Method and system for optimizing evacuation path of people in building based on shortest global evacuation time

Abstract

The invention discloses a method and a system for optimizing an evacuation path of people in a building based on shortest global evacuation time, and relates to the field of optimization of the evacuation path of people in the building. The problems that in the prior art, a path optimization method cannot truly and accurately reflect the influence of crowd crowd on the evacuation process, and the actual condition of crowd evacuation in the crowd state cannot be reasonably considered in the path optimization process are solved. The method comprises the following steps: generating a corresponding evacuation road network model according to an architectural plan of a to-be-analyzed case; determining an evacuation personnel distribution scheme; determining a shortest-path evacuation path scheme, calculating an evacuation simulation result of the scheme, and obtaining global evacuation time and the number of the finally evacuated group; determining an optimizable evacuation group set according to a bidirectional transfer strategy; setting an initial optimization scheme; and iteratively optimizing the evacuation paths of the groups in the first optimization adjustment area and the second optimization adjustment area. And outputting a final optimized evacuation path scheme and a corresponding evacuation process simulation calculation result.

Description

Technical Field

[0001] The present invention relates to the technical field of optimization of evacuation paths for people in buildings, and in particular to a method and system for optimizing evacuation paths for people in buildings based on the shortest global evacuation time. Background Art

[0002] With the development of economy and the acceleration of urbanization, the urban population is becoming more and more dense. At the same time, the problem of tight land resources in cities has gradually become prominent, which makes the development of multi-story buildings and large public places in cities an inevitable choice. These buildings have large spaces and diverse functions, and often gather a large number of people. Once an emergency such as an earthquake, fire, flood, terrorist attack, etc. occurs, it is very easy to cause heavy casualties. Therefore, the safety of people in various large complexes, high-rise buildings and other crowded places in the city has become the focus of attention of all sectors of society. When an emergency occurs in a building, if the people inside can evacuate quickly and safely, casualties can be effectively reduced or even avoided. This highlights the importance of efficient evacuation in ensuring the life safety of people in the building. In summary, there is a strong demand for practical applications to determine efficient emergency evacuation routes for people in buildings in a scientific and reasonable way.

[0003] Existing research generally solves the optimization problem of evacuation paths by applying intelligent algorithms such as genetic algorithms, ant colony algorithms, and particle swarm optimization. This type of optimization algorithm generally uses the inaccessibility of the crowded location as a constraint condition for the optimization process to avoid stampedes caused by extreme crowding. However, in most real evacuation processes, when the crowd is in a crowded state, people are often able to pass through the crowded location, but the movement speed of people passing through the crowded place will be significantly slowed down. It can be seen that the above-mentioned processing method cannot truly and accurately reflect the impact of crowd crowding on the evacuation process, so it is impossible to reasonably consider the actual situation of crowd evacuation under crowded conditions during the optimization process. Crowd crowding has a serious impact on the overall evacuation efficiency in the building. It is necessary to accurately and reasonably consider its impact in the process of optimizing the evacuation path of personnel.

[0004] This application uses the Chinese invention patent with application number CN202410420273.5, and its invention name is "Macroscopic simulation method and device for crowd evacuation considering the reduction of the traffic speed of people in crowded places". As an evacuation process simulation calculation tool in the iterative process of path optimization, a method for optimizing the evacuation path of people in a building is proposed, which can take into account the actual situation of crowd evacuation under crowded conditions. Summary of the invention

[0005] The present invention solves the problem that the path optimization method involved in the prior art cannot truly and accurately reflect the impact of crowd congestion on the evacuation process, and cannot reasonably consider the actual situation of crowd evacuation under a crowded state during the path optimization process, that is, the problem that crowd congestion has a serious impact on the overall evacuation efficiency in the building.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] Solution 1: A method for optimizing the evacuation path of people in a building based on the shortest global evacuation time, the method comprising:

[0008] Step 1: Generate the corresponding evacuation road network model G(V,E) from the building plan of the case to be analyzed;

[0009] Step 2: Determine the evacuation personnel distribution plan P based on the evacuation road network model G(V,E) obtained in step 1 num ;

[0010] Step 3: Based on the evacuation personnel distribution plan P determined in step 2 num , determine the shortest evacuation path plan P R_min , the shortest evacuation path solution P R_min Including determining the set of alternative evacuation paths S for each group ap And the weight value matrix D of the group alternative evacuation path ap ;

[0011] Step 4: Calculate the shortest evacuation path plan P based on step 3 R_min The evacuation simulation results of the scheme are used to obtain the global evacuation time t g0 The group number k0 that has completed evacuation;

[0012] Step 5: According to the two-way mobilization strategy, determine the evacuation group sets to be optimized Ord_FSR_SV_set and Ord_SSR_SV_set;

[0013] Step 6: Based on the evacuation group sets to be optimized Ord_FSR_SV_set and Ord_SSR_SV_set determined in step 5, set the initial optimization scheme P R_oe ;

[0014] Step 7: Based on the initial optimization solution P set in step 6 R_oe Iteratively optimizing the evacuation path of the group in the first optimization adjustment area, where the first optimization adjustment area is the evacuation area on one side where the last group to complete evacuation is located;

[0015] Step 8: Based on the initial optimization solution P set in step 6 R_oeIteratively optimizing the evacuation path of the group in the second optimization adjustment area; the second optimization adjustment area is the evacuation area on the other side that does not include the last group to complete the evacuation as the second optimization adjustment area;

[0016] Step 9: Output the final optimized evacuation path plan P R_oe And the corresponding evacuation process simulation results.

[0017] Further, a preferred implementation is provided, in step 3, determining the shortest evacuation path solution P R_min Calculated by Floyd algorithm.

[0018] Further, a preferred implementation is provided, in step 6, an initial optimization scheme P is set R_oe The method is to convert the shortest evacuation path plan P R_min As the initial optimization solution P in the optimization iteration process R_oe , that is, let P R_oe =P R_min , t g_oe =t g0 , and take m FSR =0.

[0019] Further, a preferred implementation is provided, in step seven, based on the initial optimization solution P set in step six R_oe The method of iteratively optimizing the evacuation path of the group in the first optimization adjustment area is:

[0020] S7.1. Each iteration adjusts the evacuation path of only one group, which is numbered Ord_FSR_SV_set[m FSR ];

[0021] S7.2. Calculate P R_temp The evacuation simulation results of the scheme are used to obtain the global evacuation time t g_temp ;

[0022] S7.3, according to the global evacuation time t g_temp Determine whether the iteration is terminated

[0023] Further, a preferred implementation is provided, in step eight, based on the initial optimization solution P set in step six R_oe The method for iteratively optimizing the evacuation path of the group in the second optimization adjustment area is:

[0024] S8.1. Each iteration adjusts the evacuation path of only one group, which is numbered Ord_SSR_SV_set[m SSR ].

