Method and system for deploying rescue teams under single-point emergencies considering road condition information

Abstract

This invention provides a method and system for deploying rescue teams in single-point emergencies that considers road condition information. This method, which belongs to the field of emergency management technology, involves obtaining the needs of the affected site, namely, the available rescue team resources, establishing a collection of various rescue resources, constructing a rescue team dispatch plan, and updating the rescue travel time based on road conditions. The system also calculates the coordination score of the rescue team dispatch plan. An objective function is established to minimize arrival time and ensure simultaneous arrival of rescue forces from all parties, while establishing constraints based on actual conditions. Finally, an NSGA-II algorithm is designed to solve the problem, taking coordination information into account. The method provided by this invention can achieve a rescue team deployment plan with enhanced coordination while ensuring optimal objectives in emergency rescue team dispatch.

Description

Technical Field

[0001] The present invention relates to the technical field of emergency management, and in particular to a method and system for deploying a rescue team in a single-point emergency event taking into account road condition information. Background Art

[0002] With the development of transportation, the scale of railway construction continues to expand, and the number of railway bridges and tunnels built has increased accordingly. Geological disasters such as landslides and mudslides, or sudden accidents such as sudden mud and water surges during construction, often cause disasters at construction sites within railway sections, trapping construction workers, seriously threatening their safety, and impacting project progress. Rapid and efficient multi-agent collaborative emergency rescue team deployment methods still need to be improved. Disasters often lead to road congestion around the affected area. To expedite the arrival of rescue teams, it is necessary to consider traffic control measures based on road conditions. Rescue team dispatch plans that simultaneously minimize the arrival time of all parties involved and ensure that all rescue forces arrive at the disaster site simultaneously can minimize casualties and property losses. Furthermore, considering historical collaboration information between different rescue teams during dispatch can achieve more efficient and close coordination in emergency rescue scenarios, maximizing the utilization of rescue resources. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for deploying rescue teams in a single-point emergency event that takes road condition information into consideration when an accident occurs at a construction site in a railway construction section and when multiple rescue entities participate in the deployment of emergency rescue teams, so as to solve at least one technical problem existing in the above-mentioned background technology.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions:

[0005] In one aspect, the present invention provides a method for deploying a rescue team in a single-point emergency event taking into account road condition information, comprising:

[0006] Obtain the needs of the disaster site, namely the existing rescue team resources, establish a collection of various rescue resources, build a rescue team dispatch plan, and update the rescue travel time according to road conditions;

[0007] Calculate the coordination score of the rescue team dispatch plan;

[0008] Establish an objective function that minimizes arrival time and ensures that rescue forces from all parties arrive at the same time as much as possible, establish constraints based on actual conditions, and build a rescue team deployment model;

[0009] The rescue team deployment model is solved based on the NSGA-II algorithm considering collaborative information, and the rescue team deployment plan is obtained.

[0010] Furthermore, a demand set of disaster-affected points, a set of various rescue resources, and updated rescue travel time are established; including: establishing a set of disaster-affected points, with the total number of disaster-affected points being 1; establishing a demand set of disaster-affected points, including the number of rescue teams equipped with large-scale rescue equipment required at the disaster-affected points, the number of rescue teams equipped with medium-sized rescue equipment required at the disaster-affected points, the number of professional tunnel rescue teams required at the disaster-affected points, the number of fire brigades required at the disaster-affected points, the number of doctors required at the disaster-affected points, the number of nurses required at the disaster-affected points, and the number of volunteers required at the disaster-affected points; establishing a set of the number of rescue points and rescue teams, including a set of rescue centers, a set of hospitals, a set of county governments, a set of professional tunnel rescue teams, a set of fire centers, and a set of rescue centers with medium-sized equipment rescue teams The number of rescue teams, the number of large-scale equipment rescue teams owned by the rescue center, the number of professional tunnel rescue teams, the number of fire brigades owned by the fire center, the number of doctors owned by the hospital, and the number of nurses owned by the hospital are established; other rescue resource sets are established, including the number of ambulances owned by the hospital and the total number of vehicles that the county government where the hospital is located can dispatch; a rescue team dispatch plan set is established, including the actual dispatch plan of the rescue equipment rescue team, the actual dispatch plan of the professional tunnel rescue equipment rescue team, the actual dispatch plan of the fire brigade, and the actual dispatch plan of the nurse; the road travel time is updated according to the disaster situation, including the construction of the travel time set t from the departure point to the disaster site when no accident occurs. A0 , including the time required for the three shortest paths from the starting point to the disaster site.

[0011] Furthermore, the coordination score of the rescue team dispatch plan is calculated, including:

[0012] Establish an external historical collaboration information set; obtain joint dispatch information of rescue centers and hospitals; calculate internal collaboration scores; calculate collaboration scores.

[0013] Furthermore, an objective function is established to minimize the arrival time and ensure that rescue forces from all parties arrive at the same time as much as possible, and constraints are established based on actual conditions, including: establishing an objective function for minimizing arrival time; calculating the time required for various rescue teams to arrive at the disaster site; establishing an objective function for minimizing the arrival time difference of rescue forces from all parties; establishing various constraints including constraints on the number of rescue teams, constraints on the number of dispatchable vehicles, constraints on the number of medical staff, and ensuring that there is at least one rescue team at each disaster site.

