Emergency communication equipment dispatching management method and system

Abstract

The application discloses a kind of emergency communication equipment dispatch management method and system related to dispatch management technical field, obtain the communication demand information corresponding to each task point and the resource supply information corresponding to each emergency communication equipment, the communication demand information and the resource supply information are matched based on emergency dynamic weight, obtain initial scheduling scheme;Based on the initial scheduling scheme and the real-time traffic information of emergency area, generate initial scheduling strategy;The initial scheduling strategy includes the initial scheduling scheme and the scheduling path corresponding to the implementation initial scheduling scheme;Based on multi-objective optimization algorithm, the initial scheduling strategy is optimized, and target scheduling strategy is obtained, can according to the communication demand information of task point and the resource supply information of emergency communication equipment, real-time determination reasonable emergency communication equipment scheduling strategy, improve the real-time performance and reliability of emergency dispatch.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of dispatch management, in particular to an emergency communication equipment dispatch management method and system. BACKGROUND

[0002] With the improvement of emergency support requirements in China, the related technology provides an emergency communication command system, taking "emergency communication one map" as the goal, realizing "one network access, one screen overview, one key dispatch" of emergency communication equipment, so as to realize that the emergency command center can be directly connected to the rescue front line in the case of major disasters, and real-time grasp the position and equipment state information of production and repair personnel, and ensure "double online" of communication information and repair personnel.

[0003] However, although the prior art realizes the purpose of information concentration and unified dispatch through "emergency communication one map", the emergency communication equipment dispatch still has the problem of complex disposal, for example, due to the problems of multi-source heterogeneous communication equipment, multi-department cooperation and multi-task cooperation in emergency support, there are problems of low efficiency of manual coordination, complicated process and easy to make mistakes. SUMMARY

[0004] In view of the above defects or deficiencies in the prior art, it is desirable to provide an emergency communication equipment dispatch management method and system, which can determine a reasonable emergency communication equipment dispatch strategy in real time according to the communication demand information of the task point and the resource supply information of the emergency communication equipment, and improve the real-time performance and reliability of emergency dispatch.

[0005] In a first aspect, an emergency communication equipment dispatch management method is provided, comprising:

[0006] Obtaining communication demand information corresponding to each task point and resource supply information corresponding to each emergency communication equipment, matching the communication demand information and the resource supply information based on an emergency dynamic weight to obtain an initial dispatch scheme; the initial dispatch scheme includes a dispatch mapping relationship between the emergency communication equipment and the task point; the emergency dynamic weight is related to an emergency support stage and a real-time index value of the emergency communication equipment;

[0007] Generating an initial dispatch strategy based on the initial dispatch scheme and real-time road condition information of an emergency area; the initial dispatch strategy includes the initial dispatch scheme and a dispatch path corresponding to the implementation of the initial dispatch scheme;

[0008] Optimizing the initial dispatch strategy based on a multi-objective optimization algorithm to obtain a target dispatch strategy.

[0009] In some embodiments, further comprising:

[0010] The basic weights between the emergency communication equipment and the evaluation indicators are determined based on prior expert assessments.

[0011] Obtain real-time indicator data corresponding to the emergency communication equipment, and determine the real-time correction weight corresponding to the emergency communication equipment based on the real-time indicator data;

[0012] The weight of each emergency support phase is determined based on the emergency support phase in which the emergency mission is located.

[0013] The emergency dynamic weight is determined based on the basic weight, the real-time correction weight, and the emergency support phase weight.

[0014] In some embodiments, determining the real-time correction weight corresponding to the emergency communication equipment based on the real-time indicator data includes:

[0015] For each evaluation indicator, calculate the real-time evaluation value for each evaluation indicator;

[0016] Based on the various emergency communication devices mentioned above, determine the real-time evaluation entropy of each evaluation indicator;

[0017] The real-time correction weight is determined based on the real-time evaluation entropy.