[0025] S8.2. Calculate P R_tempThe evacuation simulation results of the scheme are used to obtain the global evacuation time t g_temp ;

[0026] S8.3, based on the global evacuation time t g_temp Determine whether the iteration is terminated.

[0027] Further, a preferred implementation is provided, in step seven, based on the initial optimization solution P set in step six R_oe The iterative optimization of the evacuation path of the group in the first optimization adjustment area also includes a step of determining whether the iteration is terminated.

[0028] Further, a preferred embodiment is provided, in S3, according to the global evacuation time t g_temp The method to determine whether the iteration is terminated is:

[0029] If g_temp <t g_oe , then update P R_oe With t g_oe , that is, let P R_oe =P R_temp , t g_oe =t g_temp , and enter the next iteration at the same time;

[0030] If g_temp >t g_oe , then stop the iteration and exit step seven.

[0031] Solution 2: This solution proposes a building evacuation path optimization system based on the shortest global evacuation time, the system comprising:

[0032] An evacuation road network model building module is used to generate a corresponding evacuation road network model G(V,E) from the building plan of the case to be analyzed;

[0033] Determine the evacuation personnel distribution plan P num Module, based on the evacuation road network model G(V,E) obtained by the evacuation road network model construction module, determines the evacuation personnel distribution plan P num ;

[0034] The shortest evacuation path plan P R_min A determination module is used to determine the evacuation personnel distribution plan P based on num The evacuation personnel distribution plan P determined by the module num , determine the shortest evacuation path plan P R_min , the shortest evacuation path solution P R_min Including determining the set of alternative evacuation paths S for each group ap And the weight value matrix D of the group alternative evacuation path ap ;

[0035] The group number k0 determination module is used to determine the evacuation path based on the shortest path solution P R_min The determination module calculates the shortest evacuation path solution P R_min The evacuation simulation results of the scheme are used to obtain the global evacuation time t g0 The group number that finally completed evacuation is k0;

[0036] The module for determining the optimal evacuation group set is used to determine the optimal evacuation group sets Ord_FSR_SV_set and Ord_SSR_SV_set according to the two-way mobilization strategy;

[0037] Set the initial optimization plan P R_oe Module, used to determine the optimal evacuation group set Ord_FSR_SV_set and Ord_SSR_SV_set determined by the optimal evacuation group set module, and set the initial optimization plan P R_oe ;

[0038] The first optimization adjustment area optimization module is used to set the initial optimization solution P R_oe The initial optimization scheme P set by the module R_oe Iteratively optimizing the evacuation path of the group in the first optimization adjustment area, where the first optimization adjustment area is the evacuation area on one side where the last group to complete evacuation is located;

[0039] The first optimization adjustment area optimization module is used to set the initial optimization solution P R_oe The initial optimization scheme P set by the module R_oe Iteratively optimize the evacuation path of the group in the second optimization adjustment area; the second optimization adjustment area is the evacuation area on the other side that does not include the last group to complete the evacuation as the second optimization adjustment area;

[0040] Output module, used to output the final optimized evacuation path plan P R_oe And the corresponding evacuation process simulation results.

[0041] Solution three: A computer device includes a memory and a processor, wherein the memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the method for determining the formula described in any one of Solution one.

[0042] Solution 4: A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for determining the formula described in any one of Solution 1.

[0043] The present invention is beneficial in that:

[0044] The present invention proposes a method and system for optimizing the evacuation path of people in a building based on the shortest global evacuation time. In the optimization process, a crowd evacuation simulation method that can take into account the reduction of the traffic rate of people in crowded places is used as a simulation calculation tool for the evacuation process in the iteration step. Compared with the existing evacuation path optimization method, this method can take into account the actual situation of crowd evacuation in a crowded state during the process of optimizing the evacuation path, and can further improve the traffic capacity of each intermediate node.

[0045] The method used in the present invention optimizes the evacuation path of a multi-story building example, and compares the evacuation results of the optimized solution with the evacuation results of the shortest path evacuation path solution. The results show that the proposed optimization method can make the utilization rate of each exit of a single building more balanced and reduce the global evacuation time.

[0046] That is, the present invention is also applicable to the field of optimizing the evacuation path of people in a building. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of the optimization method using a bidirectional mobilization strategy as described in implementation mode 1.

[0048] Figure 2 This is a schematic diagram of the horizontal section simplification process described in Implementation Method 11.

[0049] Figure 3 This is a schematic diagram of the simplified process of the vertical section described in Implementation Method 11.

[0050] Figure 4 For the multi-story building case described in the eleventh embodiment, the shortest path solution P R_min Below is a floor plan diagram of the evacuation area covered by each exit - 01 floor.

[0051] Figure 5 For the multi-story building case described in the eleventh embodiment, the shortest path solution P R_min Below is a floor plan diagram of the evacuation area covered by each exit - 02 floor.

[0052] Figure 6 For the multi-story building case described in the eleventh embodiment, the shortest path solution P R_min Below is a floor plan diagram of the evacuation area covered by each exit - 03 floor.

[0053] Figure 3 (a) is a vertical schematic diagram of the actual passable road section. Figure 3 (b) is a schematic diagram of the 2D representation of the vertical edge. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of the implementation methods of the present application clearer, the technical solutions in the implementation methods of the present application will be clearly and completely described below in conjunction with the drawings in the implementation methods of the present application. Obviously, the described implementation methods are only part of the implementation methods of the present application, not all of the implementation methods.

[0055] Implementation method 1, see Figure 1 The present embodiment is described as follows: a method for optimizing the evacuation path of people in a building based on the shortest global evacuation time, the method comprising:

[0056] Step 1: Generate the corresponding evacuation road network model G(V,E) from the building plan of the case to be analyzed;

[0057] Step 2: Determine the evacuation personnel distribution plan P based on the evacuation road network model G(V,E) obtained in step 1 num ;

[0058] Step 3: Based on the evacuation personnel distribution plan P determined in step 2 num , determine the shortest evacuation path plan P R_min , the shortest evacuation path solution P R_min Including determining the set of alternative evacuation paths S for each group ap And the weight value matrix D of the group alternative evacuation path ap ;

[0059] Step 4: Calculate the shortest evacuation path plan P based on step 3 R_min The evacuation simulation results of the scheme are used to obtain the global evacuation time t g0 The group number k0 that has completed evacuation;

[0060] Step 5: According to the two-way mobilization strategy, determine the evacuation group sets to be optimized Ord_FSR_SV_set and Ord_SSR_SV_set;

[0061] Step 6: Based on the evacuation group sets to be optimized Ord_FSR_SV_set and Ord_SSR_SV_set determined in step 5, set the initial optimization scheme P R_oe ;

[0062] Step 7: Based on the initial optimization solution P set in step 6 R_oe Iteratively optimizing the evacuation path of the group in the first optimization adjustment area, where the first optimization adjustment area is the evacuation area on one side where the last group to complete evacuation is located;

[0063] Step 8: Based on the initial optimization solution P set in step 6 R_oeIteratively optimize the evacuation path of the group in the second optimization adjustment area; the second optimization adjustment area is the evacuation area on the other side that does not include the last group to complete the evacuation as the second optimization adjustment area;

[0064] Step 9: Output the final optimized evacuation path plan P R_oe And the corresponding evacuation process simulation results.