[0014] Furthermore, the rescue team deployment model is solved based on the NSGA-II algorithm considering collaborative information, including: chromosome encoding, using real number encoding to construct chromosomes representing the solution, treating a variable matrix as a substring of the chromosome as a whole; determining model parameters; initializing the population; crossover mutation to generate offspring; and elite selection strategy.

[0015] Furthermore, according to the initial conditions involved in the established rescue team deployment model based on target coordination; the algorithm parameters are population size, maximum iteration generation, gene pool size, crossover probability, crossover probability, number of variables, number of objective functions, the number of optimal individuals retained in elite selection, the number of optimal individuals randomly selected, and the number of external individuals introduced.

[0016] In a second aspect, the present invention provides a rescue team deployment system for a single-point emergency event taking into account road condition information, comprising:

[0017] The acquisition module is used to obtain the needs of the disaster site, namely the existing rescue team resources, establish a collection of various rescue resources, build a rescue team dispatch plan, and update the rescue travel time according to road conditions;

[0018] Collaboration information scoring module, used to calculate the collaboration score of the rescue team dispatch plan;

[0019] The construction module is used to establish the objective function of minimizing the arrival time and ensuring that rescue forces from all parties arrive at the same time as much as possible, and to establish constraint conditions based on actual conditions to build a rescue team deployment model;

[0020] The solution module is used to solve the rescue team deployment model based on the NSGA-II algorithm considering collaborative information and obtain the rescue team deployment plan.

[0021] In a third aspect, the present invention provides a non-transitory computer-readable storage medium, which is used to store computer instructions. When the computer instructions are executed by a processor, the rescue team deployment method under a single-point emergency event considering road condition information as described above is implemented.

[0022] In a fourth aspect, the present invention provides a computer device comprising a memory and a processor, wherein the processor and the memory communicate with each other, the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the rescue team deployment method for a single-point emergency event taking into account road condition information as described above.

[0023] In a fifth aspect, the present invention provides an electronic device comprising: a processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to execute instructions for implementing the rescue team deployment method under a single-point emergency event taking into account road condition information as described above.

[0024] The beneficial effects of the present invention are as follows: in view of the characteristics of limited emergency resources, urgent emergency rescue, and disasters affecting traffic, a model is constructed by considering road condition information during the rescue process and historical collaborative information between collaborative entities, which conforms to actual rescue scenarios and utilizes the cooperation advantages between different rescue teams and personnel, which is conducive to the efficient completion of emergency rescue tasks; an NSGA-II algorithm is designed to solve the target collaborative rescue team deployment model, and the collaborative score replaces the traditional congestion as the elite selection operator. While ensuring the optimal goal, a rescue team deployment plan with better collaborative effect is obtained.

[0025] Additional advantages of the present invention will be more clearly given in the following description or learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 This is a flow chart of the NSGA-II algorithm considering collaborative information according to an embodiment of the present invention.

[0028] Figure 2 This is a diagram of a chromosome encoding method in the NSGA-II algorithm considering collaborative information according to an embodiment of the present invention.

[0029] Figure 3 This is a diagram showing the actual meaning of the gene fragments within the substring described in an embodiment of the present invention.

[0030] Figure 4 This is a diagram of the crossover process in the NSGA-II algorithm considering collaborative information according to an embodiment of the present invention.

[0031] Figure 5 This is a diagram of the mutation process in the NSGA-II algorithm considering collaborative information according to an embodiment of the present invention.

[0032] Figure 6 This is the Pareto front graph of the external optimal solution set obtained in the embodiment of the present invention.

[0033] Figure 7 This is a comparison chart of the changes in the objective function value of the shortest arrival time in the optimal solutions of all generations described in an embodiment of the present invention and the changes in the objective function value of the shortest arrival time in the optimal solutions of all generations in the external optimal solution set.

[0034] Figure 8This is a comparison chart of the objective function value changes of ensuring that rescue forces from all parties arrive at the same time as much as possible in the optimal solutions of all generations described in the embodiments of the present invention and the objective function value changes of ensuring that rescue forces from all parties arrive at the same time as much as possible in the optimal solutions of all generations in the external optimal solution set.

[0035] Figure 9 This is a comparison chart of the changes in the collaborative scores of the optimal solutions of all generations described in an embodiment of the present invention and the changes in the collaborative scores of the optimal solutions of all generations in the external optimal solution set.

[0036] Figure 10 This figure shows the comparison results between the optimal solution obtained by the method of the embodiment of the present invention and the method using the traditional congestion degree as the selection operator.

[0037] Figure 11 This is a flow chart of a method for deploying rescue teams in a single-point emergency event taking into account road condition information according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention and are not to be construed as limiting the present invention.

[0039] Those skilled in the art will understand that unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this invention belongs.

