An emergency rescue resource scheduling dynamic programming method for post-disaster wounded evacuation

Abstract

The application discloses an emergency rescue resource scheduling dynamic programming method for post-disaster wounded evacuation, and particularly relates to the technical field of emergency rescue, which is based on a preset disaster area rescue environment, and introduces a deprivation cost to divide a wounded evacuation and rescue process into multiple stages to calculate the deprivation cost of each stage, including the deprivation cost of seriously wounded, the total deprivation cost of each wounded, and the total deprivation cost of all wounded, by setting a tent and service constraint, maintaining wounded flow and conservation, ambulance scheduling constraint, un-treated wounded and hospital treatment, and setting a decision variable type; and obtains a target function, that is, minimizes the total cost of the whole emergency rescue, by combining the total deprivation cost of all wounded with the moving cost of a medical rescue tent, the transportation cost of an ambulance, and the punishment cost of un-treated wounded.

Description

Technical Field

[0001] This invention relates to the field of emergency rescue technology, specifically to a dynamic planning method for emergency rescue resource scheduling for the evacuation of injured people after a disaster. Background Technology

[0002] Following natural disasters, the destructive power of these events often results in severe casualties and devastating economic losses in affected areas. In disaster zones, relief supplies are consistently insufficient to meet all needs. The core objective of emergency medical rescue is rapid response, providing timely medical assistance to the injured to minimize casualties and property damage. However, due to the destruction of infrastructure and road closures, direct access to the disaster area for evacuation and rescue becomes extremely difficult. Therefore, setting up medical rescue tents on the periphery of the disaster area not only effectively gathers the injured, preventing them from being threatened by secondary disasters, but also, through scientific site selection and the use of mobile medical rescue tents, enables dynamic, multi-stage evacuation and rescue of the injured, thus becoming a practical and effective rescue strategy. The entire evacuation route for the injured is 'disaster site – medical rescue tent – ​​hospital'. However, due to the shortage of medical resources, the injured may not receive immediate medical treatment, potentially leading to further deterioration of their injuries. Summary of the Invention

[0003] Therefore, this invention provides a dynamic planning method for emergency rescue resource scheduling for post-disaster casualty evacuation, in order to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a dynamic programming method for emergency rescue resource scheduling for post-disaster casualty evacuation. Based on a pre-defined disaster area rescue environment, the method introduces deprivation costs by considering constraints on the setup and service of medical rescue tents, maintaining casualty flow and conservation, ambulance scheduling constraints, untreated casualties and hospital treatment, and defining decision variable types. This divides the casualty evacuation and rescue process into multiple stages, calculating the deprivation cost for each stage, including the deprivation cost for seriously injured individuals, the total deprivation cost for each casualty, and the total deprivation cost for all casualties. The total deprivation cost for all casualties, combined with the movement cost of medical rescue tents, the transportation cost of ambulances, and the penalty cost for untreated casualties, yields the objective function, which minimizes the total emergency rescue cost.

[0005] Preferred, pre-defined rescue environments include:

[0006] (1) The arrival of wounded patients in the hospital follows a Poisson distribution; it is assumed to be an M / M / 1 single-channel service system, that is, all medical staff are treated as a whole and the existence of multiple service stations in the actual environment is ignored;

[0007] (2) During the evacuation process, it is assumed that the wounded will not die due to the evacuation process itself. In the modeling process, only the deprivation cost of the wounded is considered.

[0008] (3) Assume that all ambulances are homogeneous and their speeds remain constant;

[0009] (4) Assume that the number of seriously injured or killed people in the disaster area is known;

[0010] (5) Assume that the ambulance returns to its affiliated hospital after completing the rescue mission.