[0065] Implementation method 2: This implementation method is a further limitation of the method for optimizing the evacuation path of people in a building based on the shortest global evacuation time described in implementation method 1. In step 3, the shortest evacuation path solution P is determined. R_min Calculated by Floyd algorithm.

[0066] Implementation method 3: This implementation method is a further limitation of the method for optimizing the evacuation path of people in a building based on the shortest global evacuation time described in implementation method 1. In step 6, an initial optimization scheme P is set. R_oe The method is to convert the shortest evacuation path plan P R_min As the initial optimization solution P in the optimization iteration process R_oe , that is, let P R_oe =P R_min , t g_oe =t g0 , and take m FSR =0.

[0067] Implementation mode 4: This implementation mode further limits the method for optimizing the evacuation path of people in a building based on the shortest global evacuation time described in implementation mode 1. In step 7, the initial optimization scheme P set in step 6 is R_oe The method of iteratively optimizing the evacuation path of the group in the first optimization adjustment area is:

[0068] S7.1. Each iteration adjusts the evacuation path of only one group, which is numbered Ord_FSR_SV_set[m FSR ];

[0069] S7.2. Calculate P R_temp The evacuation simulation results of the scheme are used to obtain the global evacuation time t g_temp ;

[0070] S7.3, according to the global evacuation time t g_temp Determine whether the iteration is terminated.

[0071] Implementation mode 5: This implementation mode further limits the method for optimizing the evacuation path of people in a building based on the shortest global evacuation time described in implementation mode 1. In step 8, the initial optimization scheme P set in step 6 is R_oeThe method for iteratively optimizing the evacuation path of the group in the second optimization adjustment area is:

[0072] S8.1. Each iteration adjusts the evacuation path of only one group, which is numbered Ord_SSR_SV_set[m SSR ].

[0073] S8.2. Calculate P R_temp The evacuation simulation results of the scheme are used to obtain the global evacuation time t g_temp ;

[0074] S8.3, based on the global evacuation time t g_temp Determine whether the iteration is terminated.

[0075] Implementation method 6: This implementation method further limits the method for optimizing the evacuation path of people in a building based on the shortest global evacuation time described in implementation method 1. In step 7, the initial optimization scheme P set in step 6 is R_oe The iterative optimization of the evacuation path of the group in the first optimization adjustment area also includes a step of determining whether the iteration is terminated.

[0076] Implementation VII: This implementation is a further limitation of the method for optimizing the evacuation path of people in a building based on the shortest global evacuation time described in Implementation VI. In S3, according to the global evacuation time t g_temp The method to determine whether the iteration is terminated is:

[0077] If g_temp <t g_oe , then update P R_oe With t g_oe , that is, let P R_oe =P R_temp , t g_oe =t g_temp , and enter the next iteration at the same time;

[0078] If g_temp >t g_oe , then stop the iteration and exit step seven.

[0079] Embodiment 8: This embodiment proposes a system for optimizing the evacuation path of people in a building based on the shortest global evacuation time, the system comprising:

[0080] An evacuation road network model building module is used to generate a corresponding evacuation road network model G(V,E) from the building plan of the case to be analyzed;

[0081] Determine the evacuation personnel distribution plan P num Module, based on the evacuation road network model G(V,E) obtained by the evacuation road network model construction module, determines the evacuation personnel distribution plan P num ;

[0082] The shortest evacuation path plan P R_min A determination module is used to determine the evacuation personnel distribution plan P based on num The evacuation personnel distribution plan P determined by the module num , determine the shortest evacuation path plan P R_min , the shortest evacuation path solution P R_min Including determining the set of alternative evacuation paths S for each group ap And the weight value matrix D of the group alternative evacuation path ap ;

[0083] The group number k0 determination module is used to determine the evacuation path based on the shortest path solution P R_min The determination module calculates the shortest evacuation path plan P R_min The evacuation simulation results of the scheme are used to obtain the global evacuation time t g0 The group number that finally completed evacuation is k0;

[0084] The module for determining the optimal evacuation group set is used to determine the optimal evacuation group sets Ord_FSR_SV_set and Ord_SSR_SV_set according to the two-way mobilization strategy;

[0085] Set the initial optimization plan P R_oe Module, used to determine the optimal evacuation group set Ord_FSR_SV_set and Ord_SSR_SV_set determined by the optimal evacuation group set module, and set the initial optimization plan P R_oe ;

[0086] The first optimization adjustment area optimization module is used to set the initial optimization solution P R_oe The initial optimization scheme P set by the module R_oe Iteratively optimizing the evacuation path of the group in the first optimization adjustment area, where the first optimization adjustment area is the evacuation area on one side where the last group to complete evacuation is located;

[0087] The first optimization adjustment area optimization module is used to set the initial optimization solution P R_oe The initial optimization scheme P set by the module R_oe Iteratively optimizing the evacuation path of the group in the second optimization adjustment area; the second optimization adjustment area is the evacuation area on the other side that does not include the last group to complete the evacuation as the second optimization adjustment area;

[0088] Output module, used to output the final optimized evacuation path plan P R_oe And the corresponding evacuation process simulation results.

[0089] Embodiment 9. This embodiment proposes a computer device, including a memory and a processor, wherein the memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the method for determining the formula described in any one of embodiments 1 to 7.

[0090] Embodiment 10: This embodiment proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the method for determining the formula described in any one of embodiments 1 to 7 are implemented.

[0091] Implementation 11: This implementation proposes an example, which is used to explain the above implementations 1 to 10. Figures 1 to 6 The present embodiment is described, and the specific contents of the present embodiment are as follows:

[0092] This implementation method proposes a method for optimizing the evacuation path of people in a building that can take into account the actual situation of crowd evacuation under crowded conditions. This method can quantitatively consider the reduction in the traffic rate of people in crowded locations during the optimization process, and establish a corresponding optimization strategy based on the physical formation mechanism of the global evacuation time in the building, which can make the utilization rate of each exit of a single building more balanced and reduce the global evacuation time.

[0093] The working process of the method for optimizing the evacuation path of people in a building proposed in this embodiment is as follows: Figure 1 As shown, it specifically includes 9 steps:

[0094] Step 1: Generate the corresponding evacuation road network model G(V,E) from the building plan of the case to be analyzed;

[0095] Step 2: Determine the evacuation personnel distribution plan P num ;

[0096] Step 3: Determine the shortest evacuation path plan P R_min , the set of alternative evacuation paths S for each group ap And the weight value matrix D of the group alternative evacuation path ap ;

[0097] Step 4: Calculate P R_min The evacuation simulation results of the scheme are used to obtain the global evacuation time t g0 The group number that finally completed evacuation is k0;

[0098] Step 5: According to the two-way mobilization strategy, determine the optimal evacuation group sets Ord_FSR_SV_set and Ord_SSR_SV_set;

[0099] Step 6: Set the initial optimization plan PR_oe ;

[0100] Step 7: Iterative Optimization First, optimize and adjust the evacuation path of the group in the area.

