Material matching and dispatching system integrating disaster response and emergency situation

Abstract

The invention discloses a material matching and dispatching method under the condition of integrating disaster response and emergency. The method comprises the following steps: S1, obtaining material information of a supply site and a demand site; s2, evaluating the emergency degree of the demand place, and mapping the emergency degree as a priority distribution basis; s3, calculating a distance parameter between the supply site and the demand site for path planning; s4, based on the emergency degree and the distance factor, generating a comprehensive adjustment factor to dynamically adjust the demand quantity and make a matching decision; s5, selecting a transportation path through a path planning algorithm; s6, automatically allocating and transporting materials according to the matching decision and the path planning result; and S7, monitoring supply and demand changes in real time, and dynamically adjusting a matching and dispatching scheme. According to the method, the demand urgency and the transportation path efficiency are comprehensively considered, so that efficient material distribution and transportation in a disaster scene are realized, the demand change can be quickly responded, and the resource allocation is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of disaster response and emergency material allocation, and in particular to a material matching and transportation system integrating disaster response and emergency situations. Background Art

[0002] In the process of disaster response and emergency management, the rapid and accurate allocation of materials is crucial to reducing disaster losses and improving rescue efficiency. Traditional emergency material allocation systems face many challenges in disaster scenarios, mainly reflected in the delay of information acquisition and processing, the lack of optimization capabilities of transportation routes, and the lack of flexibility in responding to real-time changes in demand and inventory status. These problems have led to the existing systems often being unable to meet the needs of efficient and flexible material allocation in actual applications.

[0003] The first is that the collection and integration efficiency of material information in existing technologies is low. Especially when disasters occur, the types and urgency of material demand at demand points change rapidly, and the inventory and distribution status of materials at supply locations are also constantly updated. Traditional systems often rely on static data to integrate material information at supply locations and demand locations, and most of the relevant information is obtained through manual entry and processing, making it difficult to achieve real-time updates of supply and demand. In addition, due to the lack of systematic algorithm support, traditional systems often rely on pre-established rules and fixed parameters to allocate materials, making it difficult to dynamically adjust allocation strategies to adapt to the complex changes at the disaster site.

[0004] Second, the existing emergency material allocation system lacks an effective optimization solution when selecting the transportation route from the supply point to the demand point. In disaster scenarios, traffic conditions may change due to the impact of disasters. Path planning in existing systems is often based on preset route maps, and fails to fully consider dynamic factors such as traffic feasibility, cost, and time in emergency situations. Traditional systems find it difficult to update routes and adjust path priorities in real time, resulting in poor timeliness in material transportation and increasing the risk that materials cannot reach the required location in time. In addition, the existing system path selection algorithm is mostly a single shortest path selection, lacking a joint trade-off based on the urgency of material demand and distance, and failing to effectively improve the overall efficiency of transportation.

[0005] Third, the traditional emergency material allocation system has a weak ability to respond to changes in demand; the demand situation at the disaster site may fluctuate frequently in a short period of time, and the inventory allocation at the supply location will also change with the mobilization of materials. Most of the existing systems are static inventory monitoring modes, which cannot reflect the dynamic changes in the supply and demand relationship in real time, resulting in a mismatch between demand and inventory. Especially when there are sudden changes in supply and demand, it is difficult for the system to make corresponding adjustments in time, which in turn affects the accuracy and response speed of material transportation and cannot meet the actual needs of the disaster site.

[0006] Therefore, how to provide a material matching and transportation system that integrates disaster response and emergency situations is an urgent problem that technical personnel in this field need to solve. Summary of the invention

[0007] One purpose of the present invention is to propose a material matching and transportation method that integrates disaster response and emergency situations. The present invention makes full use of the emergency assessment algorithm, the path optimization algorithm and the real-time monitoring technology, and describes in detail the steps of realizing efficient material transportation through information acquisition, priority allocation, path planning and dynamic adjustment in disaster and emergency situations, and has the advantages of fast response speed, accurate resource allocation and strong dynamic adaptability.