[0011] Preferably, the probability density function of the deprivation cost of seriously injured patients is defined as follows:

[0012] ;

[0013] Time set ;

[0014] : The coefficient of the deprivation cost function;

[0015] Disaster area To the medical relief tent The walking time of the wounded;

[0016] This indicates that the wounded are being transferred from the medical relief tent. To the hospital The delivery time;

[0017] The injured are in the hospital. Average waiting time;

[0018] Disaster site assembly, ;

[0019] Collection of alternative locations for medical relief tents ;

[0020] Existing hospitals (collection) ;

[0021] S∆ABC is the formula for the area of ​​the linearly descending region. Its mathematical meaning is to + During this period, the injured person's condition stabilized due to basic emergency treatment received during ambulance transport, and the deprivation cost of the injured person decreased linearly to 0.

[0022] Preferably, the total deprivation cost per wounded soldier is as follows:

[0023] .

[0024] Preferred total deprivation cost for all wounded:

[0025] ;

[0026] : Always from the disaster point To the medical relief tent The number of seriously injured;

[0027] : From the medical relief tent Arrive at the hospital The number of seriously injured.

[0028] Ideally, minimize the total cost of the entire emergency response. for:

[0029] ;

[0030] Collection of alternative locations for medical relief tents ;

[0031] Medical relief tents from The unit movement cost of moving point j to point j;

[0032] Medical relief tents from Move the point to Distance between points;

[0033] :if Momentary medical rescue tents from Move the point to If the value is 1, then =1; otherwise =0.

[0034] : The unit time transportation cost of ambulances;

[0035] : From the hospital To the medical relief tent The number of ambulances;

[0036] Disaster area The number of seriously injured people who have not been rescued;

[0037] Disaster area The penalty coefficient for wounded personnel not receiving medical treatment;

[0038] : Momentary Medical Rescue Tent The number of wounded who did not receive treatment;

[0039] Medical rescue tent The penalty coefficient for wounded soldiers who do not receive medical treatment;

[0040] The cost of moving medical relief tents;

[0041] The cost of ambulance transportation;

[0042] The punitive cost of not providing medical treatment to the wounded.

[0043] Preferably, tent setup and service constraints include:

[0044] This indicates that at any given time t, any medical tent candidate point j can have at most one medical rescue tent;

[0045] The location and status of the medical relief tent at the initial moment;

[0046] To restrict the movement of medical relief tents;

[0047] This indicates that for any disaster site i, there is at least one alternative medical relief tent j serving it;

[0048] This indicates that only if the alternative point j has a medical relief tent can it serve the disaster site i;

[0049] This indicates the capacity constraints of the medical relief tent;

[0050] The number of injured at disaster site i is conserved;

[0051] The initial location status of the ambulances at each hospital is given;

[0052] The state and location of the ambulance at any time t are given;

[0053] This indicates that ambulances will only be assigned to point j if a medical aid tent is available at that point;

[0054] The capacity constraints of existing hospitals;

[0055] This indicates that the total capacity of the ambulances dispatched to medical relief tent point j is sufficient to meet the vehicle capacity required by the injured at that point.

[0056] This indicates that the number of wounded individuals who have not received treatment at point j of the medical rescue tent at the initial moment is 0.

[0057] This represents the conservation of the number of untreated wounded at point j of the medical relief tent;

[0058] This represents the arrival rate of wounded patients at any hospital h at any time t;

[0059] This represents the maximum processing capacity of hospital h;

[0060] Let t be the waiting time of the wounded in any hospital at any time; The average waiting time for hospitalized wounded patients;

[0061] and The definition of decision variable types is given.

[0062] The present invention has the following advantages:

[0063] This invention comprehensively considers various factors such as casualty evacuation, facility site selection, medical service allocation, and emergency resource dispatch. It also effectively improves the efficiency of casualty evacuation by taking into account the cost of depriving casualties, in order to provide more comprehensive and accurate auxiliary decision support for relevant decision-makers.

