A method and system for optimizing indoor evacuation layout for guide arrangement

Abstract

The application belongs to the field of computer simulation and optimization algorithm, and proposes an indoor evacuation layout optimization method and system for guide arrangement. First, an evacuation model containing space boundary, exit location and width, and pedestrian distribution is constructed; under the condition that the exit layout is unchanged, the position, size and orientation of the guide are taken as optimization variables, and space and safety constraints are set; based on the slime mold algorithm, the guide layout scheme is generated, and the evacuation time, crowd density and exit utilization rate are comprehensively evaluated through simulation. The method optimizes the guide arrangement, improves the crowd flow structure, reduces the congestion degree, and improves the overall evacuation efficiency, which can provide a basis for indoor design and emergency evacuation optimization.

Description

Technical Field

[0001] This invention relates to the fields of computer simulation and optimization algorithms, and in particular to a layout optimization method and system that improves the efficiency of indoor crowd evacuation by combining parametric modeling of guide objects with optimization algorithms under fixed exit layout conditions. Background Technology

[0002] With the continuous advancement of urbanization, the number of large public buildings such as commercial complexes, exhibition halls, transportation hubs, and sports stadiums is constantly increasing. These buildings often experience high-density crowd gatherings during peak hours. In the event of emergencies such as fires or earthquakes, people need to evacuate quickly within a limited time. If the evacuation is not properly organized, it can easily lead to secondary disasters such as overcrowding and stampedes. Therefore, improving the efficiency and safety of evacuation within buildings has become an important research issue in the field of building safety engineering.

[0003] Existing research mainly focuses on optimizing the layout of exits, such as improving evacuation efficiency by adjusting parameters such as the number, location and width of exits. However, in actual building spaces, in addition to the exit structure, the interior space structure and the layout of local facilities can also significantly affect the flow of people. For example, structures such as columns, partitions and flow guidance facilities may hinder the flow of people, but when properly arranged, they may also guide the flow of people, disperse peak density and improve the balance of exit utilization.

[0004] Recent studies have shown that the reasonable placement of obstacles or guidance structures in the upstream area of ​​the exit can improve evacuation efficiency under certain conditions. However, the effect of such guidance is significantly scene-dependent, and its effectiveness is closely related to factors such as spatial structure, crowd density, and the location of the guidance. Relying solely on experience or manual methods to determine the layout of guidance often fails to achieve stable results.

[0005] Meanwhile, with the development of computer simulation technology, crowd evacuation simulation methods have been widely used in building safety assessments. However, existing research mainly focuses on simulating and analyzing evacuation processes under given layout conditions, lacking computational methods for systematically optimizing indoor guidance facility layout schemes. Therefore, it is necessary to propose a method that combines crowd evacuation simulation with intelligent optimization algorithms to generate and optimize indoor guidance facility layout schemes, thereby improving building evacuation efficiency. Summary of the Invention

[0006] The purpose of this invention is to improve existing indoor evacuation layout optimization methods that only focus on the exit structure and ignore the impact of the indoor layout structure on crowd evacuation. This invention proposes an indoor evacuation layout optimization method and system that, under the condition of a fixed exit layout, optimizes the layout by using parametric modeling of guided objects and slime mold algorithm to improve overall evacuation efficiency and reduce the risk of local congestion.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] An indoor evacuation layout optimization method oriented towards the placement of guiding objects includes the following steps:

[0009] 1) Construct an indoor evacuation scenario model: Abstract the indoor evacuation space into a two-dimensional planar area, import fixed exit layout parameters, including exit position and exit width, and set the initial pedestrian distribution state to establish a unified evacuation simulation environment.

[0010] 2) Establish a parameterized model of the guide: Under the condition of fixed exit layout, the guide is used as a layout optimization variable. The spatial position, geometric dimensions and orientation of the guide are parameterized and described. Geometric constraints and safety distance constraints between the guide and the exit, building boundary and other guides are established to limit the feasible solution space of the guide layout.