[0008] According to an embodiment of the present invention, a material matching and transportation method for integrated disaster response and emergency situations includes the following steps:

[0009] S1. Obtaining material information of places with supply capabilities and places of demand, wherein the material information includes material types, quantities, warehouse locations, and feasibility of transportation routes;

[0010] S2. Evaluate the urgency of the demand locations, map the urgency of each demand location into an urgency parameter, and use this as the basis for priority allocation of materials;

[0011] S3, calculating the distance parameter between the supply-capable location and the demand location, and using the distance parameter for path planning when transporting materials;

[0012] S4. Based on the urgency and distance factors, a comprehensive adjustment algorithm is used to jointly calculate the urgency parameters and distance parameters of the demand location to generate a comprehensive adjustment factor, dynamically adjust the material demand at each demand location, and generate a material matching decision;

[0013] S5. Select a transportation route for materials by optimizing the path planning algorithm, taking into account the urgency of material demand and the efficiency of the transportation route;

[0014] S6. According to the matching decision results, the transportation system automatically selects materials at locations with supply capabilities, and transfers them from the supply locations to the demand locations based on the transportation routes;

[0015] S7. During the material allocation process, monitor the inventory changes and demand changes of both the supply and demand sides in real time, and dynamically adjust the material matching and transportation plans.

[0016] Optionally, the S3 specifically includes:

[0017] S21. Obtain geographical location information of locations with supply capabilities and demand locations, and calculate the distance d between each demand location and each location with supply capabilities. ij , where dij represents the distance between the i-th demand location and the j-th supply location;

[0018] S22, by calculating the distance parameter D ij , distance parameter D ij Based on the distance d between each pair of demand locations and supply locations ij , and used as input basis for path planning;

[0019] S23, the distance parameter D ij Based on the feasibility of the transportation route and traffic conditions, determine the path from each supply location to the demand location.

[0020] Optionally, the S4 specifically includes:

[0021] S41. Define the urgency parameter U according to the urgency of the required location. i , where U i Indicates the urgency of the i-th demand location, quantified in the range of 0 to 100, with lower values ​​indicating higher urgency;

[0022] S42, based on the distance parameter D between the demand location and the supply location ij , calculate the distance adjustment factor

[0023]

[0024] Among them, D ij is the distance between the i-th demand location and the j-th supply location, in kilometers, d max is the preset maximum distance parameter, and α is the control coefficient, which is used to adjust the influence of distance on demand;

[0025] S43. Calculate the comprehensive adjustment factor C ij , comprehensive adjustment factor C ij By using the urgency parameter U i and distance adjustment factor The joint calculation of

[0026] S44, based on comprehensive adjustment factor C ij , calculate the adjusted demand Q ij :

[0027]

[0028] Among them, Q i is the initial demand of the ith demand location, Qi j The adjusted demand is used to generate material matching decisions and realize dynamic adjustment and allocation of materials.

[0029] Optionally, the S43 specifically includes:

[0030] S431, according to the urgency parameter U of the required location i and distance adjustment factor The comprehensive adjustment factor C is calculated by ij :

[0031]

[0032] Among them, U i It represents the urgency of the i-th demand location, which is quantified in the range of 0 to 100. β is the urgency control coefficient, which is used to control the weight of the urgency in the comprehensive adjustment factor. is the distance adjustment factor between the oth demand location and the jth supply location, which is used to express the impact of distance on material demand; y is the distance impact control coefficient, which is used to adjust the impact of the distance factor on demand;

[0033] S432. Setting the urgency control coefficient β and the distance influence control coefficient γ according to different situations, adjusting the weights of the urgency and distance in the comprehensive adjustment factor. The higher the value of β, the greater the impact of the urgency on the comprehensive adjustment factor. The higher the value of y, the more significant the impact of the distance on the comprehensive adjustment factor.

[0034] S433. Calculate distance adjustment factor On this basis, the influence of distance on demand is regulated by setting different distance influence coefficients α:

[0035]

[0036] Among them, D ij is the distance between the i-th demand location and the j-th supply location, d max is the preset maximum distance parameter, α is the distance influence coefficient, which controls the nonlinear influence of distance on the comprehensive adjustment factor, and realizes the smooth increase of the distance adjustment factor through the sine function;

[0037] S434, the comprehensive adjustment factor C ij It is used to adjust the priority of material distribution, combining the dynamic factors of urgency and distance, giving priority to locations that meet urgent needs and balancing the distance factor.