[0064] The method proposed in this invention performs sensitivity analysis on key parameters, revealing the direct impact of the number of medical rescue tents on rescue costs and efficiency: increasing the number of medical rescue tents can significantly reduce rescue costs, but when the number exceeds a certain level, the marginal benefit of cost reduction gradually weakens. Compared with existing technologies, this finding provides an important reference for emergency management decision-makers to optimize the allocation of medical rescue resources. Attached Figure Description

[0065] Figure 1 This is a schematic diagram of an emergency rescue network provided by the present invention;

[0066] Figure 2 The three-stage preemption cost function image provided by this invention;

[0067] Figure 3The experimental network diagram provided for this invention;

[0068] Figure 4 The present invention provides a trend chart of the number of injured persons at various disaster sites.

[0069] Figure 5 The disaster relief-medical rescue tent service allocation diagram provided by this invention;

[0070] Figure 6 A diagram illustrating the site selection and relocation process of the medical rescue tent provided by this invention;

[0071] Figure 7 The medical rescue tent provided by this invention – existing hospital decision-making outcome service allocation diagram;

[0072] Figure 8 The present invention provides a trend chart of the number of ambulances in each hospital;

[0073] Figure 9 This is a schematic diagram illustrating the arrival of wounded patients in each hospital, as provided by the present invention.

[0074] Figure 10 A schematic diagram illustrating the impact of the number of available medical rescue tents provided by this invention on the cost of each component of the system;

[0075] Figure 11 This is a schematic diagram illustrating the impact of the number of available medical rescue tents on tent movement, as provided by the present invention. Detailed Implementation

[0076] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0077] This embodiment, based on the technical solution of the present invention, takes the actual road network of a certain year's earthquake as the research object and conducts numerical experiments. The experiments are solved using GAMS 23.9.1 software. Given the strong nonlinearity in the proposed objective function, the Snopt nonlinear solver is used for optimization. All numerical experiments are conducted on a mobile workstation equipped with an i5-11320H CPU, 3.20GHz frequency, and 16MB of RAM.

[0078] This embodiment establishes a three-tiered emergency rescue network consisting of the disaster site, backup medical rescue tent sites, and existing hospitals. Following this catastrophic earthquake, the disaster site... There have been numerous casualties. Due to road closures near the disaster area, medical relief tents have been set up inside or on the edge of the disaster zone to facilitate the rapid transfer of the injured to safe areas awaiting further evacuation. Emergency casualties at the disaster site are being transferred by rescue personnel to designated backup medical relief tent locations. The injured were then transported by ambulance to the existing hospital. Due to the scarcity of rescue resources, after completing the rescue mission at one disaster site, medical rescue tents can be moved from one disaster site to another to complete evacuation and rescue operations at different rescue points at multiple times. The entire rescue cycle consists of T discrete cycles. An emergency rescue network diagram is shown below. Figure 1 As shown.

[0079] In this experiment, this embodiment selected a road network containing 38 nodes from the earthquake as the research object. For example... Figure 3 As shown, the road network covers 15 disaster sites, 18 alternative locations for medical relief tents, and 5 existing hospitals. These nodes are interconnected, forming a complete experimental road network. The latitude and longitude data of each node were obtained through a free map navigation service application, and the distances between nodes were calculated using the Euclidean distance formula.

[0080] In the experiment, it was assumed that each existing hospital could provide 200 ambulances, each ambulance could carry two seriously injured patients, and the unit usage cost was 50 yuan / hour; 7 medical tents could be obtained, each medical rescue tent could accommodate 900 seriously injured patients, and its unit movement cost was 100 yuan / km; each hospital could accommodate 1500 seriously injured patients; in terms of penalty coefficient, the penalty coefficient for patients at disaster point i not being treated was 300, that is, the penalty coefficient for patients at medical rescue tent rescue point j not being treated was 300, and the deprivation cost coefficient for seriously injured patients was as shown in Table 1;