[0018] In some embodiments, the initial scheduling strategy includes a scheduling strategy for multiple emergency communication devices, and the optimization of the initial scheduling strategy based on a multi-objective optimization algorithm to obtain the target scheduling strategy includes:

[0019] Based on each of the aforementioned task points and the aforementioned emergency communication equipment, an objective function corresponding to the optimization strategy is constructed; the objective function includes total response time, total scheduling cost, and total coverage defect.

[0020] Based on the objective function, the initial scheduling strategy is subjected to non-dominated sorting genetic optimization based on congestion constraints to obtain the target scheduling strategy.

[0021] In some embodiments, the step of performing non-dominated sorting genetic optimization of the initial scheduling strategy based on the objective function includes:

[0022] For each of the initial scheduling strategies, determine the objective function value corresponding to the initial scheduling strategy;

[0023] Based on the objective function value, the initial scheduling strategy is sorted non-dominated to obtain a non-dominated front scheduling strategy, which is then used as the genetic parent scheduling strategy for the current iteration round.

[0024] For each of the non-dominated front scheduling strategies, calculate the congestion degree corresponding to the non-dominated front scheduling strategy;

[0025] Select the non-dominated front scheduling strategy that meets the preset congestion condition, perform genetic iteration, and obtain the candidate scheduling strategy for the next iteration round;

[0026] The candidate scheduling strategies are sorted by non-dominated order to obtain the non-dominated front scheduling strategy for the next iteration round, and so on until the preset exit condition is met.

[0027] In some embodiments, it also includes:

[0028] The congestion level is determined based on the distance between the non-dominated front scheduling strategies.

[0029] Secondly, embodiments of this application provide an emergency communication equipment dispatch and management system, including:

[0030] The matching module is used to obtain communication demand information corresponding to each task point and resource supply information corresponding to each emergency communication equipment. Based on the emergency dynamic weight, the communication demand information and the resource supply information are matched to obtain an initial scheduling scheme. The initial scheduling scheme includes the scheduling mapping relationship between the emergency communication equipment and the task point. The emergency dynamic weight is related to the emergency support stage and the real-time indicator value of the emergency communication equipment.

[0031] The generation module is used to generate an initial dispatch strategy based on the initial dispatch plan and real-time traffic information of the emergency area; the initial dispatch strategy includes the initial dispatch plan and the dispatch path corresponding to implementing the initial dispatch plan;

[0032] The optimization module is used to optimize the initial scheduling strategy based on a multi-objective optimization algorithm to obtain the target scheduling strategy.

[0033] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in embodiments of this application.

[0034] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in embodiments of this application.

[0035] Fifthly, embodiments of this application provide a computer program product, including a computer program, characterized in that, when the computer program is executed by a processor, it implements the method described in embodiments of this application.

[0036] The emergency communication equipment scheduling and management method and system proposed in this application obtains an initial scheduling scheme by matching the communication demand information of each task point and the resource supply information of each emergency communication equipment based on emergency dynamic weights. This effectively improves the matching degree between the initial scheduling scheme and the real-time data of the emergency communication equipment, thereby improving the reliability of the initial scheduling scheme and providing a reliable data foundation for subsequent target scheduling strategy optimization. Then, based on the initial scheduling scheme and the real-time road condition information of the emergency area, an initial scheduling strategy is generated, further ensuring the timeliness of the initial scheduling strategy. Finally, based on a multi-objective optimization algorithm, the initial scheduling strategy is optimized to obtain the target scheduling strategy, which can effectively balance the relationship between the scheduling strategy and the scheduling objective, while effectively ensuring the feasibility of updating the scheduling strategy.

[0037] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0038] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0039] Figure 1 A flowchart illustrating an embodiment of the emergency communication equipment dispatch and management method provided in this application is shown.

[0040] Figure 2 This invention provides a schematic diagram of the structure of an emergency communication equipment dispatch and management system according to an embodiment of the present application.