[0038] Optionally, the S5 specifically includes:

[0039] S51. Obtain all possible transportation routes based on the geographical location information of the demand location and the supply location, and calculate the distance parameter L of each route. ij and transportation time T ij , where L ijrepresents the path distance between the i-th demand location and the j-th supply location, T ij Indicates the estimated transportation time required for the route;

[0040] S52, according to the path distance parameter L ij and transportation time T ij , define the path efficiency factor E ij , which is used to measure the transportation efficiency of each path:

[0041]

[0042] Among them, ω1 and ω2 are the path efficiency control coefficients, which are used to adjust the weights of path distance and transportation time in the path efficiency factor respectively. λ is the time impact adjustment coefficient, which controls the impact of transportation time on the efficiency factor. ij The higher the value of , the higher the path efficiency;

[0043] S53, urgency parameter U based on the demand location i and the path efficiency factor E ij , calculate the path priority factor P ij ;

[0044] S54. Select path priority factor P ij The highest path is used as the transportation path, and the transportation path is used to transport materials from the supply location to the demand location, thereby realizing the optimal transportation path selection for the materials.

[0045] Optionally, it is characterized in that the S53 specifically includes:

[0046] S531, according to the urgency parameter U of the required location i and the path efficiency factor E ij , calculate the path priority factor P ij :

[0047]

[0048] Among them, P ij is the path priority factor between the i-th demand location and the j-th supply location, U i Indicates the urgency of the i-th demand location, E ij is the path efficiency factor, which measures the efficiency of the transportation path. max is the maximum value of the path efficiency factor, which is used to convert E ij Normalization, δ is the urgency control coefficient, which controls the weight of urgency in the path priority factor, σ is the path efficiency control coefficient, which controls the influence of path efficiency in the path priority factor;

[0049] S532. By adjusting the emergency control coefficient δ, the impact of the emergency degree on the priority factor can be flexibly adjusted according to the needs of different disasters and emergency situations;

[0050] S533, based on the path efficiency control coefficient σ and the path efficiency factor E ij , apply the sine function for nonlinear adjustment:

[0051]

[0052] Among them, when E ij Close to E max When , the priority factor increases, which makes the impact of path efficiency on priority gradually stabilize.

[0053] Optionally, the S7 specifically includes:

[0054] S71. During the material allocation process, monitor the inventory status of the supply location and the demand location in real time, obtain the inventory change and demand change, and determine the dynamic changes in the supply and demand situation;

[0055] S72. Based on inventory changes and demand changes, define real-time adjustment factors, and dynamically adjust the priority allocation of materials at each demand location through adjustment factors to reflect the urgency of demand and the availability of supply;

[0056] S73, combining the path priority factor and the real-time adjustment factor, updating the material allocation priority to reflect the supply and demand changes and the optimal choice of the transportation path;

[0057] S74. During the material allocation process, the material matching and transportation plan are adjusted in real time according to the updated material allocation priority factors, and priority is given to transportation to demand locations with high priority factors, so as to achieve dynamic response of emergency material allocation, adapt to sudden changes in demand and optimize material allocation efficiency.

[0058] A material matching and transportation system integrating disaster response and emergency situations according to an embodiment of the present invention includes:

[0059] An information acquisition module is used to acquire material information of places with supply capabilities and places of demand, wherein the material information includes material types, quantities, warehouse locations and feasibility of transportation routes;

[0060] The urgency assessment module is used to assess the urgency of each demand location, map the urgency of each demand location into an urgency parameter, and use the parameter as the basis for priority allocation of materials;

[0061] The distance calculation module is used to calculate the distance parameter between the supply location and the demand location, and use the distance parameter for the route planning of transporting materials;

[0062] The comprehensive adjustment module uses a comprehensive adjustment algorithm to jointly calculate the urgency parameter and distance parameter of the demand location to generate a comprehensive adjustment factor, dynamically adjust the material demand at each demand location, and generate material matching decisions;

[0063] The path planning module is used to select the optimal transportation path for materials based on material matching decisions and path planning algorithms, taking into account the urgency of material demand and the efficiency of the transportation path;

[0064] The automatic transportation module is used to automatically select materials with supply capacity from supply locations to demand locations through the transportation system based on material matching decisions and optimal path results;

[0065] The real-time monitoring module is used to monitor the inventory changes and demand changes of both the supply and demand sides in real time during the material allocation process, calculate the real-time adjustment factors, and dynamically update the material matching and transportation plans according to the changes in the supply and demand situation.

[0066] The beneficial effects of the present invention are:

[0067] (1) The present invention effectively improves the efficiency of material allocation and response flexibility in disaster response by introducing an emergency assessment algorithm, a comprehensive adjustment algorithm, and a dynamic programming algorithm based on path priority. Compared with the traditional static allocation method, this method can optimize material allocation in real time according to the emergency level and distance factors, so that high-priority needs can be met first when resources are limited, thereby significantly improving the timeliness and reliability of disaster emergency response.