[0040] It should also be understood that terms, such as those defined in commonly used dictionaries, should be understood to have a meaning consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless as defined herein.

[0041] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a," "an," "said," and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the stated features, integers, steps, operations, elements, and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, and / or groups thereof.

[0042] In the description of this specification, reference to the terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. In addition, those skilled in the art may combine and integrate different embodiments or examples described in this specification, as well as features of different embodiments or examples, unless otherwise inconsistent.

[0043] To facilitate understanding of the present invention, the present invention is further explained below with reference to specific embodiments in conjunction with the accompanying drawings. However, the specific embodiments do not constitute a limitation on the embodiments of the present invention.

[0044] Those skilled in the art should understand that the drawings are merely schematic diagrams of embodiments, and the components in the drawings are not necessarily necessary for implementing the present invention.

[0045] Example 1

[0046] like Figure 11 As shown, in this embodiment 1, a rescue team deployment system for a single-point emergency event taking into account road condition information is first provided, including: an acquisition module for acquiring the needs and rescue resources of the disaster-stricken point; a collaborative information scoring module for calculating the collaborative score of the rescue team dispatch plan; a construction module for establishing an objective function that minimizes the arrival time and ensures that the rescue forces of all parties arrive at the same time as much as possible, and establishes constraint conditions according to actual conditions to establish a rescue team deployment model; a solution module for solving the rescue team deployment model based on the NSGA-II algorithm taking into account collaborative information to obtain a rescue team dispatch plan.

[0047] In this embodiment 1, the method of establishing disaster site requirements, establishing various rescue resource sets, and updating rescue travel time includes the following steps:

[0048] Step 1. Establish a set of disaster-affected points:

[0049] I: set of disaster-affected points, the total number of disaster-affected points is 1;

[0050] Step 2. Establish a set of disaster-affected point requirements:

[0051] a L : The number of rescue teams equipped with large-scale rescue equipment required at the disaster site;

[0052] a M : The number of rescue teams equipped with medium-sized rescue equipment required at the disaster site;

[0053] a P: The number of professional tunnel rescue teams required at the disaster site;

[0054] a F : The number of fire brigades required at the disaster site;

[0055] b: the number of doctors required at the disaster site;

[0056] c: number of nurses required at the disaster site;

[0057] d: number of volunteers needed at the disaster site;

[0058] Step 3. Establish a set of rescue points and the number of rescue teams:

[0059] Rescue center gathering, where J i represents the i-th rescue center, n r is the total number of rescue centers;

[0060] Hospital collection, including Y k represents the kth hospital, n p is the total number of hospitals;

[0061] County government collection, including Z v represents the vth county government, n t is the total number of county governments;

[0062] Professional tunnel rescue team assembled, including P u represents the u-th professional tunnel rescue team, n z is the total number of professional tunnel rescue teams;

[0063] Fire center assembly, where F w represents the w-th fire center, n f is the total number of fire centers;

[0064] The rescue center has a collection of medium-sized rescue teams, including represents the number of medium-sized equipment rescue teams in the i-th rescue center;

[0065] The rescue center has a large number of rescue teams, including represents the number of large-scale equipment rescue teams in the i-th rescue center;

[0066] A collection of professional tunnel rescue teams, including represents the number of professional tunnel rescue teams at the location of the u-th professional tunnel rescue team, The fire protection center has a set of fire brigades, including represents the number of fire brigades in the w-th fire center;

[0067] The hospital has a set of doctors, among which represents the number of doctors in the k-th hospital;

[0068] The hospital has a set of nurses, of which represents the number of nurses in the k-th hospital.

[0069] Step 4. Create other rescue resource collections:

[0070] The hospital has a set of ambulances, of which represents the number of ambulances in the k-th hospital;

[0071] The total number of vehicles that the county government where the hospital is located can dispatch, including represents the number of vehicles that the county government of the county where the k-th hospital is located can dispatch;

[0072] Step 5. Create a rescue team dispatch plan set:

[0073] Rescue teams include rescue teams equipped with large-scale rescue equipment, rescue teams equipped with medium-sized rescue equipment, professional tunnel rescue teams, fire brigades, doctors, and nurses;

[0074] a′ L :Actual dispatch plan for large rescue equipment and rescue teams:

[0075]

[0076] in, It represents the number of rescue teams equipped with large rescue equipment sent by the i-th rescue center to the disaster site in the actual dispatch plan;

[0077] a′ M : Actual dispatch plan for rescue teams with medium-sized rescue equipment:

[0078]

[0079] in, It represents the number of rescue teams equipped with medium-sized rescue equipment sent by the i-th rescue center to the disaster site in the actual dispatch plan;

[0080] a′ P : Actual dispatch plan for professional tunnel rescue equipment rescue team:

[0081]

[0082] in, It represents the number of professional tunnel rescue teams dispatched to the disaster site from the location of the u-th professional tunnel rescue team in the actual dispatch plan;

[0083] a′ F : Actual dispatch plan of the fire brigade:

[0084]

[0085] Among them, a′ F represents the number of fire brigades dispatched by the w-th fire center to the disaster site in the actual dispatch plan;