[0101] Step 8: Iteratively optimize the evacuation path of the group in the second optimization adjustment area.

[0102] Step 9: Output the final optimized evacuation path plan P R_oe And the corresponding evacuation process simulation results.

[0103] The working principles of the above nine steps are introduced in detail below.

[0104] Step 1: Generate the corresponding evacuation road network model G(V,E) from the building plan of the case to be analyzed;

[0105] Based on the building plan of the case to be analyzed, the spatial information of the evacuation scene is converted into the corresponding evacuation road network model G(V,E) according to the modeling method of the geometric network model of the evacuation path in the invention titled "Macroscopic Simulation Method and Device for Crowd Evacuation Considering Reduction of Passage Rate of People in Congested Places", which mainly includes the setting rules of nodes and edges. In the subsequent content, we will refer to the geometric network model of the evacuation path in the building as the evacuation road network. Next, the node setting rules and edge setting rules in the evacuation road network modeling method will be introduced respectively.

[0106] 1.1.1.Node setting rules

[0107] The evacuation network in a building is denoted as G(V,E). Each room or area with a certain use function, the building's exit, passage, and both ends of the stairs are set as nodes (vertex, denoted as V), and the passable paths between nodes are set as edges (edge, denoted as E), thus forming an evacuation network. The nodes V in the evacuation network G(V,E) can be divided into three categories, and their respective setting rules are shown in Table 1.

[0108]

[0109] The setting of source nodes is also related to the number of people. At present, we set that if the number of people in a room exceeds 10, multiple source nodes should be set, that is, the room is divided into multiple areas, and a corresponding source node is set for each area to ensure that the number of people in each source node does not exceed 10. Considering that the position of each person in the room / area is different, and the distance from the exit of the room / area is close or far, the geometric center of the room / area is used as the position of the simplified node, that is, the evacuation departure position of all people in the room / area is simplified and set at the geometric center of the room / area. It can be seen that in our simulation method, each source node contains only one group (the number of people in each group is ≤10), then the number of source nodes is equal to the number of evacuation groups, that is, the source node corresponds to the evacuation group contained in it one by one. Therefore, we set the source node in the simulation method to the same number as the evacuation group contained in it, that is, the number of the source node is the number of the evacuation group contained in it.

[0110] The traffic connection part in the building refers to the corridor, hallway, staircase and other parts. The location where the intermediate node is set is often where the evacuation paths converge or the traffic capacity changes significantly. These locations are where congestion may occur during emergency evacuation. That is, the location where the intermediate node is set includes all the locations where congestion may occur during the actual evacuation process. In the evacuation road network, the node numbering order is source node, intermediate node, exit node, and the starting value of the numbering is 0.

[0111] 1.1.2. Edge Setting Rules

[0112] All types of traffic connections in the building are simplified as edges E to represent the passable sections between nodes. Each edge in the evacuation road network is a directed edge, with one node connected at the beginning and end, that is, there are only two nodes on an edge. The length of the actual passable section from the origin of the edge to the terminus of the edge is used as the weight of the edge.

[0113] According to the space type, the accessible sections in the building can be divided into horizontal sections and vertical sections. The details of the simplified process of the edges of the horizontal sections are as follows: Figure 1 As shown. When earthquakes, fires and other emergencies that damage building structures occur, some obstacles will be created to affect the passage of people. Figure 2 As shown in the actual passable road section from node 1 to node 57 in the figure, for obstacles such as furniture and building debris during the evacuation process, the actual passable evacuation road section needs to maintain a certain distance from these obstacles to ensure the continuity of the evacuation process and the safety of personnel. In other words, the proposed evacuation road network modeling method can reflect the details of the evacuation process of evacuees avoiding obstacles. Figure 1The green dotted line in the middle represents the actual passable road section during the evacuation process, and the black solid line represents the edge E simplified from the actual passable road section. The simplified edge E connects the first and last nodes with a straight line. It only indicates the passability between the nodes and the direction of the road section, and cannot reflect the actual shape of the passable road section during the evacuation process.

[0114] According to current international standards, stairs are currently the only legal means of evacuation in multi-story buildings. As the most traditional evacuation method, stairs have always been the first choice for people to evacuate vertically in dangerous situations in buildings. Therefore, in the process of establishing the evacuation network of multi-story buildings, we only use stairs for vertical evacuation, that is, the evacuation network only contains vertical edges simplified from the vertically accessible evacuation sections corresponding to the stairs. The details of the simplification process of the edges corresponding to the vertical sections are as follows: Figure 2 As shown. Among them, Figure 3 (a) represents the actual traversable road section in vertical direction. Figure 3 (b) shows the representation of the one-way edge corresponding to the vertical section in the two-dimensional plane diagram of the evacuation road network. Similar to the horizontal sections, the evacuation road network modeling method proposed in this paper can also consider the impact of obstacles in the vertical sections on the evacuation process of personnel. In addition, considering that the evacuation process in a multi-story building is to leave the building and reach a safe area outside the building as the evacuation goal. Therefore, in the evacuation road network, the direction of the vertical sections is from top to bottom, that is, from the nodes on the high floors to the nodes on the low floors. In the two-dimensional plane diagram of the evacuation road network, the edges corresponding to the vertical sections are represented by yellow one-way solid lines, and their specific representation is as follows Figure 3 As shown in (b), the representation of vertical edges cannot reflect the actual shape of the passage section during the evacuation process.

[0115] 1.1.3. Schematic diagram of evacuation road network

[0116] According to the edge setting rules in Section 1.1.2., in the evacuation road network diagram, the edges corresponding to the horizontal evacuation sections are mainly divided into two categories: one-way edges are represented by black single arrow solid lines, and the arrow direction points to the end point of the one-way edge; two-way edges are represented by blue double arrow solid lines, and each has an arrow pointing to the two end-vertices of the two-way edge. The edges corresponding to the vertical evacuation sections are one-way edges from top to bottom, represented by yellow single arrow solid lines. Figures 4 to 6 This is a multi-story building case. In the shortest path solution P R_min The following is a schematic diagram of the evacuation area covered by each exit. Figures 4 to 6 The evacuation road network of the multi-story building case is also shown in the figure. The setting rules of the nodes and edges of the evacuation road network comply with the relevant requirements of Sections 1.1.1 and 1.1.2.

[0117] 1.2. Step 2: Determine the evacuation personnel distribution plan P num ;

[0118] Determine the initial number of people in each room, that is, the evacuation personnel distribution plan P num , and according to P num Update the setting of the source node in G(V,E) according to the situation.