[0081] This experiment focuses on the additional suffering, psychological trauma, and physical impairment incurred by injured personnel during evacuation while awaiting rescue. To more accurately quantify these costs, the experiment divides the evacuation and rescue time into three stages and introduces a three-stage deprivation cost function to calculate the deprivation cost for each stage. Figure 2 It can be seen that, for seriously injured individuals, the cost of deprivation of medical services increases exponentially with the duration of deprivation as they travel from the disaster area to the designated medical aid tent. During ambulance transport, the injured receive basic emergency treatment, and their condition stabilizes somewhat, so the cost of deprivation decreases linearly. Upon arrival at the hospital, due to limited doctors and medical resources, the injured do not receive immediate treatment. Therefore, as the waiting time increases, the cost of deprivation experiences another, slightly slower, exponential increase, ceasing only when they finally receive medical treatment.

[0082] Table 1. Deprivation Cost Coefficient

[0083] Given the complexity of post-disaster emergency rescue, the number of seriously injured people at disaster sites and the number of medical staff in hospitals are difficult to determine. Therefore, it is assumed that the number of seriously injured people at each disaster site follows a random distribution of [200, 350] and the number of medical staff follows a random distribution of [600, 800].

[0084] The entire rescue cycle is set at 30 hours. To facilitate calculation, the entire rescue cycle is discretized, with each unit of time being 1 hour. , .

[0085] The solution results are shown in Table 2. The total cost of the system is... Yuan, of which the cost of depriving the wounded is as high as Yuan. Considering minimizing the cost of depriving the wounded, during the evacuation process, due to limited medical resources, some wounded could not be transported to hospitals for treatment in a timely manner. The longer the wounded endure pain, the higher the deprivation cost. Furthermore, a small number of wounded could not be transported to hospitals for treatment due to resource constraints; these untreated wounded were assigned a penalty value in the objective function. The corresponding penalty cost is... Yuan.

[0086] Table 2 Calculation results under the experimental road network

[0087] pass Figure 4 It can be seen that all the injured at the disaster sites were evacuated within 5 hours. This result shows that despite limited resources, the method performed well in the rational allocation of medical resources and was able to complete the evacuation of the injured in a relatively short period of time.

[0088] The cost of moving a medical relief tent is Yuan. Figure 5 The study clearly demonstrates the site selection results for medical relief tents in this example, as well as the service allocation relationships between these tents, disaster sites, and hospitals. Based on the decision analysis, the optimal site locations for the medical relief tents are nodes 3, 9, 13, 20, 24, 28, 30, 32, 37, and 36. However, since only 6 medical relief tents are available, the initial site locations for the tents are nodes 3, 9, 13, 20, 24, and 37. Each disaster site is provided with at least one medical relief tent to meet the evacuation requirements of the injured. Figure 5 It is clear that rescue services are allocated based on proximity to meet the evacuation requirements of the injured.

[0089] For example, disaster site 10 receives relief services from medical relief tent nodes 13, 20, and 24. Disaster site 8, however, receives services solely from medical relief tent node 9. The movement of the medical relief tents is as follows: Figure 6 As shown, in At that time, medical relief tent node 13 moved to node 30, and... Arrive at the time; At that time, node 3 moves to node 28, node 20 moves to node 32, and node 37 moves to node 36. All of these are within the specified timeframes. or Arrive at the target node in time.

[0090] Table 3 details the distribution of injured people among medical relief tents at the disaster site. For example, in At that time, 153 injured people from disaster site 1 were evacuated to medical relief tent node 3; At that time, 34 injured people arrived at the medical relief tent at point 9; At that time, 108 injured people arrived at the location. Due to the movement of medical relief tents, the evacuation routes for the injured would also change accordingly. For example, the injured at disaster site 33... and The injured at disaster site 33 were evacuated to medical relief tent node 37. After node 37 moved to node 36, the injured at disaster site 33 were evacuated to node 36. The evacuation of injured between disaster sites and medical relief tents incurs deprivation costs, which are proportional to the evacuation time.