[0011] 3) Generate the initial population for guide object layout: The slime mold algorithm is used to randomly initialize the guide object layout parameters to generate an initial population containing multiple guide object placement schemes, where each individual corresponds to a complete guide object layout scheme;

[0012] 4) Perform crowd evacuation simulation: Introduce the guide layout scheme into the evacuation scenario model, and simulate the movement behavior of pedestrians in an emergency based on the speed obstacle model. Dynamically update the pedestrian movement speed and position status according to the interaction relationship between pedestrians and surrounding pedestrians, guides and building boundaries.

[0013] 5) Calculate evacuation performance indicators: Calculate the evacuation performance indicators corresponding to each guide layout scheme based on the evacuation simulation results. The evacuation performance indicators include total evacuation time, maximum local population density and exit utilization rate, and construct a multi-objective fitness function based on the evacuation performance indicators.

[0014] 6) Update guide layout parameters: Utilize the shrink-expansion search mechanism of the slime mold algorithm to iteratively update the guide layout parameters based on the fitness values ​​of each individual, and adjust the search direction through a fitness-based weight adjustment strategy to obtain new candidate solutions for guide layout.

[0015] 7) Terminate optimization and output results: Repeat the evacuation simulation, layout parameter update and individual selection process until the preset termination conditions are met. The termination conditions include reaching the maximum number of iterations or the fitness change is less than a set threshold. Finally, the optimal guide placement scheme and its corresponding evacuation performance index are output.

[0016] Preferably, the indoor evacuation scenario model constructed in step 1) is a two-dimensional planar model, which is defined by the indoor space boundary, and the guide object placement area is located inside the boundary. Throughout the optimization process, the position and width of the exit remain unchanged to eliminate the interference of exit layout changes on the guide object placement optimization results, thereby allowing the optimization process to focus on the impact of guide object layout on evacuation efficiency.

[0017] Preferably, the guide objects are represented using parametric modeling, with each guide object including at least center position coordinates, geometric dimension parameters, and orientation angle parameters. By uniformly encoding these parameters, the guide object placement problem is transformed into an optimization search problem in a continuous parameter space, thereby facilitating the automatic search and updating of the guide object layout using intelligent optimization algorithms.

[0018] Preferably, the guide layout scheme must simultaneously meet the following constraints to ensure the physical feasibility and engineering rationality of the layout result: the center of the guide is located within a preset feasible area; a preset minimum safe distance is maintained between the guide and the exit; a preset safe distance is maintained between the guide and the boundary of the indoor space; and multiple guides do not have geometric overlap or unreasonable contact.

[0019] Preferably, during the optimization iteration process, when the generated guide layout scheme violates the above constraints, its position or size parameters are adjusted through a boundary repair mechanism to make it satisfy the spatial constraints again; or the fitness value of the layout scheme is reduced through a penalty function, and the fitness value is recalculated after correction, thereby ensuring that the layout schemes participating in the optimization search are actually feasible.

[0020] Preferably, the fitness function uses total evacuation time as the core evaluation index, and combines it with maximum local crowd density and pedestrian conflict or collision costs for comprehensive evaluation. The comprehensive fitness function is constructed by normalizing each evaluation index and using a dynamic weighting method. A better fitness value is obtained when the evacuation time is shorter, the local congestion is lower, and the pedestrian conflict cost is smaller.

[0021] An indoor evacuation layout optimization system oriented towards the placement of guiding objects includes:

[0022] The data input module is used to acquire indoor building space structure data, exit location and exit width information, and initial pedestrian distribution data.

[0023] The scene modeling module is used to construct an indoor evacuation scene model based on the building space structure data, and to establish feasible passage areas and spatial boundaries in the scene model.

[0024] The guide modeling module is used to perform parametric modeling of the guide and generate a set of guide layout parameters, which include at least the spatial position, geometric dimensions and orientation angle of the guide;

[0025] The evacuation simulation module is used to introduce a guide layout scheme into the constructed indoor evacuation scenario model, and to simulate the evacuation behavior of pedestrians in an emergency based on a speed obstacle model, so as to obtain pedestrian movement trajectory and evacuation performance data.

[0026] The layout optimization module is used to iteratively update the layout parameters of the guide based on the slime mold algorithm, and to construct a fitness function based on the evacuation performance index to drive the layout optimization search process.

[0027] The constraint management module is used to detect whether the layout scheme of the guide meets the preset spatial constraints, and to process the layout scheme that does not meet the constraints through boundary repair or penalty function.