[0068] (2) The present invention coordinates the transportation of materials between supply locations and demand locations through intelligent path planning and real-time monitoring modules. By optimizing the comprehensive calculation of path efficiency and demand priority factors, the system can automatically select the optimal transportation path to achieve efficient and low-cost material transportation, avoiding material transportation delays or resource waste caused by insufficient route planning.

[0069] (3) The present invention combines dynamic monitoring and real-time adjustment mechanisms to continuously update supply and demand information and dynamically adjust allocation plans during the material transportation process. This real-time update and adaptive regulation capability enables the system to respond to sudden changes in demand during disaster emergency response, ensuring that materials can be accurately delivered to demand points, thereby improving the adaptability and response speed of material allocation, ensuring the continuity of rescue work and the optimal effect of resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0071] Figure 1 A flow chart of a material matching and transportation method for integrated disaster response and emergency situations proposed by the present invention;

[0072] Figure 2 This is a framework diagram of a material matching and transportation system that integrates disaster response and emergency situations proposed by the present invention. DETAILED DESCRIPTION

[0073] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0074] refer to Figure 1-2 , a material matching and transportation method integrating disaster response and emergency situations, including the following:

[0075] S1. Obtaining material information of places with supply capabilities and places of demand, wherein the material information includes material types, quantities, warehouse locations, and feasibility of transportation routes;

[0076] S2. Evaluate the urgency of the demand locations, map the urgency of each demand location into an urgency parameter, and use this as the basis for priority allocation of materials;

[0077] S3, calculating the distance parameter between the supply-capable location and the demand location, and using the distance parameter for path planning when transporting materials;

[0078] S4. Based on the urgency and distance factors, a comprehensive adjustment algorithm is used to jointly calculate the urgency parameters and distance parameters of the demand location to generate a comprehensive adjustment factor, dynamically adjust the material demand at each demand location, and generate a material matching decision;

[0079] S5. Select a transportation route for materials by optimizing the path planning algorithm, taking into account the urgency of material demand and the efficiency of the transportation route;

[0080] S6. According to the matching decision results, the transportation system automatically selects materials at locations with supply capabilities, and transfers them from the supply locations to the demand locations based on the transportation routes;

[0081] S7. During the material allocation process, monitor the inventory changes and demand changes of both the supply and demand sides in real time, and dynamically adjust the material matching and transportation plans.

[0082] In this implementation, S3 specifically includes:

[0083] S21. Obtain geographical location information of locations with supply capabilities and demand locations, and calculate the distance d between each demand location and each location with supply capabilities.ij , where d ij represents the distance between the i-th demand location and the j-th supply location;

[0084] S22, by calculating the distance parameter D ij , distance parameter D ij Based on the distance d between each pair of demand locations and supply locations ij , and used as input basis for path planning;

[0085] S23, the distance parameter D ij Based on the feasibility of the transportation route and traffic conditions, determine the path from each supply location to the demand location.

[0086] In this implementation, S4 specifically includes:

[0087] S41. Define the urgency parameter U according to the urgency of the required location. i , where U i Indicates the urgency of the i-th demand location, quantified in the range of 0 to 100, with lower values ​​indicating higher urgency;

[0088] S42, based on the distance parameter D between the demand location and the supply location ij , calculate the distance adjustment factor

[0089]

[0090] Among them, D ij is the distance between the i-th demand location and the j-th supply location, in kilometers, d max is the preset maximum distance parameter, and α is the control coefficient, which is used to adjust the influence of distance on demand;

[0091] S43. Calculate the comprehensive adjustment factor C ij , comprehensive adjustment factor C ij By using the urgency parameter U i and distance adjustment factor The joint calculation of

[0092] S44, based on comprehensive adjustment factor C ij , calculate the adjusted demand Q ij :

[0093]

[0094] Among them, Q i is the initial demand of the ith demand location, Qi jThe adjusted demand is used to generate material matching decisions and realize dynamic adjustment and allocation of materials.