[0091] Table 3. Changes in the number of injured at each disaster site at each time point.

[0092] pass Figure 7 It can be seen that each hospital has at least two medical rescue tents providing services. Since the waiting time for the injured within the medical rescue tents is difficult to estimate accurately, it is neglected in the experiment. During ambulance transfer, the injured receive basic treatment, and their deprivation costs decrease linearly with transport time. Therefore, corresponding deprivation and transport costs are incurred during the transport of the injured.

[0093] The rate at which injured people arrive at hospitals is closely related to the number of ambulances. Figure 8 and Figure 9 This data shows changes in the number of ambulances at five hospitals and the arrival status of injured persons within those hospitals. Because each ambulance has a different allocation and travel time, their return times to the hospital also vary. Taking Hospital 18 as an example... Figure 8 As shown, in At that time, the hospital dispatched a total of 170 ambulances to the disaster area for rescue operations. After the corresponding travel time, such as Figure 9 As shown, in At that time, the hospital received 200 injured people. After returning to the hospital, the ambulances were dispatched again for rescue missions. At that time, all 200 ambulances from the hospital were dispatched to the disaster area. Subsequently... At that time, another 282 injured people arrived at the hospital; At that time, the hospital dispatched another 200 ambulances; upon arrival... At that time, another 220 wounded arrived at Hospital 18. Hospital 18 was... The last time 200 ambulances were dispatched, and... and At that time, 228 and 198 injured people arrived at Hospital 18 respectively, after which Hospital 18 did not admit any more injured people. Upon arrival, due to the limited number of medical personnel, some injured people could not receive immediate medical treatment, resulting in a waiting time between arrival and treatment. The longer the waiting time, the greater the deprivation cost for the injured. Deprivation cost is an important indicator for measuring the suffering and losses suffered by injured people while waiting for rescue and treatment. In actual rescue operations, timely response and efficient allocation of medical resources are crucial to reducing the deprivation cost for the injured.

[0094] To evaluate the robustness of the method and the impact of key parameters on the optimal decision-making process, this experiment conducted sensitivity analyses on a series of important parameters. By systematically adjusting the values ​​of each parameter, we analyzed in depth the degree of influence of these parameters on the method's output. According to the experimental results, the number of available medical rescue tents was the most sensitive parameter to the method's results, therefore, this experiment analyzed it in detail. In the experiment, by fixing other parameters and only changing the number of medical rescue tents, we analyzed the sensitivity of this parameter to the objective function value. Specifically, this experiment set the total number of available medical rescue tents to 3, 6, 9, 12, 15, and 18 tents. Figure 10It can be seen that changes in the number of tents affect tent relocation costs, the penalty cost of untreated casualties, the cost of deprivation of casualties, and the total system cost. Tent relocation costs gradually decrease as the number of available tents increases, reaching zero when the number of medical rescue tents reaches 18. This is because when the number of medical rescue tents is relatively insufficient, their service coverage cannot fully encompass all disaster-stricken areas. In this case, it is necessary to move medical rescue tents to achieve multi-stage, dynamic rescue of the injured to ensure the comprehensiveness and effectiveness of the rescue work, thus incurring corresponding relocation costs. However, when the number of medical rescue tents is extremely sufficient to fully cover all disaster-stricken areas, there is no need to move or allocate tents, and the relocation cost naturally becomes zero. The penalty cost of untreated casualties decreases significantly when the number of tents increases from 3 to 6, and then remains stable. This indicates that when the number of medical rescue tents reaches 6, the treatment needs of the injured are basically met, and further increasing the number of tents has limited effect on reducing penalty costs. The trend of the cost of deprivation of casualties is consistent with that of the penalty costs. The total system cost decreased significantly when the number of tents increased from 3 to 6, after which the rate of decrease gradually slowed. This indicates that within a certain range, increasing the number of medical rescue tents can significantly reduce rescue costs, but beyond a certain number, the marginal benefit of cost reduction gradually diminishes.