[0028] The results output module is used to output the optimized guide layout scheme and the corresponding evacuation performance indicators.

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0030] This invention uses the relevant parameters of the guide as an important design variable for evacuation layout optimization. While keeping the exit layout unchanged, it improves the overall flow of people by optimizing the position, size and orientation of the guide, reduces congestion and collision, and improves the smoothness of evacuation, thereby reducing local congestion and shortening the overall evacuation time.

[0031] This invention introduces a swarm intelligence optimization method based on slime mold algorithm, which utilizes its self-organization, positive and negative feedback and global search capabilities to efficiently search for the optimal placement scheme of guide objects in complex continuous space. Compared with traditional empirical placement or exhaustive evaluation methods, it significantly improves optimization efficiency and solution quality.

[0032] By constructing a target fitness function and introducing a dynamic weight adjustment mechanism, a balance can be achieved between evacuation efficiency and safety during the optimization process, avoiding local overcrowding or safety risks caused by single-target optimization.

[0033] This invention introduces a unified feasible domain constraint and layout repair mechanism during the optimization process, which effectively avoids layout schemes that are "theoretically optimal but not feasible in engineering" and improves the feasibility of optimization results in actual building environments.

[0034] The optimized layout of guideways obtained by this invention can provide decision-making reference for interior space design, emergency evacuation organization and safety facility deployment, effectively improving the efficiency of pedestrian traffic inside buildings while ensuring the safe evacuation of personnel. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating the overall process of optimizing indoor evacuation layout for the purpose of guiding objects, as described in this invention.

[0036] Figure 2 A schematic diagram of an indoor crowd evacuation scenario that includes the deployment of guide objects;

[0037] Figure 3 Define the geometric parameters of the guide;

[0038] Figure 4 A schematic diagram of the feasible region constraints;

[0039] Figure 5 A diagram showing the changes in evacuation performance indicators before and after optimization of the guiding structure;

[0040] Figure 6 This is a structural block diagram of the indoor evacuation layout optimization system of the present invention;

[0041] Figure 7 A comparison chart of evacuation time metrics under different guidance object deployment strategies; Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. The present invention provides a technical solution:

[0043] An indoor evacuation layout optimization method and system oriented towards the placement of guiding objects includes the following steps:

[0044] 1) Construct an indoor evacuation scenario model, abstract the indoor evacuation space into a two-dimensional planar area, import fixed exit layout parameters, including exit position and exit width, and set the initial pedestrian distribution state to establish a unified evacuation simulation environment.

[0045] 2) Establish a parameterized model of the guide objects. Under the condition of a fixed exit layout, the guide objects are used as layout optimization variables. The spatial position, geometric dimensions and orientation of the guide objects are parameterized. Geometric constraints and safety distance constraints between the guide objects and the exit, building boundaries and other guide objects are established to limit the feasible solution space of the guide object layout.

[0046] 3) Generate an initial population for guide object layout. Use the slime mold algorithm to randomly initialize the guide object layout parameters and generate an initial population containing multiple guide object placement schemes, where each individual corresponds to a complete guide object layout scheme.

[0047] 4) Perform crowd evacuation simulation, introduce the guide layout scheme into the evacuation scenario model, simulate the movement behavior of pedestrians in an emergency based on the speed obstacle model, and dynamically update the pedestrian movement speed and position status according to the interaction relationship between pedestrians and surrounding pedestrians, guides and building boundaries.

[0048] 5) Calculate evacuation performance indicators. Based on the evacuation simulation results, calculate the evacuation performance indicators corresponding to each guide layout scheme. The evacuation performance indicators include at least the total evacuation time, the maximum local population density, and the exit utilization rate. Construct a multi-objective fitness function based on the evacuation performance indicators.

[0049] 6) Update the guide layout parameters. Utilize the shrink-expansion search mechanism of the slime mold algorithm to iteratively update the guide layout parameters based on the fitness values ​​of each individual. Adjust the search direction through a fitness-based weight adjustment strategy to obtain new candidate solutions for guide layout.