[0041] Figure 3 A schematic diagram of the structure of a computer system suitable for implementing an electronic device or server according to embodiments of this application is shown. Detailed Implementation

[0042] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0043] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0044] To further illustrate the technical solutions provided in the embodiments of this application, a detailed description is provided below in conjunction with the accompanying drawings and specific implementation methods. Although the embodiments of this application provide method operation instruction steps as shown in the following embodiments or drawings, the method may include more or fewer operation instruction steps based on conventional or non-creative effort. In steps where there is no logically necessary causal relationship, the execution order of these steps is not limited to the execution order provided in the embodiments of this application. In actual processing or when the device executes the method, it may be executed sequentially or in parallel according to the method shown in the embodiments or drawings.

[0045] It should be noted that the acquisition or use of data in the embodiments of this application requires the user's consent. The relevant data can only be obtained after the user's authorization, and the acquisition or use of the data complies with the provisions of relevant laws and regulations.

[0046] Please refer to Figure 1 , Figure 1 A flowchart illustrating an embodiment of the emergency communication equipment dispatch and management method provided in this application is shown. Figure 1 As shown, the method includes:

[0047] Step 101: Obtain communication demand information corresponding to each task point and resource supply information corresponding to each emergency communication equipment. Match the communication demand information and resource supply information based on emergency dynamic weights to obtain an initial scheduling plan. The initial scheduling plan includes the scheduling mapping relationship between emergency communication equipment and task points. The emergency dynamic weights are related to the emergency support phase and the real-time indicator values ​​of emergency communication equipment.

[0048] It should be noted that the task point is the location where emergency communication equipment needs to be deployed. The task point can be the direct site of the disaster or a surrounding area affected by the disaster; this application does not impose specific limitations. The communication requirement information corresponding to the task point can be the task point's requirements for multiple communication indicators, including but not limited to bandwidth requirements, coverage radius, and user capacity.

[0049] Emergency communication equipment can be any equipment that provides emergency communication capabilities, including but not limited to dual-mode satellite vehicles, large-beam satellite vehicles, large-beam portable satellite stations, spot-wave satellite vehicles, spot-wave portable satellite stations, Tiantong satellite phones, 800M walkie-talkies, 400M walkie-talkies, VHF portable base stations, VHF fixed base stations, and drones. Resource supply information corresponding to emergency communication equipment can refer to the availability of multiple communication indicators, including but not limited to the bandwidth provided by the equipment, maximum coverage radius, and maximum user capacity.

[0050] The initial scheduling scheme includes the scheduling mapping relationship between emergency communication equipment and task points. Specifically, the initial scheduling scheme is a matching scheme for scheduling emergency communication equipment to task points.

[0051] In a feasible embodiment, the communication demand information and resource supply information are matched based on emergency dynamic weights to obtain an initial scheduling scheme, including: determining the matching degree between the communication demand information corresponding to each task point and the resource supply information corresponding to each emergency communication equipment based on emergency dynamic weights; constructing a scheduling mapping relationship between the emergency communication equipment with the highest matching degree and the task point to obtain the initial scheduling scheme.

[0052] For example, the matching degree between the communication demand information corresponding to each task point and the resource supply information corresponding to each emergency communication equipment can be calculated using the following formula:

[0053]

[0054] in, Communication requirements information corresponding to the task points Resource supply information corresponding to emergency communication equipment The degree of matching between them , n is the number of evaluation indicators. , Let be the emergency dynamic weight corresponding to the i-th evaluation indicator.

[0055] In one feasible embodiment, the basic weights between emergency communication equipment and evaluation indicators are determined based on prior expert evaluation, real-time indicator data corresponding to the emergency communication equipment is obtained, and real-time correction weights corresponding to the emergency communication equipment are determined based on the real-time indicator data. The emergency support stage weights are determined based on the emergency support stage in which the emergency mission is located, and the emergency dynamic weights are determined based on the basic weights, real-time correction weights, and emergency support stage weights.

[0056] Specifically, experts can be organized to construct an expert evaluation system based on emergency communications, including indicators and their weights. Through expert evaluation, the fundamental weights between emergency communication equipment and the evaluation indicators can be determined. .