[0086] b′: Actual doctor dispatch plan:

[0087]

[0088] Among them, b′ k represents the number of doctors dispatched by the kth hospital to the disaster site in the actual dispatch plan;

[0089] c′: Actual nurse dispatch plan:

[0090]

[0091] Among them, c′ k represents the number of nurses dispatched by the kth hospital to the disaster site in the actual dispatch plan;

[0092] Step 6. Update road travel times based on the disaster situation:

[0093] Construct the required travel time set t from the departure point to the disaster site when no accident occurs A0 , including the time required for the three shortest paths from the starting point to the disaster site:

[0094]

[0095] in, represents the time required to travel from point a to the disaster site via the three shortest paths, A represents different locations. When A=1, it represents a rescue center; when A=2, it represents a hospital; when A=3, it represents a county government; and when A=4, it represents a fire department.

[0096] After the accident, the path is damaged and the travel time is t′ A , t′ A There are four situations:

[0097]

[0098] Among them, λ represents the degree of congestion, l is the coefficient of influence of road congestion on transportation time, t 管 is the coefficient of influence of traffic control on road travel time;

[0099] Obtain the travel time set t′ to the disaster site under the condition of path damage A0 as follows:

[0100]

[0101] The shortest time set t′ to reach the disaster site is thus established A :

[0102]

[0103] in, It represents the shortest time from the a-th rescue point to the disaster site under the condition of path damage.

[0104] In this embodiment 1, the coordination score of the rescue team dispatch plan is calculated by using historical coordination information and the actual dispatch plan of the rescue team to obtain the coordination score of the current dispatch plan, including the following:

[0105] Step 1. Establish external historical collaborative information collection:

[0106] Construct the historical drill count set E of the rescue center and the hospital:

[0107]

[0108] Among them, E ik represents the number of historical drills between the i-th rescue center and the k-th hospital;

[0109] Step 2. Obtain joint dispatch information from the rescue center and hospital:

[0110] Construct rescue center dispatch decision variable α r :

[0111]

[0112] in, represents the decision variable of the i-th rescue center to dispatch a rescue team to the disaster site;

[0113] Construct hospital dispatch decision variables:

[0114]

[0115] in, represents the decision variable of the kth hospital to send doctors or nurses to the disaster site;

[0116] Construct a joint dispatch information collection between rescue centers and hospitals:

[0117]

[0118] in, represents the joint dispatch information of the i-th rescue center and the k-th hospital, num2() represents the number of 2s in the calculation matrix; α r (i) represents α r The i-th row is the dispatch information of the i-th rescue center to the disaster site; α pw (k) represents α pw The kth row is the dispatch information of the kth hospital to the disaster site;

[0119] Step 3. Calculate the external collaboration score:

[0120] Construct external collaborative information set H:

[0121]

[0122] Among them, H ik represents the collaborative information between the i-th rescue center and the k-th hospital;

[0123] Calculate the external collaboration score w :

[0124]

[0125] Step 4. Obtain the joint dispatch information of doctors and nurses within the hospital:

[0126] Construct the decision variable α for the joint dispatch of doctors and nurses within the hospital pn :

[0127]

[0128] in, represents the decision variable of the kth hospital sending doctors and nurses to the disaster site at the same time, that is, the information of joint dispatch of doctors and nurses;

[0129] Step 5. Calculate the internal collaboration score:

[0130] Calculate the internal collaboration score n :

[0131]

[0132] Step 6. Calculate the collaboration score:

[0133] score=ω1*score w+ω2*score n

[0134] Among them, score represents the total coordination score of the rescue personnel dispatch, ω1 represents the weight of external coordination information, and ω2 represents the weight of internal coordination information.

[0135] In this embodiment, an objective function and constraints are established to minimize the arrival time and ensure that rescue forces from all parties arrive at the same time as much as possible, including the following specific steps.

[0136] Step 1. Establish the shortest arrival time objective function:

[0137]

[0138] Among them, F1 represents the first objective function, that is, the shortest arrival time; t i represents the arrival time of various rescue teams, t1-t5 respectively represent the sum of the time required for the rescue team equipped with large rescue equipment, the rescue team equipped with medium rescue equipment, doctors and nurses, volunteers, fire brigade, and professional tunnel rescue team to arrive at the disaster site;

[0139] Step 2. Calculate the time required for various rescue teams to reach the disaster site:

[0140]

[0141]

[0142]

[0143] Among them, t1 represents the sum of the time required for the rescue team equipped with large rescue equipment and the rescue team equipped with medium rescue equipment to reach the disaster site; represents the shortest time required for the i-th rescue center to reach the disaster site under the condition of path damage; The decision variable representing whether the i-th rescue center sends a large equipment rescue team to the disaster site; The decision variable that indicates whether the i-th rescue center sends a large equipment rescue team to the disaster site.

