables, establishing optimization targets of decision variables, the optimization targets including maximizing the number of supported processes, maximizing safety indicators, and minimizing the risk of falling swings; simulating the multi-objective optimization model: using a non-dominated sorting genetic algorithm to simulate and calculate the multi-objective optimization model, and determining the optimal safety rope anchor point layout scheme that meets the optimization targets; using the optimal safety rope anchor point layout scheme to layout the safety rope anchor points of various processes in the construction project. The present invention provides a calculation method for optimizing the position of safety rope anchor points in a high-altitude work fall protection system, and realizes the control of safety risks of operators and the improvement of construction production efficiency through an information 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 anchor points j The coordinates of x j ，y j ) and the total number of anchor point positioning in the area J .

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

[0013]

[0014]

[0015] in, ST Indicates the total number of processes supported by the fall protection system; ST i Indicates the state index, representing the process i Whether it can be supported by any planned anchor point; x i Indicates the process i The horizontal axis of y i Indicates the process i The vertical coordinate of x j Indicates anchor point j The horizontal axis of y j Indicates anchor point j The vertical coordinate of l 0 Indicates the length of the safety rope of the fall protection system.

[0016] Preferably, the safety index in S1 is maximized, specifically as follows:

[0017] (3)

[0018] in, SIIndicates the safety index of the process in the planned area; SI i Indicates execution process i The work group safety performance index; J Indicates the total number of positioning times of the anchor point; I Indicates the total number of processes.

[0019] Furthermore, the safety index is calculated as follows:

[0020] By dividing the space where the construction project is located into two areas, a safe area away from the edge of the working platform and a dangerous area close to the edge of the working platform; check the anchor points j Does the safety rope protection range cover the mission? i Position, determine the process i The safety performance of the work platform is improved, and the fall risk index increases as the work platform edge approaches; as follows:

[0021] The work platform area is divided into nine areas, with area codes S 1 -S 9 ; Each process area is determined by the process coordinates （x i ，y i ) to determine; safety indicators SI The calculation rule is as follows, which is used to calculate the average safety level of all processes;

[0022] w i =k, if Q i ∈S k

[0023] w Ai =p, if Q Ai ∈S p

[0024]

[0025]

[0026] in, A i Indicates that it can support the process i The corresponding anchor point of w i Indicates the process i The zone code; w Ai Indicates the process i The partition code to which the corresponding anchor point belongs;α、β It indicates 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; l 0 Indicates the length of the safety rope; P i Indicates the process i The classification of working postures, where 1 represents the process being performed in a standing posture, and 2 represents the process being performed in a squatting posture; d imin Indicates the process i The shortest distance to the nearest platform edge.

[0027] 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:

[0028]

[0029]

[0030] in, x Ai Indicates the process i The horizontal coordinate of the corresponding anchor point x ; y Aj Indicates the process i The ordinate of the corresponding anchor point y ; x i Indicates the process i The horizontal axis of y j Indicates the process i The vertical coordinate of x max Indicates that the platform edge is x The maximum coordinate on the axis; y max Indicates that the platform edge is y The maximum coordinate on the axis; w i Representation Task i The corresponding area code.

[0031] Preferably, in S2, a non-dominated sorting genetic algorithm is used to perform simulation calculation on the multi-objective optimization model, as follows:

[0032] Randomly generate an initial population of safety rope anchor point layout plans; each plan includes the spatial location of the safety rope anchor point, including the number of anchor point positioning times J , the coordinates of the anchor point position ( xj ，y j ) and the anchor distribution of the scheme;

[0033] For each generated solution, calculate the corresponding objective function value, that is, the total number of processes supported by the solution ST , Safety indicators SI and fall swing risk indicators SF ;

[0034] 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;

[0035] The best solution of the previous generation will be selected as the base population for the next iteration;

[0036] Crossover and mutation operations are performed to generate new safety rope anchor point layout solutions for the next generation.

[0037] Preferably, the optimal safety rope anchor point layout solution includes: the total number of positioning times of the safety rope anchor point of the fall protection system J ; Optimal location of anchor points for fall protection systems （x j ，y j ）； The index value of each optimal safety rope anchor point layout solution, including the total number of supported processes ST , Safety indicators SI and fall swing risk indicators SF .

[0038] 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;

[0039] 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;

[0040] 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.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] (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 an optimization function and optimization target for the decision variables. Based on the multi-objective model, a simulation-based optimization module is further developed to explore the safety planning scheme for 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

[0043] Figure 1 This is a schematic diagram of the structure of the high altitude fall protection system in Embodiment 1 of the present invention;

[0044] Figure 2 It is a schematic diagram of the spatial partitioning of the working platform in Example 1 of the present invention;

[0045] Figure 3 is a schematic diagram of a change rule of a fall risk index in Embodiment 1 of the present invention;

[0046] Figure 4 This is a schematic diagram of the partitions of a rectangular work platform in Example 1 of the present invention;

[0047] Figure 5 It is a schematic plan view of the working floor in Embodiment 2 of the present invention;

[0048] Figure 6 This is a spatial layout diagram of the optimal anchor point solution selected in Example 2 of the present invention. DETAILED DESCRIPTION

[0049] 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.