[0095] In this implementation manner, the S43 specifically includes:

[0096] S431, according to the urgency parameter U of the required location i and distance adjustment factor The comprehensive adjustment factor C is calculated by ij :

[0097]

[0098] Among them, U i It represents the urgency of the i-th demand location, which is quantified in the range of 0 to 100. β is the urgency control coefficient, which is used to control the weight of the urgency in the comprehensive adjustment factor. is the distance adjustment factor between the i-th demand location and the j-th supply location, which is used to express the impact of distance on material demand; γ is the distance impact control coefficient, which is used to adjust the impact of the distance factor on demand;

[0099] S432. Setting the urgency control coefficient β and the distance influence control coefficient γ according to different situations, adjusting the weights of the urgency and distance in the comprehensive adjustment factor. The higher the value of β, the greater the impact of the urgency on the comprehensive adjustment factor. The higher the value of y, the more significant the impact of the distance on the comprehensive adjustment factor.

[0100] S433. Calculate distance adjustment factor On this basis, the influence of distance on demand is regulated by setting different distance influence coefficients α:

[0101]

[0102] Among them, D ij is the distance between the i-th demand location and the j-th supply location, d max is the preset maximum distance parameter, α is the distance influence coefficient, which controls the nonlinear influence of distance on the comprehensive adjustment factor, and realizes the smooth increase of the distance adjustment factor through the sine function;

[0103] S434, the comprehensive adjustment factor C ij It is used to adjust the priority of material distribution, combining the dynamic factors of urgency and distance, giving priority to locations that meet urgent needs and balancing the distance factor.

[0104] In this implementation manner, S5 specifically includes:

[0105] S51. Obtain all possible transportation routes based on the geographical location information of the demand location and the supply location, and calculate the distance parameter L of each route.ij and transportation time T ij , where L ij represents the path distance between the i-th demand location and the j-th supply location, T ij Indicates the estimated transportation time required for the route;

[0106] S52, according to the path distance parameter L ij and transportation time T ij , define the path efficiency factor E ij , which is used to measure the transportation efficiency of each path:

[0107]

[0108] Among them, ω1 and ω2 are the path efficiency control coefficients, which are used to adjust the weights of path distance and transportation time in the path efficiency factor respectively. λ is the time impact adjustment coefficient, which controls the impact of transportation time on the efficiency factor. ij The higher the value of , the higher the path efficiency;

[0109] S53, urgency parameter U based on the demand location i and the path efficiency factor E ij , calculate the path priority factor P ij ;

[0110] S54. Select path priority factor P ij The highest path is used as the transportation path, and the transportation path is used to transport materials from the supply location to the demand location, thereby realizing the optimal transportation path selection for the materials.

[0111] In this implementation, it is characterized in that the S53 specifically includes:

[0112] S531, according to the urgency parameter U of the required location i and the path efficiency factor E ij , calculate the path priority factor P ij :

[0113]

[0114] Among them, P ij is the path priority factor between the i-th demand location and the j-th supply location, U i Indicates the urgency of the i-th demand location, E ij is the path efficiency factor, which measures the efficiency of the transportation path. max is the maximum value of the path efficiency factor, which is used to convert E ijNormalization, δ is the urgency control coefficient, which controls the weight of urgency in the path priority factor, σ is the path efficiency control coefficient, which controls the influence of path efficiency in the path priority factor;

[0115] S532. By adjusting the emergency control coefficient δ, the impact of the emergency degree on the priority factor can be flexibly adjusted according to the needs of different disasters and emergency situations;

[0116] S533, based on the path efficiency control coefficient σ and the path efficiency factor E ij , apply the sine function for nonlinear adjustment:

[0117]

[0118] Among them, when E ij Close to E max When , the priority factor increases, which makes the impact of path efficiency on priority gradually stabilize.

[0119] In this implementation manner, the S7 specifically includes:

[0120] S71. During the material allocation process, monitor the inventory status of the supply location and the demand location in real time, obtain the inventory change and demand change, and determine the dynamic changes in the supply and demand situation;

[0121] S72. Based on inventory changes and demand changes, define real-time adjustment factors, and dynamically adjust the priority allocation of materials at each demand location through adjustment factors to reflect the urgency of demand and the availability of supply;

[0122] S73, combining the path priority factor and the real-time adjustment factor, updating the material allocation priority to reflect the supply and demand changes and the optimal choice of the transportation path;

[0123] S74. During the material allocation process, the material matching and transportation plan are adjusted in real time according to the updated material allocation priority factors, and priority is given to transportation to demand locations with high priority factors, so as to achieve dynamic response of emergency material allocation, adapt to sudden changes in demand and optimize material allocation efficiency.