[0119] 1.3. Step 3: Determine the shortest evacuation path P R_min , the set of alternative evacuation paths S for each group ap And the weight value matrix D of the group alternative evacuation path ap ;

[0120] Next, we will further explain that the Floyd algorithm determines the shortest path information between all node pairs in the evacuation network, and further generates the shortest path evacuation path plan P R_min , the set of alternative evacuation paths S for each group ap And the weight value matrix D of the group alternative evacuation path ap process.

[0121] 1.3.1. Initial evacuation path plan P R_min

[0122] In this embodiment, the shortest evacuation path solution P R_min As the initial evacuation path plan of the iterative optimization process, the Floyd algorithm is used to calculate the shortest path information between all node pairs in the evacuation network. As described in Section 1.1.1, the number of the source node in the evacuation network is the number of the evacuee group contained in it. Therefore, after the Floyd algorithm determines the shortest path information between all node pairs in the evacuation network, the initial evacuation path plan, i.e., the shortest path evacuation path plan P, can be determined from the source node number set. R_min Specifically, this study sets all safety zones in the evacuation road network as an abstract node V s Then, connect each outlet to the abstract node V s The length weights of the edges are all set to 1m. Therefore, from a source node to the abstract node V s The shortest path is the global shortest evacuation path of the source node in the building. The path length of this evacuation path is shorter than the path from the source node to the abstract node V. s The shortest path length is 1m less. Repeat the above operation for all source nodes in the source node number set (one-to-one correspondence with the personnel group) to obtain the shortest evacuation path plan P for the building. R_min .

[0123] 1.3.2. Group Alternative Path Set Sap

[0124] According to the shortest path information between all node pairs in the evacuation network, the set of alternative evacuation paths S for each group can be further determined. ap The alternative path set stores the accessible paths for each evacuation group to all the exits of the building, and its data storage structure is shown in Table 2. The sample data in Table 2 comes from Figures 4 to 6 The group alternative evacuation path set S for the multi-story building example shown ap . Group alternative evacuation path set S ap is a matrix whose row index value corresponds to the source node V in the building evacuation network s The number of the personnel group is consistent with the personnel group number, and the column index corresponds to the exit node V in the building evacuation network. e Each element represents the shortest passable path from a group to a certain exit, which is represented in the form of an array. The array contains all the node numbers that the shortest passable path passes through from the starting point to the end point. ap If an element S ap [i][j] is an empty array [], indicating that there is no traversable path from the source node i to the exit j, that is, the group of people i corresponding to the source node cannot reach the exit j during the evacuation process.

[0125] In addition, when generating the group alternative evacuation path set S ap At the same time, the corresponding group alternative evacuation path weight value matrix D is also generated ap , the row index value and column index value of the matrix are the same as S ap Consistent. D ap An element D in ap [i][j] and the element S in the group's alternative evacuation path set ap [i][j] correspond one to one. ap The value of [i][j] is the shortest traversable path S from group i to exit j. ap The total length of [i][j]. ap When [i][j] is an empty array [] (source node i and exit j are not accessible), its corresponding D ap [i][j] takes the value of inf, i.e., infinity. In the subsequent optimization iteration process, the evacuation path adjustment of group i will be selected in order from low to high according to the length values ​​of the alternative paths.

[0126]

[0127] 1.4. Step 4: Calculate P R_min The evacuation simulation results of the scheme are used to obtain the global evacuation time t g0 The group number that finally completed evacuation is k0;

[0128] According to the invention titled "Crowd Evacuation Macroscopic Simulation Method and Device Considering Reduction of Passage Rate of People in Crowded Places", P is calculated. R_min The evacuation simulation results of the scheme are used to obtain the global evacuation time t g0 The group number that finally completed evacuation is k0;

[0129] 1.5. Step 5: According to the two-way mobilization strategy, determine the optimal evacuation group sets Ord_FSR_SV_set and Ord_SSR_SV_set;

[0130] This implementation method establishes a two-way mobilization optimization strategy based on the physical formation mechanism of the global evacuation time in the building, and then through the two-way mobilization strategy, P R_min , k0 and S ap Two sets of optimized evacuation groups Ord_FSR_SV_set and Ord_SSR_SV_set are determined in turn. The specific description of the two-way mobilization strategy is as follows:

[0131] First, the last exit to be evacuated is V el The evacuation groups in the evacuation area are divided into two parts (each of which establishes a set) according to their positions relative to the stairwell connected to the exit. One part of the group is on the side where the last group k to complete the evacuation is located, and the remaining group is on the other side of the stairwell. In this patent, the evacuation area on the side where the last group to complete the evacuation is located is called the first optimization adjustment region. The evacuation area on the other side that does not contain the last group to complete the evacuation is called the second optimization adjustment region.

[0132] Then, the two groups are sorted according to the order to be adjusted in the optimization iteration process. The group k that is the last to be evacuated is the first to be optimized (corresponding to the first optimization adjustment area). It is sorted from high to low according to the distance from the current exit (the last exit to be evacuated under the shortest path solution). The sorted set is recorded as Ord_FSR_SV_set. For the group set on the other side, it needs to be sorted according to the following two sorting rules:

[0133] First, arrange them according to the floors where the groups are located, from the highest floor down (the higher the floor, the longer the evacuation distance, and the later the order of completing the evacuation);

[0134] Secondly, for the evacuation groups within the same floor, they are further sorted from low to high according to their distance from the nearest exit in the direction to be adjusted (the closer to the nearest exit in the direction to be adjusted, the farther from the original exit. In this way, the groups in the evacuation area of ​​the original exit are mobilized from the outside to the inside, which can avoid conflicts in personnel flow lines).

[0135] The final set of personnel groups in the second optimized adjustment area that has been sorted is recorded as Ord_SSR_SV_set. After completing the classification and sorting of the above personnel groups, the first optimized adjustment area and the second optimized adjustment area are optimized in turn according to the optimization iteration criteria. After the optimization is completed, the final optimized evacuation path plan can be obtained. The above is an explanation of the two-way mobilization strategy.

[0136] 1.6. Step 6: Set the initial optimization plan P R_oe

[0137] The shortest evacuation path plan P R_min As the initial optimization solution P in the optimization iteration process R_oe , that is, let P R_oe =P R_min , t g_oe =t g0 . At the same time, take m FSR =0.

[0138] 1.7. Step 7: Iterative Optimization First, optimize and adjust the evacuation path of the group in the area.

[0139] In order to make the utilization rate of each exit in the building more balanced, this patent starts from the perspective of global evacuation of a single building and takes the global evacuation time t g The shortest is the optimization goal, and the corresponding iteration termination criterion is shown in formula (1).

[0140] t g_temp ≥t g_oe (1)

[0141] Where, t g_temp is the global evacuation time (s) corresponding to the updated evacuation path plan in the current iteration step; t g_oe is the global evacuation time (s) corresponding to the optimal evacuation path solution in the current iteration step.