[0144]

[0145]

[0146]

[0147]

[0148]

[0149] t2 represents the sum of the time required for doctors and nurses to reach the disaster site; represents the shortest time required for the kth hospital to reach the disaster site under the condition of path damage; β k is the decision variable for whether the kth hospital sends doctors to the disaster site; k is the decision variable for whether a hospital sends nurses to a disaster site; represents the time required to dispatch a vehicle to the kth hospital; δ k is the decision variable for whether to dispatch a vehicle from the nearby k-th hospital to the disaster site.

[0150] t3=min t″3

[0151]

[0152]

[0153] Where t3 represents the sum of the time required for volunteers to reach the disaster site; t″3 represents the total time required for volunteers from different counties to reach the disaster site; represents the total time required to send volunteers from the vth county to the disaster site; represents the shortest time required for volunteers to reach the disaster site from the vth county government; represents the volunteer assembly time in the vth county under disaster conditions; represents the volunteer assembly time of the vth county when no accident occurs; ζ(v) is the disaster impact coefficient of the vth county, which represents the degree of disaster impact on the vth county.

[0154]

[0155]

[0156] Among them, t4 represents the sum of the time required for the fire brigade to reach the disaster site; represents the shortest time from the wth fire center to the disaster site under the condition of path damage; The decision variable representing whether the w-th fire center sends a professional tunnel rescue team to the disaster site.

[0157]

[0158] Where t5 represents the total time required for the professional tunnel rescue team to reach the disaster site; represents the shortest time from the location of the u-th professional tunnel rescue team to the disaster site under the condition of path damage; The decision variable representing whether the location of the u-th professional tunnel rescue team sends a professional tunnel rescue team to the disaster site;

[0159] Step 3. Establish the objective function of the minimum arrival time difference of the minimum rescue forces of all parties:

[0160]

[0161]

[0162]

[0163] Among them, F2 represents the third objective function, which is the minimum arrival time difference of the rescue forces of all parties; It means to find the variance of A, which includes the time required for the rescue team to arrive at the disaster site, the time required for doctors and nurses to arrive at the disaster site, the time required for volunteers to arrive at the disaster site, the time required for the fire brigade to arrive at the disaster site, and the time required for the professional tunnel rescue team to arrive at the disaster site. Indicates the time required for doctors and nurses to reach the disaster site.

[0164] Step 4. Establish various constraints:

[0165] Establish constraints, including the number of rescue teams, the number of dispatchable vehicles, the number of medical personnel, and the requirement that each disaster site has at least one rescue team;

[0166] Construct the number of rescue teams:

[0167]

[0168]

[0169]

[0170]

[0171] in, represents the total number of rescue teams with large rescue equipment and the number of rescue teams with medium rescue equipment actually dispatched by the i-th rescue center; represents the number of professional tunnel rescue teams actually dispatched at the location of the u-th professional tunnel rescue team; represents the number of fire brigades actually dispatched by the w-th fire center;

[0172] Construct dispatchable vehicle constraints, including:

[0173] Construct the matrix D of the number of trains required to be shunted:

[0174]

[0175] Among them, D k represents the number of vehicles that the k-th hospital needs to dispatch when sending doctors or nurses to the disaster site; represents the total number of doctors and nurses who need to take government-dispatched vehicles to the disaster site, and 4 represents the number of people a vehicle can carry in addition to the driver;

[0176] Construct dispatchable vehicle constraints:

[0177]

[0178] Among them, D k Indicates the total number of shunting vehicles required for a hospital;

[0179] Constructing constraints on the number of medical staff:

[0180]

[0181]

[0182] Where b′ k represents the number of doctors sent by the kth hospital; c′ k represents the number of nurses sent by the k-th hospital;

[0183] Construct the constraint that each disaster site must have at least one rescue team:

[0184]

[0185] It means that the number of medium-sized rescue teams actually received by each disaster-stricken site is at least 1.

[0186] In this embodiment 1, an NSGA-II algorithm that takes collaborative information into consideration is designed to solve the established rescue team deployment model, and a rescue team deployment plan with better collaborative effect is obtained under the optimal goal.

[0187] The algorithm flow is as follows Figure 1 shown.

[0188] Step 1: Chromosome encoding

[0189] Use real number coding to construct chromosomes representing solutions, and treat a variable matrix as a substring of the chromosome. Each chromosome consists of 6 substrings, representing the medium-sized rescue team dispatch plan, large-scale rescue team dispatch plan, professional tunnel rescue team dispatch plan, fire brigade dispatch plan, doctor dispatch plan, and nurse dispatch plan, respectively. Figure 2 Taking the medium-sized rescue team dispatch plan as an example, the actual meaning of the gene fragment in its substring is as follows Figure 3 shown.

[0190] Step 2: Determine model parameters

[0191] Model parameters: The initial conditions involved in the established rescue team deployment model based on target coordination are as follows: aM 、a L 、a P 、a F , b, c, R M 、R L 、R P 、R F , b0, c0, T′ c 、n c ,E,t 10 , t 20 , t 30 , t 40 , t′ g , t d wait.

[0192] Algorithm parameters: population size pop, maximum iteration number gen_max, gene pool size pool, crossover probability pc, crossover probability pm, number of variables x_num, number of objective functions f_num, number of optimal individuals retained in elite selection pop_choose, number of optimal individuals randomly selected pop_random, number of external individuals introduced pop_new.