[0050] Embodiment 1:

[0051] 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.

[0052] The optimization method of the safety rope anchor point layout in the high altitude fall protection system includes the following steps:

[0053] Step 1: Construct a multi-objective optimization model;

[0054] 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.

[0055] (1) Determine the decision variables of the mathematical model;

[0056] 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 fall protection anchor point j The coordinates of x j ，y j ), ②The total number of anchor points in the area ( J ).

[0057] (2) Establish a multi-objective optimization model;

[0058] 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 );②Maximization of safety index ( SI ); ③ Minimize the risk of falling and swinging ( SF ).

[0059] Goal ①: Maximize the number of tasks that can be supported;

[0060] The first objective function aims to maximize the number of processes that the fall protection system can support. ST Indicates the number of tasks that the fall protection system can support.

[0061] (1)

[0062] (2)

[0063] in, ST Indicates the total number of tasks supported by the fall protection system; ST i Indicates the state index, representing the task iWhether it can be supported by any planned anchor point; x i Representation Task i The horizontal axis of y i Representation Task i The vertical coordinate of x j Indicates anchor point j The horizontal axis of y j Indicates anchor point j The vertical coordinate of l 0 Indicates the length of the safety rope of the fall protection system.

[0064] Goal ②: Maximize safety indicators;

[0065] 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.

[0066] (3)

[0067] in, SI Indicates the safety performance index of the process in the planned area; SI i Indicates execution activity i The work group safety performance index; J represents the total number of anchor positions; I Indicates the total number of activities.

[0068] To achieve the safety performance index ( SI ) is maximized, and a rule-based algorithm is established. The algorithm can consider the dangerous area and safe area 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:

[0069] First, establish the partitioning rules of the platform;

[0070] like Figure 2-Figure 3 As shown in Figure 1, the space near the edge of the high-altitude platform is divided into two areas: a safe area and a dangerous area. j and tasks i , the algorithm analyzes its relative spatial position and checks the anchor points j Does the safety rope protection range cover the mission? i The location of the process is determined iDuring the process, the position of the anchor point can be optimized to keep the workers away from the danger zone of the platform while ensuring the construction efficiency. The fall risk index is determined based on the risk of workers who may fall while performing the process at the edge of the platform. α and β The working postures of workers during welding can be divided into standing posture and squatting posture. Since the stability of squatting posture is about 1.6 times that of standing posture, the value of squatting posture fall risk index β is set to be 1.6 times that of standing posture fall risk index α.

[0071] Secondly, calculate the safety index;

[0072] 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 shown in the figure. （x i ，y i ) to determine. Safety indicators ( SI ) is calculated as shown in formulas (4)-(7), thereby calculating the average safety level of operators performing all processes.

[0073] w i =k, if Q i ∈S k (4)

[0074] w Ai =p, if Q Ai ∈S p (5)

[0075] (6)

[0076] (7)

[0077] in, A i Indicates that it can support the process i The corresponding anchor point of w i Indicates the process i The zone code; w Ai Indicates the process i The partition code to which the corresponding anchor point belongs; S 5 Indicates the safe area of ​​the working platform; α、β Indicates the fall risk index determined based on the worker’s working posture;l 0 Indicates the length of the safety rope; P i Indicates the process i The classification of working postures, where 1 represents the process being performed in a standing posture, and 2 represents the process being performed in a squatting posture; d imin Indicates the process i The shortest distance to the nearest platform edge; S k 、S p express Figure 4 The partitions shown in .

[0078] Objective ③: Minimize the risk of falling and swinging;

[0079] 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:

[0080] (8)

[0081] (9)

[0082] in, x Ai Indicates the process i The horizontal coordinate of the corresponding anchor point x ; y Aj Indicates the process i The ordinate of the corresponding anchor point y ; x i Indicates the process i The horizontal axis of y j Indicates the process i The vertical coordinate of x max Indicates that the platform edge is x The maximum coordinate on the axis; y max Indicates that the platform edge is y The maximum coordinate on the axis; w i express Figure 3 Medium Task i The corresponding area code.

[0083] Step 2: Simulation-based optimization module;

[0084] Based on the established multi-objective mathematical optimization model, a non-dominated sorting genetic algorithm ( NSGA-II ) module to simulate and calculate the spatial optimization model. The optimization process can execute the established objective function and constraints and output the Pareto optimal solution. This module can be used for each process ( i ) Search and determine the best anchoring position for the safety rope of the fall arrest system ( x j , y j ), and generate Pareto Optimal solution. The optimization calculation is simulated using MATLAB R2020b, including processing relevant input data, initialization of the simulation, execution and optimization of the simulation, and output of the data.