[0095] The number of available medical rescue tents has a significant impact on tent mobility and rescue efficiency. For example... Figure 11 As shown, when the number of available medical rescue tents is 3, the overall rescue time is relatively long. This is because... At that time, tents were still being used for mobile rescue operations. However, when the number of tents increased to six or more, all tents were... The fact that the relocation was completed so quickly indicates that no further movement of the tents will be necessary during later stages of the rescue operation. Furthermore, as the number of available medical rescue tents increases, the coverage area of ​​the rescue zone also expands. In this scenario, the number of tents that need to be moved decreases accordingly. This is because more tents can cover a larger area simultaneously, thereby improving rescue efficiency and reducing the need for tent relocation.

[0096] This experiment, taking into account the actual post-disaster relief situation, focuses on efficiently providing medical assistance to the injured. It constructs a comprehensive optimization method for the evacuation of the injured and the allocation of medical resources, covering three key nodes: the disaster site, medical relief tents, and hospitals. Given the challenges posed by post-disaster conditions such as road closures and severe infrastructure damage, this experiment proposes a strategy of setting up medical relief tents on the edge of the disaster area. This not only effectively gathers the injured and prevents them from suffering secondary disasters, but also enables dynamic evacuation and rescue of the injured in multiple time periods through scientific site selection and the movement of medical relief tents. In constructing the method, the concept of emergency rescue is taken into full consideration, taking into account the potential for treatment delays due to limited resources. To protect the personal interests of the injured, the concept of deprivation cost is introduced to capture the human suffering caused by the lack of medical assistance. Based on this, a mixed-integer nonlinear method is established with the objective of minimizing the total system cost. This method achieves the effectiveness of the rescue plan while ensuring fairness, providing a scientific decision support framework for post-disaster medical relief.

[0097] To verify the effectiveness of the method, this experiment applied it to the actual road network scenario of this earthquake. Programming was performed using the GAMS platform, and the Snopt solver was used to solve the objective function, which exhibits strong nonlinearity. The optimization results clearly presented key decision variables such as the relocation of medical rescue tents, the evacuation of the injured, the dispatching of rescue vehicles, and the arrival of the injured at hospitals. The results strongly demonstrate the rationality and effectiveness of the proposed rescue plan. Further analysis revealed that under the technical solution of this invention, all injured at disaster sites could be evacuated within 5 hours, highlighting the high efficiency of the rescue plan. Furthermore, sensitivity analysis of important parameters in the method showed a direct impact of the number of medical rescue tents on rescue costs and efficiency: increasing the number of medical rescue tents significantly reduces rescue costs, but the marginal benefit of cost reduction gradually weakens after a certain number. This finding provides an important reference for emergency management decision-makers to optimize the allocation of medical rescue resources.

[0098] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A dynamic programming method for emergency rescue resource allocation for post-disaster casualty evacuation, characterized in that: Based on a pre-defined disaster relief environment, the method introduces deprivation costs by considering constraints on the setup and service of medical relief tents, maintaining the flow and conservation of the injured, constraints on ambulance dispatch, untreated injured and hospital treatment, and defining decision variable types. The method divides the injured evacuation and rescue process into multiple stages and calculates the deprivation costs for each stage, including the deprivation cost for seriously injured, the total deprivation cost for each injured person, and the total deprivation cost for all injured. The total deprivation cost for all injured is combined with the movement cost of medical relief tents, the transportation cost of ambulances, and the penalty cost for untreated injured to obtain the objective function, which is to minimize the total cost of the entire emergency rescue. Among these, minimizing the total cost of the entire emergency response for: ； Collection of alternative locations for medical relief tents ; Medical relief tents from The unit movement cost of moving point j to point j; Medical relief tents from Move the point to Distance between points; :if Momentary medical rescue tents from Move the point to If the value is 1, then =1; otherwise =0. : The unit time transportation cost of ambulances; : From the hospital To the medical relief tent The number of ambulances; Disaster area The number of seriously injured people who have not been rescued; Disaster area The penalty coefficient for wounded personnel not receiving medical treatment; : Momentary Medical Rescue Tent The number of wounded who did not receive treatment; Medical rescue tent The penalty coefficient for wounded soldiers who do not receive medical treatment; The cost of moving medical relief tents; The cost of ambulance transportation; The punitive cost of not treating the wounded; Time set ; : The coefficient of the deprivation cost function; Disaster area To the medical relief tent The walking time of the wounded; This indicates that the wounded are being transferred from the medical relief tent. To the hospital The delivery time; The injured are in the hospital. Average waiting time; Disaster site assembly, ; Collection of alternative locations for medical relief tents ; Existing hospitals (collection) ; : Always from the disaster point To the medical relief tent The number of seriously injured; : From the medical relief tent Arrive at the hospital The number of seriously injured.