[0193] Step 3: Initialize the population

[0194] Step 3.1: The variables involved in the model are in matrix form, and the chromosomes representing the solutions are encoded using real numbers. Based on the constraints, the needs of the disaster-stricken points in the model, and the principle of dispatching as many rescue teams as possible, pool solutions that meet the conditions are randomly generated for each x_num variable to form the gene pool of each substring.

[0195] Step 3.2: For a chromosome, each substring is randomly selected from its corresponding gene pool. Pop chromosomes are randomly generated to form the parent population chromo. The generation number gen = 1.

[0196] Step 3.3 Calculate the objective function values ​​corresponding to pop solutions.

[0197] Step 3.4 performs a fast non-dominated sort on the initial parent population and divides the population into different Pareto levels pareto_rank.

[0198] Step 3.5: For each pareto_rank, calculate the synergy score of each solution within the rank and sort them from high to low according to the synergy score.

[0199] Step 3.6 Add the individuals with pareto_rank of 1 in the current population and their objective function, pareto_rank, and collaboration score to the external optimal solution set BEST_CHROMO; add the individuals with the highest collaboration score among the individuals with pareto_rank of 1 in the current population to the optimal solution set RESULT.

[0200] Step 4: Crossover mutation to generate offspring

[0201] Step 4.1 Randomly select two individuals from the parent population chromo, namely parent_1 and parent_2, and the number of crossover mutations cm_num = 1.

[0202] Step 4.2 Crossover to obtain offspring off_1′ and off_2′: Randomly generate the current crossover probability pc_n. If pc_n ≥ pc, no crossover is performed, and offspring off_1′ = parent_1 and off_2′ = parent_2. If pc_n < pc, a crossover operation is performed: randomly select the substring position crosspoint in the chromosome, and swap the two chromosomes parent_1 and parent_2 from crosspoint+1 to the last substring position. The two chromosomes after crossover are the two offspring off_1′ and off_2′. The crossover process is as follows: Figure 4 As shown:

[0203] Step 4.3 Mutation to obtain offspring off_1″ and off_2″: Generate the current mutation probabilities pm_n1 and pm_n2 for off_1′ and off_2′ obtained in the previous step respectively. If pm_n1 ≥ pm, no mutation is performed, and the offspring off_1″ = off_1′ and off_2″ = off_2′; if pm_n1 < pm, mutation is performed on off_1′: randomly select the substring position mutatepoint in the chromosome, and randomly select a substring from the gene library of the substring to exchange with it to obtain the offspring off_1″; the same is true for off_2′. The mutation process is as follows Figure 5 shown.

[0204] Step 4.4: The number of crossover mutations cm_num = cm_num + 1. The obtained off_1″ and off_2″ are added to the offspring population chromo_off after calculating the objective function.

[0205] When step 4.5cm_num≤0.5*pop, repeat step 3.1-step 3.3.

[0206] Step 5: Elite selection strategy

[0207] Step 5.1: Merge the offspring population chromo_off with the parent population chromo to obtain chromo_combine.

[0208] Step 5.2 performs fast non-dominated sorting on chromo_combine to divide the population into different Pareto levels pareto_rank.

[0209] Step 5.3 For each pareto_rank, calculate the synergy score of each solution within the rank and sort them from high to low according to the synergy score.

[0210] Step 5.4: Add the optimal pop_choose individuals from chromo_combine after non-dominated sorting and synergy score sorting to the new population chromo_new. Randomly select pop_random individuals from chromo_combine and add them to chromo_new. Then, randomly select pop_new variables from each of the x_num gene pools to form pop_new externally introduced individuals and add them to chromo_new. pop_choose + pop_random + pop_new = pop. This results in a new population that has undergone both selection and introduction.

[0211] Step 5.5: Add the individuals with pareto_rank of 1 in the current population chromo_new and their objective function, pareto_rank, and synergy score to the external optimal solution set BEST_CHROMO; add the individuals with the highest synergy score among the individuals with pareto_rank of 1 in the current population chromo_new to the optimal solution set RESULT.

[0212] Step 5.6 Let chromo_new be the parent population of the next generation, that is, chromo = chromo_new, and generation number gen = gen + 1.

[0213] When Step 5.7gen<gen_max, repeat Step 3-Step 4.

[0214] Based on the actual example input, the optimal solutions of the external optimal solution set tend to converge after the maximum iteration number reaches 300. The Pareto frontier of the external optimal solution set is obtained as follows Figure 6 As shown in the figure, the changes in the objective function values ​​corresponding to the optimal solutions of all generations and the changes in the objective function values ​​of the optimal solutions of all generations in the external optimal solution set are shown in the figure. Figure 7 、 Figure 8 、 Figure 9As shown; Under the same parameter settings, the comparison results are as follows: Figure 10 As shown in the figure, compared with the traditional congestion selection operator, the objective function of ensuring the simultaneous arrival of rescue forces from all parties and the coordination score are improved by 7.4%, 4.9%, and 12.5%, respectively, verifying the effectiveness of the NSGA-II algorithm considering coordination information described in this embodiment.