[0085] Enter the data as follows:

[0086] 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.

[0087] The optimized calculation is as follows:

[0088] Matlab is used to establish a simulation optimization module based on genetic algorithm. The steps of optimization calculation are as follows:

[0089] Step 1: Read and process project data to complete initialization;

[0090] Step 2: Randomly generate an initial population of safety planning solutions. In this step, each solution contains the spatial location 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.

[0091] Step 3: For each generated solution, calculate the corresponding objective function value, that is, the total number of processes supported by the solution ( ST )、Safety Index( SI ) and the fall swing risk index ( SF );

[0092] 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.

[0093] Step 5: The best solution of the previous generation will be selected as the base population for the next iteration.

[0094] Step 6: Perform crossover and mutation operations to generate new security planning solutions for the next generation.

[0095] The model output is as follows:

[0096] 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 Optimal position of anchor point of fall protection system （x j ，y j ）； ③ The index value of each optimal safety planning scheme, including the total number of supported processes ( ST )、Safety Index( SI ) and fall swing risk ( SF ) indicator value.

[0097] 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.

[0098] Embodiment 2:

[0099] 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.

[0100] 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.

[0101] Table 1 summarizes the input data of 184 activities on a sample floor (23rd floor). The process-related input data include the location coordinates of each process ( 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.

[0102] Table 1 Process-related simulation input information

[0103]

[0104] 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.

[0105] In the simulation, different total number of anchor points ( N ), different optimal solution results can be output, each of which represents a Pareto optimal solution and can achieve the best balance between ST, SI and SF objectives, thereby effectively improving labor productivity and reducing the safety risks of operators.

[0106] 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.

[0107] 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; The number of supported processes is maximized, as follows: in, ST Indicates the total number of processes supported by the fall protection system; ST i Indicates the state index, representing the process i Whether it can be supported by any planned anchor point; x i Indicates the process i The horizontal axis of y i Indicates the process i The vertical coordinate of x j Indicates anchor point j The horizontal axis of y j Indicates anchor point j The vertical coordinate of l 0 indicates the safety rope length of the fall protection system; The safety index is calculated as follows: By dividing the space where the construction project is located into two areas, a safe area away from the edge of the working platform and a dangerous area close to the edge of the working platform; check the anchor points j Does the safety rope protection range cover the mission? i Position, determine the process i The safety performance of the work platform is improved, and the fall risk index increases as the work platform edge approaches; 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; safety indicators SI The calculation rule is as follows, which is used to calculate the average safety level of all processes; w i =k, if Q i ∈S k w Ai =p, if Q Ai ∈S p in, A i Indicates that it can support the process i The corresponding anchor point of w i Indicates the process i The zone code; w Ai Indicates the process i The corresponding anchor point A i The zone code; α、β It indicates 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; l 0 indicates the length of the safety rope; P i Indicates the process i The classification of working postures, where 1 represents the process being performed in a standing posture, and 2 represents the process being performed in a squatting posture; d imin Indicates the process i The shortest distance to the nearest platform edge; Minimize the risk of falling and swinging by establishing a falling and swinging index to represent the average falling and swinging angle of accidental falls during each process in the planning area, and convert potential injuries into a swinging falling risk index; specifically: in, x Ai Indicates the process i The horizontal coordinate of the corresponding anchor point x ; y Aj Indicates the process i The ordinate of the corresponding anchor point y ; x i Indicates the process i The horizontal axis of y j Indicates the process i The vertical coordinate of x max Indicates that the platform edge is x The maximum coordinate on the axis; y max Indicates that the platform edge is y The maximum coordinate on the axis; w i Indicates the task i The corresponding area code; 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 anchor points j The coordinates of x j ，y j ) and the total number of anchor point positioning in the area J .

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 safety index in S1 is maximized as follows: in, SI Indicates the safety index of the process in the planned area; SI i Indicates execution process i The work group safety performance index; J Indicates the total number of positioning times of the anchor point; I Indicates the total number of processes.

4. 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: Randomly generate an initial population of safety rope anchor point layout plans; each plan includes the spatial location 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 supported by the solution ST , safety indicators SI and fall swing risk indicators SF ; 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.

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 optimal safety rope anchor point layout scheme includes: the total number of positioning times of the safety rope anchor point of the fall protection system J ; Optimal location of anchor points for fall protection systems （x j ，y j ）； The index value of each optimal safety rope anchor point layout solution, including the total number of supported processes ST , safety indicators SI and fall swing risk indicators SF .

6. 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 5, 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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