2. The dynamic planning method for emergency rescue resource allocation for post-disaster casualty evacuation as described in claim 1, characterized in that: The pre-defined rescue environment includes: (1) The arrival of wounded patients in the hospital follows a Poisson distribution; it is assumed to be an M / M / 1 single-channel service system, that is, all medical staff are treated as a whole and the existence of multiple service stations in the actual environment is ignored; (2) During the evacuation process, it is assumed that the wounded will not die due to the evacuation process itself. In the modeling process, only the deprivation cost of the wounded is considered. (3) Assume that all ambulances are homogeneous and their speeds remain constant; (4) Assume that the number of seriously injured or killed people in the disaster area is known; (5) Assume that the ambulance returns to its affiliated hospital after completing the rescue mission.

3. The dynamic planning method for emergency rescue resource allocation for post-disaster casualty evacuation as described in claim 1, characterized in that: The probability density function of the deprivation cost for seriously wounded patients is defined as follows: 。 4. The dynamic planning method for emergency rescue resource allocation for post-disaster casualty evacuation as described in claim 1, characterized in that: The total deprivation cost per wounded soldier is as follows: ； S∆ABC is the formula for the area of ​​the linearly descending region; its mathematical meaning is: to + During this period, the injured person's condition stabilized due to basic emergency treatment received during ambulance transport, and the deprivation cost of the injured person decreased linearly to 0.

5. The dynamic planning method for emergency rescue resource scheduling for post-disaster casualty evacuation as described in claim 1, characterized in that: Total deprivation cost for all wounded: 。 6. The dynamic planning method for emergency rescue resource scheduling for post-disaster casualty evacuation as described in claim 1, characterized in that: Tent setup and service constraints include: This indicates that at any given time t, any medical tent candidate point j can have at most one medical rescue tent; The initial location and status of the medical relief tent; To restrict the movement of medical relief tents; This indicates that for any disaster site i, there is at least one alternative medical relief tent j serving it; This indicates that only if the alternative point j has a medical relief tent can it serve the disaster site i; This indicates the capacity constraints of the medical relief tent; The number of injured at disaster site i is conserved; The initial location status of the ambulances at each hospital is given; The state and location of the ambulance at any time t are given; This indicates that ambulances will only be assigned to point j if a medical aid tent is available at that point; The capacity constraints of existing hospitals; This indicates that the total capacity of the ambulances dispatched to medical relief tent point j is sufficient to meet the vehicle capacity required by the injured at that point. This indicates that the number of wounded individuals who had not received treatment at point j of the medical rescue tent at the initial moment was 0. This represents the conservation of the number of untreated wounded at point j of the medical relief tent; This represents the arrival rate of wounded patients at any hospital h at any time t; This represents the maximum processing capacity of hospital h; Let t be the waiting time of the wounded in any hospital at any time; The average waiting time for hospitalized wounded patients; and The definition of decision variable types is given.

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