[0142] In this step, the evacuation path of the group in the first optimization adjustment area is optimized and adjusted. The ordered number set of the group in the first optimization adjustment area is Ord_FSR_SV_set.

[0143] Each optimization iteration can be further divided into three sub-steps, as follows:

[0144] Iteration: Each iteration adjusts the evacuation path of only one group, which is numbered Ord_FSR_SV_set[m FSR The specific adjustment operation is to set the group Ord_FSR_SV_set[m FSR ] is adjusted to the shortest evacuation path between the group and the second closest (second closest) exit (this path is actually the group Ord_FSR_SV_set[m FSR ] The second shortest evacuation path in the overall building). After the adjustment is completed, a new evacuation path plan P is formed. R_temp , and let m FSR =m FSR +1.

[0145] Evacuation simulation calculation: P is calculated according to the macroscopic evacuation simulation method proposed in the invention titled Macroscopic simulation method and device for crowd evacuation considering reduction of traffic speed of people in crowded places. R_temp The evacuation simulation results of the scheme are used to obtain the global evacuation time t g_temp ;

[0146] Judgment: According to the iteration termination criterion shown in formula (5-1), g_temp Make a judgment.

[0147] If g_temp <t g_oe , then update P R_oe With t g_oe , that is, let P R_oe =P R_temp , t g_oe =t g_temp , and enter the next iteration at the same time.

[0148] If g_temp >t g_oe , then stop the iteration and exit step seven.

[0149] 1.8. Step 8: Iterative Optimization The second optimization adjusts the evacuation path of the group in the area.

[0150] In this step, the evacuation paths of the groups in the second optimization adjustment area are optimized. The ordered number set of the groups in the second optimization adjustment area is Ord_SSR_SV_set. The optimization goal and iteration termination criteria in the optimization process of this step are consistent with those in step 7. Before the first iteration begins, m SSR = 0. Consistent with step 7, each optimization iteration in step 8 can also be further divided into three steps, as follows:

[0151] Iteration: Each iteration adjusts the evacuation path of only one group, which is numbered Ord_SSR_SV_set[mSSR The specific adjustment operation is to adjust the group Ord_SSR_SV_set[m SSR ] is adjusted to the shortest evacuation path between the group and the second closest (second closest) exit (this path is actually the group Ord_SSR_SV_set[m SSR ] The second shortest evacuation path in the overall building). After the adjustment is completed, a new evacuation path plan P is formed. R_temp , and let m SSR =m SSR +1.

[0152] Evacuation simulation calculation: P is calculated according to the macroscopic evacuation simulation method proposed in Chapter 4. R_temp The evacuation simulation results of the scheme are used to obtain the global evacuation time t g_temp ;

[0153] Judgment: According to the iteration termination criterion shown in formula (5-1), g_temp Make a judgment.

[0154] If g_temp <t g_oe , then update P R_oe With t g_oe , that is, let P R_oe =P R_temp , t g_oe =t g_temp , and enter the next iteration at the same time.

[0155] If g_temp >t g_oe , then stop the iteration and exit step eight.

[0156] 1.9. Step 9: Output the final optimized evacuation path plan P R_oe And the corresponding evacuation process simulation results.

[0157] After completing the iterative optimization of steps 7 and 8, the final optimized evacuation path plan P is output. R_oe And the evacuation simulation calculation results corresponding to this scheme.

[0158] The above are the working steps and working principles of the method for optimizing the evacuation path of people in a building proposed in this embodiment. The parameter symbols used in the optimization method are summarized in Table 3.

[0159]

[0160] The following is a specific implementation example of the method for optimizing the evacuation path of people in a building proposed by this patent. The example is a hospital in H City, which is a 3-story building and includes a vertical evacuation process. The implementation process of the method for optimizing the evacuation path of people in a building proposed by this patent on this 3-story building example is as follows:

[0161] 1. From step 1 and step 2, we can obtain the evacuation road network model G(V, E) and the evacuation personnel distribution plan P of the case to be analyzed. num , forming the input data file.

[0162] Based on the building space layout and usage functions shown in the multi-story example building plan, combined with our building evacuation network establishment rules, we established the following Figures 4 to 6 The multi-layer example evacuation network shown in . In the mathematical model of the evacuation network of the multi-layer example, there are 161 source nodes, and the corresponding numbers are 0 to 160, among which: the first layer has 49 source nodes, numbered 0 to 48; the second layer has 56 source nodes, numbered 49 to 104; the third layer has 56 source nodes, numbered 105 to 160. The number of evacuees included in the evacuation group i corresponding to a certain source node i is Neg i exist Figures 4 to 6 The blue bold numbers are displayed next to the source node symbol. There are 32 intermediate nodes in total, and the distribution of intermediate nodes in each layer is shown in Table 4. There are 6 exit nodes, all on the first floor, numbered 193 to 198. The total number of nodes in the evacuation network of this multi-layer example is 199, the abstract node number of the safe zone is 199, and the total number of people participating in the evacuation in the entire building is 555, including 191 on the first floor, 184 on the second floor, and 180 on the third floor. The representation of the three types of nodes in the evacuation network of multi-story buildings in the evacuation network schematic diagram is shown in Table 1, which will not be repeated here.

[0163] The total number of directed edges in the evacuation road network of the multi-layer example is 430, and the weight value of each edge is currently calculated by manual measurement. The representation of various types of edges in the evacuation road network plan diagram is detailed in Section 1.1.2, and will not be repeated here. In the three-dimensional schematic diagram of the evacuation road network, the edges corresponding to the vertical sections are displayed in the form of red dashed lines, and the starting and ending points of the vertical edges are marked with green solid dots.

[0164]

[0165] After processing in step 1 and step 2, a data file of the evacuation path geometric network model (abbreviated as evacuation path network) of the three-story building is formed to be input into the calculation program of the optimization method. The file contains 4 data tables:

[0166] Data Table 1: Link Information, stores the relevant information of each edge in the evacuation road network model, including: 1) edge ID, 2) edge start and end information, 3) edge length weight value, 4) edge section type (horizontal or vertical).

[0167] Wherein ID means: number.

[0168] Data Table 2: Number of Source Nodes, stores the source node information in the evacuation road network model, specifically including: the ID of the source node (one-to-one correspondence with the ID of the evacuation group), and the number of evacuation groups corresponding to the source node.

[0169] Therefore, Data Table 2 shows the initial distribution of evacuees in this building instance.

[0170] Data Table 3: Middle Node capacity, stores the middle node information in the evacuation road network model, specifically including: 1) the ID of the middle node; 2) the passable width W of the middle node (indicating the passable capacity of the middle node); 3) the spatial form of the actual evacuation scene at the corresponding position of the middle node (expressed in the specific value of OPS: OPS = 0.4 represents the spatial form of the evacuation scene corresponding to the first type of crowd gathering form; OPS = 0.3 represents the spatial form of the evacuation scene corresponding to the second type of crowd gathering form).