[0215] Example 2

[0216] This embodiment 2 provides a non-transitory computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, the method for deploying a rescue team in a single-point emergency event taking into account road condition information is implemented as described above. The method includes:

[0217] Obtain the needs of the disaster site, namely the existing rescue team resources, establish a collection of various rescue resources, build a rescue team dispatch plan, and update the rescue travel time according to road conditions;

[0218] Calculate the coordination score of the rescue team dispatch plan;

[0219] Establish an objective function that minimizes arrival time and ensures that rescue forces from all parties arrive at the same time as much as possible, establish constraints based on actual conditions, and build a rescue team deployment model;

[0220] The rescue team deployment model is solved based on the NSGA-II algorithm considering collaborative information, and the rescue team deployment plan is obtained.

[0221] Example 3

[0222] This embodiment 3 provides a computer device including a memory and a processor, wherein the processor and the memory communicate with each other, the memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute a method for deploying a rescue team in a single-point emergency event taking into account road condition information. The method includes:

[0223] Obtain the needs of the disaster site, namely the existing rescue team resources, establish a collection of various rescue resources, build a rescue team dispatch plan, and update the rescue travel time according to road conditions;

[0224] Calculate the coordination score of the rescue team dispatch plan;

[0225] Establish an objective function that minimizes arrival time and ensures that rescue forces from all parties arrive at the same time as much as possible, establish constraints based on actual conditions, and build a rescue team deployment model;

[0226] The rescue team deployment model is solved based on the NSGA-II algorithm considering collaborative information, and the rescue team deployment plan is obtained.

[0227] Example 4

[0228] This embodiment 4 provides an electronic device, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory to cause the electronic device to execute instructions for implementing the above-mentioned method for deploying a rescue team in a single-point emergency event taking into account road condition information. The method includes:

[0229] Obtain the needs of the disaster site, namely the existing rescue team resources, establish a collection of various rescue resources, build a rescue team dispatch plan, and update the rescue travel time according to road conditions;

[0230] Calculate the coordination score of the rescue team dispatch plan;

[0231] Establish an objective function that minimizes arrival time and ensures that rescue forces from all parties arrive at the same time as much as possible, establish constraints based on actual conditions, and build a rescue team deployment model;

[0232] The rescue team deployment model is solved based on the NSGA-II algorithm considering collaborative information, and the rescue team deployment plan is obtained.

[0233] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0234] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0235] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0236] These computer program instructions can also be loaded onto a computer or other programmable data processing device, and a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide the functions for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0237] Although the above describes the specific embodiments of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solutions disclosed in the present invention without the need for creative work should be included in the scope of protection of the present invention.

Claims

1. A method for deploying rescue teams in a single-point emergency situation taking into account road condition information, characterized in that: include: Obtain the needs of the disaster site, namely the existing rescue team resources, establish a collection of various rescue resources, build a rescue team dispatch plan, and update the rescue travel time according to road conditions; Calculate the total coordination score of the rescue team dispatch plan; including: establishing an external historical coordination information set; obtaining the rescue center and hospital joint dispatch information; calculating the internal coordination score; calculating the coordination score; among which, establishing the external historical coordination information set is to construct a historical drill number set of the rescue center and the hospital; obtaining the rescue center and hospital joint dispatch information includes: constructing the rescue center dispatch decision variable, constructing the hospital dispatch decision variable, and constructing the rescue center and hospital joint dispatch information set; external coordination score score w for: Among them, H ik represents the collaborative information between the i-th rescue center and the k-th hospital, n r is the total number of rescue centers, n p is the total number of hospitals; The information of joint dispatch of doctors and nurses within the hospital is obtained as follows: constructing decision variables for joint dispatch of doctors and nurses within the hospital; Internal collaboration score n for: in, represents the decision variable of the kth hospital sending doctors and nurses to the disaster site at the same time, that is, the information of joint dispatch of doctors and nurses; The total synergy score is: score=μ1*score w +ω2*score n Among them, score represents the total coordination score of the rescue personnel dispatch, ω1 represents the weight of external coordination information; ω2 represents the weight of internal coordination information; Establish an objective function that minimizes arrival time and ensures that rescue forces from all parties arrive at the same time as much as possible, establish constraints based on actual conditions, and build a rescue team deployment model; The rescue team deployment model is solved based on the NSGA-II algorithm considering collaborative information, and the rescue team deployment plan is obtained.