[0050] 7) Terminate the optimization and output the results. Repeat the evacuation simulation, layout parameter update and individual selection process until the preset termination conditions are met. The termination conditions include reaching the maximum number of iterations or the fitness change is less than a set threshold. Finally, output the optimal guide placement scheme and its corresponding evacuation performance index.

[0051] Step 1) specifically includes the following steps:

[0052] 1.1 Scene Boundary Modeling: Abstracting the indoor evacuation space into a two-dimensional planar region. Its boundary is formed by walls or impassable areas, denoted as The area can be rectangular, polygonal, or a closed, passable area formed by assembling multiple sub-areas. 1.2 Fixed Exit Layout Import: Import the set of exits. Each exit Based on its position (interval or geometric segment on the boundary) and width Description: In this application, the exit position and width remain unchanged during the optimization process to eliminate interference caused by changes in the exit, so that the optimization only applies to the placement of the guide.

[0053] 1.3 Initial Pedestrian State Definition: Let the set of pedestrians be... For each pedestrian Define initial position Expected speed Simulation parameters include target exit selection rules (such as nearest exit / visible exit / strategy exit). Optionally, different crowd density fields, crowd size distributions, and reaction time distributions can be defined to construct different scenario inputs.

[0054] 1.4 Output Scene Tuples: Abstracting the scene into tuples:

[0055]

[0056] in These are the simulation control parameters (time step, maximum simulation duration, collision radius, etc.).

[0057] Step 2) specifically includes the following steps:

[0058] 2.1 Under a fixed exit layout, the guide elements are parametrically modeled as optimization design variables. Specifically, a single guide element is defined as follows:

[0059] Suppose K guiding objects are placed in an indoor space, then the guiding object parameter vector is defined as:

[0060]

[0061] in, Indicates the center position of the i-th guide. These represent the length and width of the guide, respectively. Indicates the orientation angle of the guide object.

[0062] 2.2 To ensure the physical feasibility of the guide object layout, the center of the guide object must be located within a feasible area. Within, that is:

[0063] 2.3 To avoid interference with exit operations, a minimum safe distance must be maintained between the guide object and the exit:

[0064] 2.4 To avoid obstructing pedestrian traffic by placing guide objects close to the walls, a minimum safe distance must be maintained between the guide objects and the building boundary:

[0065] 2.5 To prevent overlap between guides, different guides must meet the following requirements:

[0066] Step 3) specifically includes the following steps:

[0067] 3.1 The slime mold algorithm is used to initialize the guide layout and generate an initial population:

[0068] in, For population size, each individual This corresponds to a complete set of guide layout schemes.

[0069] 3.2 Define the spatial area occupied by the guide based on its geometric shape:

[0070] When the guide is a circular structure, its occupied area is represented as follows:

[0071] When the guide is a rectangular structure, its occupied area is represented as follows:

[0072] in Indicates the angle of rotation around the center point. A rectangular area.

[0073] Step 4) specifically includes the following steps:

[0074] 4.1 Introduce the layout scheme of the guide objects into the evacuation scenario and construct a simulation environment that includes guide objects, exits and boundary constraints.

[0075] 4.2 A speed obstacle-based pedestrian motion model (RVO) was used to simulate the evacuation process. The control speed is determined by the following optimization problem:

[0076]

[0077] in, Indicates the pedestrian's expected speed. This refers to a set of speed barriers consisting of other pedestrians and guide objects.

[0078] 4.3 Pedestrian positions are updated in discrete time steps:

[0079]

[0080] Step 5) specifically includes the following steps:

[0081] 5.1 Based on the evacuation simulation results, calculate the evacuation performance indicators corresponding to each guide object layout scheme, including:

[0082] Total evacuation time (efficiency indicator):

[0083]

[0084] Maximum local density (safety index):

[0085]

[0086] Export utilization rate (safety indicator):

[0087]

[0088] Thus, a multi-objective optimization problem is constructed:

[0089]

[0090] 5.2 To avoid target bias caused by fixed weights, each indicator is normalized and a dynamic weighting strategy is adopted:

[0091]

[0092]

[0093]

[0094] The overall objective function is:

[0095]

[0096] The weights are dynamically adjusted during the optimization phase, emphasizing safety goals in the early stages of the search and gradually strengthening efficiency goals in the later stages.