[0124] In this embodiment, a material matching and transportation system integrating disaster response and emergency situations includes:

[0125] An information acquisition module is used to acquire material information of places with supply capabilities and places of demand, wherein the material information includes material types, quantities, warehouse locations and feasibility of transportation routes;

[0126] The urgency assessment module is used to assess the urgency of each demand location, map the urgency of each demand location into an urgency parameter, and use the parameter as the basis for priority allocation of materials;

[0127] The distance calculation module is used to calculate the distance parameter between the supply location and the demand location, and use the distance parameter for the route planning of transporting materials;

[0128] The comprehensive adjustment module uses a comprehensive adjustment algorithm to jointly calculate the urgency parameter and distance parameter of the demand location to generate a comprehensive adjustment factor, dynamically adjust the material demand at each demand location, and generate material matching decisions;

[0129] The path planning module is used to select the optimal transportation path for materials based on material matching decisions and path planning algorithms, taking into account the urgency of material demand and the efficiency of the transportation path;

[0130] The automatic transportation module is used to automatically select materials with supply capacity from supply locations to demand locations through the transportation system based on material matching decisions and optimal path results;

[0131] The real-time monitoring module is used to monitor the inventory changes and demand changes of both the supply and demand sides in real time during the material allocation process, calculate the real-time adjustment factors, and dynamically update the material matching and transportation plans according to the changes in the supply and demand situation.

[0132] Embodiment 1:

[0133] In a city in southern China, a serious flood disaster occurred, and residents in many areas were trapped, water and electricity facilities were damaged, and the demand for emergency supplies was very urgent. In the emergency response to this disaster, the Municipal Emergency Management Bureau first applied the integrated disaster response and emergency material matching and transportation method of the present invention to efficiently meet the material needs of multiple disaster-stricken areas, especially to accurately deliver rescue materials to areas with high demand and high urgency in a short period of time.

[0134] At the beginning of the disaster, demand information from various disaster-stricken areas continued to pour in. The system first collected material demand data from multiple disaster-stricken areas in real time through the information acquisition module, including information such as food, drinking water, medicines, and rescue equipment. The collected information also includes the quantity and type of required materials, the geographical location of the disaster-stricken area, and the status of material inventory and available transportation routes in each temporary warehouse. The system's urgency assessment module immediately assesses the urgency of the demand point and converts this information into priorities so that high-priority demand areas can be given priority in subsequent steps. After collecting and evaluating material demand and inventory information, the system determines the distance from each supply warehouse to each demand location through the distance calculation module, providing a basis for subsequent path planning and material allocation plans. The comprehensive adjustment module further considers the two factors of demand urgency and transportation distance, and generates priority matching decisions for each demand point through a comprehensive adjustment algorithm. At this time, the path planning module selects the optimal transportation route based on the material matching decision and supply-demand distance, combined with road conditions, time, and cost, to ensure that the materials are delivered to the areas with urgent needs in the shortest time.

[0135] In the emergency deployment, the Municipal Emergency Management Bureau mobilized relief supplies from 10 supply warehouses, including 15,000 boxes of food, 10,000 barrels of drinking water and 2,000 emergency medicines. The system continuously adjusts the deployment plan based on real-time feedback information to ensure that the supplies are accurately and efficiently delivered to the disaster area. The following are the deployment data and effects of different supplies during the disaster response process:

[0136] Table 1 Data table of material allocation effect during disaster emergency response

[0137]

[0138] As shown in Table 1, by applying the method of the present invention, the transportation time of food is shortened from the traditional 6.5 hours to 4.2 hours, the transportation time of drinking water is shortened from 7.0 hours to 4.5 hours, and the transportation time of medicine is shortened from 8.5 hours to 5.8 hours, which significantly improves the timeliness of material allocation. In addition, the material demand satisfaction rates reached 95%, 93% and 92% respectively, and the distribution success rate was increased to more than 95%.

[0139] By implementing the integrated disaster response and emergency material matching and dispatching method of the present invention, the Municipal Emergency Management Bureau significantly improved the efficiency and accuracy of material dispatching, reduced material delivery delays, and increased the success rate of supply and demand matching, ensuring the smooth progress of rescue work. In addition, the method reduces the material dispatching time for high-priority needs and improves the utilization efficiency and response speed of emergency resources.

[0140] In summary, the present invention can effectively solve the problem of insufficient efficiency and flexibility in material allocation during disaster emergency response through emergency assessment, dynamic path planning and real-time monitoring and adjustment mechanism. The implementation of this method has established solid technical support for the Municipal Emergency Management Bureau in future disaster response and has significant promotion value.