2. The method for deploying rescue teams in a single-point emergency situation taking into account road condition information according to claim 1, characterized in that: Establish a set of disaster-affected point needs, a set of various rescue resources, and update the rescue passage time; including: establishing a set of disaster-affected points, with the total number of disaster-affected points being 1; establishing a set of disaster-affected point needs, including the number of rescue teams equipped with large-scale rescue equipment required at the disaster-affected points, the number of rescue teams equipped with medium-sized rescue equipment required at the disaster-affected points, the number of professional tunnel rescue teams required at the disaster-affected points, the number of fire brigades required at the disaster-affected points, the number of doctors required at the disaster-affected points, the number of nurses required at the disaster-affected points, and the number of volunteers required at the disaster-affected points; establishing a set of the number of rescue points and rescue teams, including a set of rescue centers, a set of hospitals, a set of county governments, a set of professional tunnel rescue teams, a set of fire centers, and a set of the number of rescue teams equipped with medium-sized equipment at the rescue centers The number of rescue teams with large equipment owned by the rescue center, the number of professional tunnel rescue teams, the number of fire brigades owned by the fire center, the number of doctors owned by the hospital, and the number of nurses owned by the hospital are established; other rescue resource sets are established, including the number of ambulances owned by the hospital and the total number of vehicles that the county government where the hospital is located can dispatch; a rescue team dispatch plan set is established, including the actual dispatch plan of the rescue equipment rescue team, the actual dispatch plan of the professional tunnel rescue equipment rescue team, the actual dispatch plan of the fire brigade, and the actual dispatch plan of the nurse; the road travel time is updated according to the disaster situation, including the construction of the travel time set t from the departure point to the disaster site when no accident occurs. A0 , including the time required for the three shortest paths from the starting point to the disaster site.

3. The method for deploying rescue teams in a single-point emergency situation taking into account road condition information according to claim 1, characterized in that: Establish an objective function to minimize arrival time and ensure that rescue forces from all parties arrive at the same time as much as possible, and establish constraints based on actual conditions, including: establishing an objective function to minimize arrival time; calculating the time required for various rescue teams to arrive at the disaster site; establishing an objective function to minimize the arrival time difference of rescue forces from all parties; establishing various constraints including constraints on the number of rescue teams, constraints on the number of dispatchable vehicles, constraints on the number of medical staff, and ensuring that there is at least one rescue team at each disaster site.

4. The method for deploying rescue teams in a single-point emergency situation taking into account road condition information according to claim 1, characterized in that: The rescue team deployment model is solved based on the NSGA-II algorithm considering collaborative information, including: chromosome encoding, using real number encoding to construct chromosomes representing the solution, treating a variable matrix as a substring of the chromosome as a whole; determining model parameters; initializing the population; crossover mutation to generate offspring; and elite selection strategy.

5. The method for deploying rescue teams in a single-point emergency situation taking into account road condition information according to claim 4, characterized in that: According to the initial conditions involved in the established rescue team deployment model based on target coordination; the algorithm parameters are population size, maximum iteration generation, gene pool size, crossover probability, crossover probability, number of variables, number of objective functions, the number of optimal individuals retained in elite selection, the number of optimal individuals randomly selected, and the number of external individuals introduced.

6. A rescue team deployment system for single-point emergencies taking into account road condition information, characterized in that: include: The acquisition module is used to obtain the needs of the disaster site, namely the existing rescue team resources, establish a collection of various rescue resources, build a rescue team dispatch plan, and update the rescue travel time according to road conditions; The collaborative information scoring module is used to calculate the collaborative score of the rescue team dispatch plan; including: establishing an external historical collaborative information set; obtaining the rescue center and hospital joint dispatch information; calculating the internal collaborative score; calculating the collaborative score; among which, establishing the external historical collaborative information set is to construct a historical drill number set of the rescue center and the hospital; obtaining the rescue center and hospital joint dispatch information includes: constructing the rescue center dispatch decision variable, constructing the hospital dispatch decision variable, and constructing the rescue center and hospital joint dispatch information set; external collaborative score score w for: Among them, H ik represents the collaborative information between the i-th rescue center and the k-th hospital, n r is the total number of rescue centers, n p is the total number of hospitals; The information of joint dispatch of doctors and nurses within the hospital is obtained as follows: constructing decision variables for joint dispatch of doctors and nurses within the hospital; Internal collaboration score n for: in, represents the decision variable of the kth hospital sending doctors and nurses to the disaster site at the same time, that is, the information of joint dispatch of doctors and nurses; The total synergy score is: score=ω1*score w +ω2*score n Among them, score represents the total coordination score of the rescue personnel dispatch, ω1 represents the weight of external coordination information; ω2 represents the weight of internal coordination information; The construction module is used to establish the objective function of minimizing the arrival time and ensuring that rescue forces from all parties arrive at the same time as much as possible, and to establish constraint conditions based on actual conditions to build a rescue team deployment model; The solution module is used to solve the rescue team deployment model based on the NSGA-II algorithm considering collaborative information and obtain the rescue team deployment plan.

7. A non-transitory computer-readable storage medium, characterized in that The non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by the processor, the method for deploying a rescue team in a single-point emergency event considering road condition information as described in any one of claims 1 to 5 is implemented.

8. A computer device, characterized in that: It includes a memory and a processor, the processor and the memory communicate with each other, the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the rescue team deployment method under single-point emergency events considering road condition information as described in any one of claims 1-5.

9. An electronic device, characterized in that: include: A processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to execute instructions for implementing the method for deploying a rescue team in a single-point emergency event taking into account road condition information as described in any one of claims 1-5.

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