[0097] Step 6) specifically includes the following steps:

[0098] 6.1 The slime mold algorithm is used to update the guide layout parameters. The core update equation is:

[0099]

[0100] in, The weight matrix is ​​constructed based on fitness:

[0101]

[0102] in, These represent the best, worst, and median fitness of the current generation, respectively. To prevent extremely small positive numbers from being divisible by zero.

[0103] 6.2 Individual Evaluation Loop: The resulting guide layout is converged. The evacuation simulation is re-executed for the updated individuals before proceeding to the next step. If the current optimal solution is greater than the global optimal solution, it is updated, and the optimal index and corresponding guide layout parameters are saved. For each individual... Compared to older individuals With new individuals The fitness value (or Pareto dominance).

[0104] Greedy retention strategy: If the new individual is better, replace the old individual with the new individual in the next generation; otherwise, retain the old individual.

[0105]

[0106] Step 7) specifically includes the following steps:

[0107] 7.1 Iteration Termination Conditions (at least one of the following must be met) Termination conditions may include: the number of iterations reaches the upper limit. ;

[0108] continuous The change in the optimal fitness value is less than the threshold. :

[0109]

[0110] The total evacuation time has reached the preset target threshold:

[0111]

[0112] 7.2 Output the optimal guide scheme: Output the optimal individual It includes the location, size, orientation, and shape parameters of each guide object, and simultaneously outputs the corresponding evacuation indicators. This serves as a guide layout suggestion for the project.

[0113] Example 2: Another embodiment of the present invention provides an indoor evacuation layout optimization system oriented towards the placement of guiding objects, comprising:

[0114] The data input module is used to acquire indoor building space structure data, exit location and exit width information, and initial pedestrian distribution data.

[0115] The scene modeling module is used to construct an indoor evacuation scene model based on the building space structure data, and to establish feasible passage areas and spatial boundaries in the scene model.

[0116] The guide modeling module is used to perform parametric modeling of the guide and generate a set of guide layout parameters, which include at least the spatial position, geometric dimensions and orientation angle of the guide;

[0117] The evacuation simulation module is used to introduce a guide layout scheme into the constructed indoor evacuation scenario model, and to simulate the evacuation behavior of pedestrians in an emergency based on a speed obstacle model, so as to obtain pedestrian movement trajectory and evacuation performance data.

[0118] The layout optimization module is used to iteratively update the layout parameters of the guide based on the slime mold algorithm, and to construct a fitness function based on the evacuation performance index to drive the layout optimization search process.

[0119] The constraint management module is used to detect whether the layout scheme of the guide meets the preset spatial constraints, and to process the layout scheme that does not meet the constraints through boundary repair or penalty function.

[0120] The results output module is used to output the optimized guide layout scheme and the corresponding evacuation performance indicators.

[0121] Example 3: As shown in the figure, construct an indoor 2D scene (e.g. (Lobby / shopping mall area), set up a fixed exit collection Randomly generated Initial position and expected speed of each pedestrian.

[0122] First, a baseline evacuation simulation was performed under conditions without guides to obtain the baseline total evacuation time. With maximum density The method of this invention is then executed according to the illustrated process to iteratively optimize the guide object layout parameters and output the optimal guide object placement scheme. And obtain the optimized total evacuation time. With maximum density By comparison and , and This demonstrates that the present invention can improve local congestion and enhance overall evacuation efficiency while meeting engineering feasibility constraints.