[0141] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A material matching and transportation method integrating disaster response and emergency situations, characterized in that: The following steps are involved: S1. Obtaining material information of places with supply capabilities and places of demand, wherein the material information includes material types, quantities, warehouse locations, and feasibility of transportation routes; S2. Evaluate the urgency of the demand locations, map the urgency of each demand location into an urgency parameter, and use this as the basis for priority allocation of materials; S3, calculating the distance parameter between the supply-capable location and the demand location, and using the distance parameter for path planning when transporting materials; S4. Based on the urgency and distance factors, a comprehensive adjustment algorithm is used to jointly calculate the urgency parameters and distance parameters of the demand location to generate a comprehensive adjustment factor, dynamically adjust the material demand at each demand location, and generate a material matching decision; S5. Select a transportation route for materials by optimizing the path planning algorithm, taking into account the urgency of material demand and the efficiency of the transportation route; S6. According to the matching decision results, the transportation system automatically selects materials at locations with supply capabilities, and transfers them from the supply locations to the demand locations based on the transportation routes; S7. During the material allocation process, monitor the inventory changes and demand changes of both the supply and demand sides in real time, and dynamically adjust the material matching and transportation plans.

2. A material matching and transportation method for integrated disaster response and emergency situations according to claim 1, characterized in that: The S3 specifically includes: S21. Obtain geographical location information of locations with supply capabilities and demand locations, and calculate the distance d between each demand location and each location with supply capabilities. ij , where d ij represents the distance between the i-th demand location and the j-th supply location; S22, by calculating the distance parameter D ij , distance parameter D ij Based on the distance d between each pair of demand locations and supply locations ij , and used as input basis for path planning; S23, the distance parameter D ij Based on the feasibility of the transportation route and traffic conditions, determine the path from each supply location to the demand location.

3. The material matching and transportation method for integrated disaster response and emergency situations according to claim 1 is characterized in that: The S4 specifically includes: S41. Define the urgency parameter U according to the urgency of the required location. i , where U i Indicates the urgency of the i-th demand location, quantified in the range of 0 to 100, with lower values ​​indicating higher urgency; S42, based on the distance parameter D between the demand location and the supply location ij , calculate the distance adjustment factor Among them, D ij is the distance between the i-th demand location and the j-th supply location, in kilometers, d max is the preset maximum distance parameter, and α is the control coefficient, which is used to adjust the influence of distance on demand; S43. Calculate the comprehensive adjustment factor C ij , comprehensive adjustment factor C ij By using the urgency parameter U i and distance adjustment factor The joint calculation of S44, based on comprehensive adjustment factor C ij , calculate the adjusted demand Q ij : Among them, Q i is the initial demand of the ith demand location, Q ij The adjusted demand is used to generate material matching decisions and realize dynamic adjustment and allocation of materials.

4. The integrated disaster response and emergency material matching and transportation method according to claim 3 is characterized in that: The S43 specifically includes: S431, according to the urgency parameter U of the required location i and distance adjustment factor The comprehensive adjustment factor C is calculated by ij : Among them, U i It represents the urgency of the i-th demand location, which is quantified in the range of 0 to 100. β is the urgency control coefficient, which is used to control the weight of the urgency in the comprehensive adjustment factor. is the distance adjustment factor between the i-th demand location and the j-th supply location, which is used to express the impact of distance on material demand; γ is the distance impact control coefficient, which is used to adjust the impact of the distance factor on demand; S432. Setting the urgency control coefficient β and the distance influence control coefficient γ according to different situations, adjusting the weights of the urgency and the distance in the comprehensive adjustment factor. The higher the value of β, the greater the impact of the urgency on the comprehensive adjustment factor. The higher the value of γ, the more significant the impact of the distance on the comprehensive adjustment factor. S433. Calculate distance adjustment factor On this basis, the influence of distance on demand is regulated by setting different distance influence coefficients α: Among them, D ij is the distance between the i-th demand location and the j-th supply location, d max is the preset maximum distance parameter, α is the distance influence coefficient, which controls the nonlinear influence of distance on the comprehensive adjustment factor, and realizes the smooth increase of the distance adjustment factor through the sine function; S434, the comprehensive adjustment factor C ij It is used to adjust the priority of material distribution, combining the dynamic factors of urgency and distance, giving priority to locations that meet urgent needs and balancing the distance factor.