[0171] Data Table 4: Exit capacity, stores the exit node information in the evacuation road network model, specifically including: 1) the ID of the exit node; 2) the passable width W of the exit node; 3) the spatial form of the actual evacuation scene at the corresponding position of the exit node (expressed in the specific value of OPS: OPS = 0.4 represents the spatial form of the evacuation scene corresponding to the first type of crowd gathering form; OPS = 0.3 represents the spatial form of the evacuation scene corresponding to the second type of crowd gathering form).

[0172] 2. Input the data files from step 1 and step 2 into the calculation program corresponding to the proposed optimization method. After completing the calculations corresponding to steps 3 to 9, output the final optimized evacuation path plan P. R_oe And the corresponding evacuation process simulation results.

[0173] The evacuation road network data file of the three-story building example formed in step 1 and step 2 is input into the calculation program of the building personnel evacuation path optimization method proposed in this patent. The program is run to optimize the evacuation path of the three-story building personnel. After completing the calculations corresponding to step 3 to step 9, the final optimized evacuation path plan P is obtained. R_oe And the simulation calculation results of the evacuation process corresponding to the optimization scheme.

[0174] The key results involved in the calculation process are described as follows:

[0175] Initial evacuation path plan P R_min

[0176] Compared with the initial evacuation path plan P in this example R_min The corresponding evacuation area A carried by each exit of the building i (i is the exit node number), such as Figures 4 to 6 shown. Figures 4 to 6 In an evacuation area A i The final exit for all evacuation groups within is exit i. Figures 4 to 6 In the figure, dotted lines (red or green) are used to mark the evacuation area range carried by each exit in the single-layer evacuation road network. In order to clearly distinguish the boundaries of each evacuation area, the dotted lines of adjacent evacuation areas are in different colors (red or green).

[0177] Optimize the evacuation route plan P R_oe

[0178] Optimize the evacuation route plan P R_oe The data storage structure of is shown in Table 5. The sample data in Table 5 comes from the optimized evacuation path scheme P of the multi-story building example. R_oe .

[0179]

[0180]

[0181] Initial evacuation path plan P R_min The data storage structure is also similar to P R_oe of consistency.

[0182] Simulation calculation results of the evacuation process corresponding to the optimization scheme P_Locs

[0183]

[0184] Among them: 1) Group ID: evacuation group number; 2) t d : The moment when the overall evacuation of the building is completed; 3)n d : The number of program calculation steps corresponding to the end of global evacuation; 4) The column index and row index in Table 6 (i.e., the bold words in Table 6) are not displayed in the actual result file.

[0185] The simulation calculation results of the evacuation process corresponding to each personnel evacuation path are stored in the personnel position state matrix P_Locs. In the personnel position state matrix P_Locs, the column index corresponds to the number of the group in each source node, and the row index corresponds to the cycle time step (time interval 0.1s). The position of the personnel at a certain moment in the evacuation process is identified by the corresponding position label in P_Locs. Because the numbers of nodes and edges are integers starting from 0, in order to effectively distinguish whether the personnel are on the edge or at the node, we take the position label of the personnel on the edge as the number of the edge, and take the position label of the personnel when waiting at the node as 100000×node number. In addition, in P_Locs, we uniformly set the position labels of all safe zones to -1. The data storage structure of P_Locs corresponding to the three-story building example is shown in Table 6.

[0186] Next, the optimized evacuation path solution P calculated by the proposed optimization method is R_oe Evacuation simulation results and the shortest evacuation path solution P R min The evacuation simulation results of the two evacuation paths (i.e., the initial evacuation path plan) are compared to illustrate the optimization effect of the optimization method.

[0187] Compared with the shortest evacuation path solution P in this example R_min The corresponding evacuation area A carried by each exit of the building i (i is the exit node number), such as Figures 4 to 6 shown. Figures 4 to 6 In an evacuation area A i The final exit for all evacuation groups in is exit i. The optimal evacuation path scheme P for the three-story building example is obtained by calculation using the proposed optimization method. R_oe Compared with the shortest evacuation path solution P R_min , optimize the evacuation path plan P R_oe The evacuation routes of 5 evacuation groups were adjusted, and the specific adjustments are as follows:

[0188] Groups 155 and 154 will be evacuated from Exit 197 to Exit 194;

[0189] Groups 150, 138, and 137 will be evacuated from Exit 197 to Exit 198.

[0190] At the global evacuation time t g Optimize the evacuation path plan P R_oe Relative to the shortest evacuation path plan P R_min The time was shortened by 8.0s. The relevant results are shown in Table 7.

[0191]

[0192] Next, we further compare the internal evacuation conditions of the evacuation areas carried by each exit under the two evacuation path schemes. First, we compare the distribution of people in each evacuation area. R_min The distribution of personnel in each evacuation area is shown in Table 8. The optimized evacuation path plan P R_oe The distribution of personnel in each evacuation area is shown in Table 9. Combining Tables 8 and 9 and the specific adjustment information of the evacuation path, it can be seen that the optimized evacuation path scheme P of the multi-layer example R_oe , take Exit 197 (the shortest route option P R_min Some groups of people in the evacuation area carried by Exit 197 (the last exit to complete evacuation) were adjusted to the evacuation areas of Exit 194 and Exit 198 on both sides of it, thereby alleviating the evacuation pressure at Exit 197 and increasing the utilization rate of Exits 194 and 198.

[0193]

[0194]

[0195] The second thing to compare is the evacuation time of each exit. The evacuation time of each exit under the two schemes is shown in Table 10. As can be seen from Table 10, after relieving the evacuation pressure of Exit 197, the evacuation time of Exit 197 has decreased to a certain extent. At the same time, the evacuation time of the two adjacent exits (194 and 198) also increases with the increase in the number of people in the corresponding evacuation area. This shows that the optimized evacuation path scheme P R_oe There is further use of the accessible resources of Exits 194 and 198. In addition, from the results of Table 7 and Table 10, it can be seen that in the optimization of the evacuation path plan P R_oe Under the guidance of , the exit where the evacuation was finally completed in the multi-layer example changed from Exit 197 to Exit 194. The corresponding group that finally completed the evacuation also became Group 154, which was the farthest from Exit 194 within the evacuation area of ​​Exit 194.

[0196]

[0197] Combining the optimization results of the single-layer and multi-layer examples, it can be seen that the evacuation path optimization method proposed in this embodiment adjusts the evacuation path of some evacuation groups, so that the difference between the evacuation time of the last exit to be evacuated in the single building and other exits is further reduced, and the evacuation time of each exit is relatively balanced, which shows that the proposed optimization algorithm can achieve the effect of balancing the utilization rate of the exits of the single building. Although the adjusted evacuation path increases the total evacuation distance of the corresponding group, from the perspective of global evacuation, the optimized evacuation path plan P R_oe Can reduce the global evacuation time.