[0123] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A method for optimizing indoor evacuation layout based on the placement of guiding elements, characterized in that, Includes the following steps: 1) Construct an indoor evacuation scenario model: Abstract the indoor evacuation space into a two-dimensional planar area, import fixed exit layout parameters, including exit position and exit width, and set the initial pedestrian distribution state to establish a unified evacuation simulation environment. 2) Establish a parameterized model of the guide: Under the condition of fixed exit layout, the guide is used as a layout optimization variable. The spatial position, geometric dimensions and orientation of the guide are parameterized and described. Geometric constraints and safety distance constraints between the guide and the exit, building boundary and other guides are established to limit the feasible solution space of the guide layout. 3) Generate the initial population for guide object layout: The slime mold algorithm is used to randomly initialize the guide object layout parameters to generate an initial population containing multiple guide object placement schemes, where each individual corresponds to a complete guide object layout scheme; 4) Perform crowd evacuation simulation: Introduce the guide layout scheme into the evacuation scenario model, and simulate the movement behavior of pedestrians in an emergency based on the speed obstacle model. The pedestrian movement speed and position status can be dynamically updated according to the interaction between pedestrians and surrounding pedestrians, guides and building boundaries. 5) Calculate evacuation performance indicators: Calculate the evacuation performance indicators corresponding to each guide layout scheme based on the evacuation simulation results. The evacuation performance indicators include total evacuation time, maximum local population density and exit utilization rate, and construct a multi-objective fitness function based on the evacuation performance indicators. 6) Update guide layout parameters: Utilize the shrink-expansion search mechanism of the slime mold algorithm to iteratively update the guide layout parameters based on the individual fitness value, and adjust the search direction through a fitness-based weight adjustment strategy to obtain new guide layout candidate solutions; 7) Terminate optimization and output results: Repeat the evacuation simulation, layout parameter update and individual selection process until the preset termination conditions are met. The termination conditions include reaching the maximum number of iterations or the fitness change is less than a set threshold. Finally, the optimal guide placement scheme and its corresponding evacuation performance index are output.

2. The indoor evacuation layout optimization method oriented towards guide object placement according to claim 1, characterized in that, The indoor evacuation scenario model constructed in step 1) is a two-dimensional planar model. The two-dimensional planar model is defined by the indoor space boundary, and the guide placement area is located inside the space boundary. Throughout the optimization process, the position and width of the exit remain unchanged.

3. The indoor evacuation layout optimization method oriented towards guide object placement according to claim 1, characterized in that, The guide objects are represented using a parametric modeling approach. The parameters of each guide object include at least the coordinates of the guide object's center position, geometric dimensions, and orientation angle. These parameters are randomly initialized within a preset range to generate an initial population of guide object layouts.

4. The indoor evacuation layout optimization method oriented towards guide object placement according to claim 1, characterized in that, The guide layout must simultaneously meet the following constraints: The center of the guide object is located within the pre-defined feasible area; Maintain a preset minimum safe distance between the guide and the exit; A predetermined safe distance should be maintained between the guide object and the boundary of the indoor space; There should be no geometric overlap or unreasonable contact between multiple guides.

5. The indoor evacuation layout optimization method oriented towards guide object placement according to claim 1, characterized in that, During the optimization iteration process, when a guide layout scheme violates the constraints, it is screened through a feasibility judgment strategy, or its fitness value is reduced by introducing a penalty function, so as to reduce the generation of infeasible solutions in subsequent iterations.

6. The indoor evacuation layout optimization method oriented towards guide object placement according to claim 1, characterized in that, The fitness function uses total evacuation time as the core evaluation index and combines it with the maximum local population density and pedestrian conflict cost for comprehensive evaluation. The comprehensive fitness function is constructed through multi-index normalization and dynamic weighting, and is used for the optimization search of guide layout schemes.

7. An indoor evacuation layout optimization system for implementing the method of claim 1, characterized in that, include: The data input module is used to acquire indoor building space structure data, exit location and exit width information, and initial pedestrian distribution data. The scene modeling module is used to construct an indoor evacuation scene model based on the building space structure data, and to establish feasible passage areas and spatial boundaries in the scene model. The guide modeling module is used to perform parametric modeling of the guide and generate a set of guide layout parameters, which include at least the spatial position, geometric dimensions and orientation angle of the guide; The evacuation simulation module is used to introduce a guide layout scheme into the constructed indoor evacuation scenario model and simulate pedestrian evacuation behavior in an emergency based on a speed obstacle model in order to obtain pedestrian movement trajectory and evacuation performance data. The layout optimization module is used to iteratively update the layout parameters of the guide based on the slime mold algorithm, and to construct a fitness function based on the evacuation performance index to drive the layout optimization search process. The constraint management module is used to detect whether the layout scheme of the guide meets the preset spatial constraints, and to process the layout scheme that does not meet the constraints through boundary repair or penalty function. The results output module is used to output the optimized guide layout scheme and the corresponding evacuation performance indicators.

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