5. The integrated disaster response and emergency material matching and transportation method according to claim 1, characterized in that: The S5 specifically includes: S51. Obtain all possible transportation routes based on the geographical location information of the demand location and the supply location, and calculate the distance parameter L of each route. ij and transportation time T ij , where L ij represents the path distance between the i-th demand location and the j-th supply location, T ij Indicates the estimated transportation time required for the route; S52, according to the path distance parameter L ij and transportation time T ij , define the path efficiency factor E ij , which is used to measure the transportation efficiency of each path: Among them, ω1 and ω2 are the path efficiency control coefficients, which are used to adjust the weights of path distance and transportation time in the path efficiency factor respectively. λ is the time impact adjustment coefficient, which controls the impact of transportation time on the efficiency factor. ij The higher the value of , the higher the path efficiency; S53, urgency parameter U based on the demand location i and the path efficiency factor E ij , calculate the path priority factor P ij ; S54. Select path priority factor P ij The highest path is used as the transportation path, and the transportation path is used to transport materials from the supply location to the demand location, thereby realizing the optimal transportation path selection for the materials.

6. A material matching and transportation method for integrated disaster response and emergency situations according to claim 5, characterized in that: The S53 specifically includes: S531, according to the urgency parameter U of the required location i and the path efficiency factor E ij , calculate the path priority factor P ij : Among them, P ij is the path priority factor between the i-th demand location and the j-th supply location, U i Indicates the urgency of the i-th demand location, E ij is the path efficiency factor, which measures the efficiency of the transportation path. max is the maximum value of the path efficiency factor, which is used to convert E ij Normalization, δ is the urgency control coefficient, which controls the weight of urgency in the path priority factor, σ is the path efficiency control coefficient, which controls the influence of path efficiency in the path priority factor; S532. By adjusting the emergency control coefficient δ, the impact of the emergency degree on the priority factor can be flexibly adjusted according to the needs of different disasters and emergency situations; S533, based on the path efficiency control coefficient σ and the path efficiency factor E ij , apply the sine function for nonlinear adjustment: Among them, when E ij Close to E max When , the priority factor increases, which makes the impact of path efficiency on priority gradually stabilize.

7. The integrated disaster response and emergency material matching and transportation method according to claim 1, characterized in that: The S7 specifically includes: S71. During the material allocation process, monitor the inventory status of the supply location and the demand location in real time, obtain the inventory change and demand change, and determine the dynamic changes in the supply and demand situation; S72. Based on inventory changes and demand changes, define real-time adjustment factors, and dynamically adjust the priority allocation of materials at each demand location through adjustment factors to reflect the urgency of demand and the availability of supply; S73, combining the path priority factor and the real-time adjustment factor, updating the material allocation priority to reflect the supply and demand changes and the optimal choice of the transportation path; S74. During the material allocation process, the material matching and transportation plan are adjusted in real time according to the updated material allocation priority factors, and priority is given to transportation to demand locations with high priority factors, so as to achieve dynamic response of emergency material allocation, adapt to sudden changes in demand and optimize material allocation efficiency.

8. A material matching and dispatching system integrating disaster response and emergency situations, characterized in that: These include: An information acquisition module is used to acquire material information of places with supply capabilities and places of demand, wherein the material information includes material types, quantities, warehouse locations and feasibility of transportation routes; The urgency assessment module is used to assess the urgency of each demand location, map the urgency of each demand location into an urgency parameter, and use the parameter as the basis for priority allocation of materials; The distance calculation module is used to calculate the distance parameter between the supply location and the demand location, and use the distance parameter for the route planning of transporting materials; The comprehensive adjustment module uses a comprehensive adjustment algorithm to jointly calculate the urgency parameter and distance parameter of the demand location to generate a comprehensive adjustment factor, dynamically adjust the material demand at each demand location, and generate material matching decisions; The path planning module is used to select the optimal transportation path for materials based on material matching decisions and path planning algorithms, taking into account the urgency of material demand and the efficiency of the transportation path; The automatic transportation module is used to automatically select materials with supply capacity from supply locations to demand locations through the transportation system based on material matching decisions and optimal path results; The real-time monitoring module is used to monitor the inventory changes and demand changes of both the supply and demand sides in real time during the material allocation process, calculate the real-time adjustment factors, and dynamically update the material matching and transportation plans according to the changes in the supply and demand situation.

Images