[0198] Those skilled in the art will appreciate that the above are only preferred embodiments of the present invention, and the features described in the various embodiments and / or claims of the present disclosure may be combined or combined in a variety of ways, even if such combinations or combinations are not explicitly described in the present disclosure. The above are not intended to limit the present invention, and the above are only preferred embodiments of the present invention, and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art may still modify the technical solutions described in the aforementioned embodiments, or perform equivalent substitutions on some of the technical features therein, and any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

[0199] Although preferred embodiments of the present invention have been described, additional changes and modifications may be made to these embodiments by those skilled in the art once the basic inventive concepts are known. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for optimizing the evacuation path of people in a building based on the shortest global evacuation time, characterized in that: The method comprises: Step 1: Generate the corresponding evacuation road network model G(V,E) from the building plan of the case to be analyzed; Step 2: Determine the evacuation personnel distribution plan P based on the evacuation road network model G(V,E) obtained in step 1 num ; Step 3: Based on the evacuation personnel distribution plan P obtained in step 2 num Determine the shortest evacuation path plan P R_min , the shortest evacuation path solution P R_min Including determining the set of alternative evacuation paths S for each group ap And the weight value matrix D of the group alternative evacuation path ap ; Step 4: Calculate the shortest evacuation path plan P based on step 3 R_min The evacuation simulation results of the scheme are used to obtain the global evacuation time t g0 The group number k0 that has completed evacuation; Step 5: According to the two-way mobilization strategy, determine the evacuation group sets to be optimized Ord_FSR_SV_set and Ord_SSR_SV_set; Step 6: Based on the evacuation group sets to be optimized Ord_FSR_SV_set and Ord_SSR_SV_set determined in step 5, set the initial optimization scheme P R_oe ; Step 7: Based on the initial optimization solution P set in step 6 R_oe Iteratively optimizing the evacuation path of the group in the first optimization adjustment area, where the first optimization adjustment area is the evacuation area on one side where the last group to complete evacuation is located; Step 8: Based on the initial optimization solution P set in step 6 R_oe Iteratively optimize the evacuation path of the group in the second optimization adjustment area; the second optimization adjustment area is the evacuation area on the other side that does not include the last group to complete the evacuation as the second optimization adjustment area; Step 9: Output the final optimized evacuation path plan P R_oe And the corresponding evacuation process simulation results.

2. The method for optimizing the evacuation path of people in a building based on the shortest global evacuation time according to claim 1, characterized in that: In step 3, determine the shortest evacuation path plan P R_min Calculated by Floyd algorithm.

3. The method for optimizing the evacuation path of people in a building based on the shortest global evacuation time according to claim 1, characterized in that: In step 6, set the initial optimization solution P R_oe The method is to convert the shortest evacuation path plan P R_min As the initial optimization solution P in the optimization iteration process R_oe , that is, let P R_oe =P R_min , t g_oe =t g0 , and take m FSR =0.

4. The method for optimizing the evacuation path of people in a building based on the shortest global evacuation time according to claim 1, characterized in that: In step 7, the initial optimization solution P is set based on step 6. R_oe The method of iteratively optimizing the evacuation path of the group in the first optimization adjustment area is: S7.

1. Each iteration adjusts the evacuation path of only one group, which is numbered Ord_FSR_SV_set[m FSR ]; S7.

2. Calculate P R_temp The evacuation simulation results of the scheme are used to obtain the global evacuation time t g_temp ; S7.3, according to the global evacuation time t g_temp Determine whether the iteration is terminated.

5. The method for optimizing the evacuation path of people in a building based on the shortest global evacuation time according to claim 1, characterized in that: In step 8, the initial optimization solution P set in step 6 is R_oe The method for iteratively optimizing the evacuation path of the group in the second optimization adjustment area is: S8.

1. Each iteration adjusts the evacuation path of only one group, which is numbered Ord_SSR_SV_set[m SSR ]. S8.

2. Calculate P R_temp The evacuation simulation results of the scheme are used to obtain the global evacuation time t g_temp ; S8.3, based on the global evacuation time t g_temp Determine whether the iteration is terminated.

6. The method for optimizing the evacuation path of people in a building based on the shortest global evacuation time according to claim 1, characterized in that: In step 7, the initial optimization solution P is set based on step 6. R_oe The iterative optimization of the evacuation path of the group in the first optimization adjustment area also includes a step of determining whether the iteration is terminated.

7. The method for optimizing the evacuation path of people in a building based on the shortest global evacuation time according to claim 6, characterized in that: In S3, according to the global evacuation time t g_temp The method to determine whether the iteration is terminated is: If g_temp <t g_oe , then update P R_oe With t g_oe , that is, let P R_oe =P R_temp , t g_oe =t g_temp , and enter the next iteration at the same time; If g_temp >t g_oe , then stop the iteration and exit step seven.

8. A building evacuation path optimization system based on the shortest global evacuation time, characterized in that: The system comprises: An evacuation road network model building module is used to generate a corresponding evacuation road network model G(V,E) from the building plan of the case to be analyzed; Determine the evacuation personnel distribution plan P num Module, based on the evacuation road network model G(V,E) obtained by the evacuation road network model construction module, determines the evacuation personnel distribution plan P num ; The shortest evacuation path plan P R_min A determination module is used to determine the evacuation personnel distribution plan P based on num The evacuation personnel distribution plan P obtained by the module num Determine the shortest evacuation path plan P R_min , the shortest evacuation path solution P R_min Including determining the set of alternative evacuation paths S for each group ap And the weight value matrix D of the group alternative evacuation path ap ; The group number k0 determination module is used to determine the shortest evacuation path solution P R_min Determine the module to calculate the shortest evacuation path plan P R_min The evacuation simulation results of the scheme are used to obtain the global evacuation time t g0 The group number that finally completed evacuation is k0; The module for determining the set of optimized evacuation groups is used to determine the sets of evacuation groups to be optimized Ord_FSR_SV_set and Ord_SSR_SV_set according to the two-way mobilization strategy; Set the initial optimization plan P R_oe Module, used to determine the optimized evacuation group set Ord_FSR_SV_set and Ord_SSR_SV_set determined by the evacuation group set module to be optimized, and set the initial optimization plan P R_oe ; The first optimization adjustment area optimization module is used to set the initial optimization solution P R_oe The initial optimization scheme P set by the module R_oe Iteratively optimizing the evacuation path of the group in the first optimization adjustment area, where the first optimization adjustment area is the evacuation area on one side where the last group to complete evacuation is located; The first optimization adjustment area optimization module is used to set the initial optimization solution P R_oe The initial optimization scheme P set by the module R_oe Iteratively optimize the evacuation path of the group in the second optimization adjustment area; the second optimization adjustment area is the evacuation area on the other side that does not include the last group to complete the evacuation as the second optimization adjustment area; Output module, used to output the final optimized evacuation path plan P R_oe And the corresponding evacuation process simulation results.

9. Computer device, characterized in that The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor runs the computer program stored in the memory, the processor executes the method for determining the formula according to any one of claims 1 to 7.

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

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