[0057] Then, during the application process, real-time indicator data corresponding to the emergency communication equipment is obtained in real time. For example, the real-time indicator data of the emergency communication equipment under the scheduling strategy in the environment can be used. For example, the real-time user capacity of a certain emergency communication equipment at a certain task point, the maximum actual coverage radius affected by the environment or other factors at that point, and the remaining battery life, etc.

[0058] In one feasible embodiment, determining the real-time correction weight corresponding to the emergency communication equipment based on real-time indicator data includes: calculating the real-time evaluation value of each evaluation indicator for each evaluation indicator, determining the real-time evaluation entropy of each evaluation indicator based on multiple emergency communication equipment, and determining the real-time correction weight based on the real-time evaluation entropy.

[0059] Specifically, assuming there are m emergency communication devices and n evaluation indicators, forming a matrix:

[0060]

[0061] in, Let m be the real-time indicator data of the j-th application communication device for the i-th evaluation indicator, m be the total number of emergency communication equipment, and n be the total number of evaluation indicators.

[0062] Then, the real-time evaluation value corresponding to the j-th emergency communication equipment under the i-th evaluation index is calculated using the following formula:

[0063]

[0064] in, This represents the real-time evaluation value corresponding to the j-th emergency communication equipment under the i-th evaluation indicator. This refers to the real-time indicator data of the j-th application communication device for the i-th evaluation indicator.

[0065] The real-time evaluation entropy of each evaluation indicator is determined using the following formula:

[0066]

[0067] in, Let i be the real-time evaluation entropy of the i-th evaluation index. Let be the real-time evaluation value corresponding to the j-th emergency communication equipment under the i-th evaluation index, m be the total number of emergency communication equipment, and k be the index correction coefficient.

[0068] Furthermore, based on the real-time evaluation entropy of the evaluation indicators, the real-time correction weights are determined:

[0069]

[0070] in, The real-time adjusted weight of the i-th evaluation indicator. Let be the real-time evaluation entropy of the i-th evaluation indicator, and n be the total number of evaluation indicators.

[0071] Finally, the weights of multiple evaluation indicators are combined into a real-time adjusted weight matrix. .

[0072] Furthermore, the emergency dynamic weights are determined using the following formula based on the base weights, real-time correction weights, and emergency support phase weights:

[0073]

[0074] in, For emergency dynamic weight matrix, Based on the weight matrix, To adjust the weight matrix in real time, Weighting for the emergency response phase.

[0075] Optional, emergency support phase weighting The weighting of the initial dispatch plan increases gradually with the time phase of the emergency response, for example, from the initial stage of emergency response to the middle stage of emergency response and the post-disaster recovery stage. In the initial stage of emergency response, the initial dispatch plan relies more on the objective weight of real-time data to cope with the real-time changes in the disaster situation. In the post-disaster recovery stage, the basic weighting relies more on the experience of experts to improve the stability of the initial dispatch plan and reduce the frequency of equipment dispatch in post-disaster emergency response.

[0076] Therefore, this application embodiment dynamically corrects the matching relationship between emergency communication equipment and task points by utilizing real-time indicator data of emergency communication equipment, making full use of the real-time differences of different emergency communication equipment in different environments, thereby achieving adaptive adjustment of weights, highlighting the scarce and critical capabilities of emergency communication equipment, and thus achieving a more accurate and adaptive matching relationship between emergency communication equipment and task points.

[0077] Step 102: Based on the initial scheduling plan and the real-time traffic information of the emergency area, generate the initial scheduling strategy; the initial scheduling strategy includes the initial scheduling plan and the scheduling path corresponding to the implementation of the initial scheduling plan.

[0078] In a feasible embodiment, an initial scheduling strategy is generated based on the initial scheduling scheme and real-time traffic information of the emergency area, including: obtaining at least one candidate scheduling path corresponding to the initial scheduling scheme; for each candidate scheduling path, obtaining the length, maximum speed limit, real-time congestion coefficient and damage status of the candidate scheduling path; determining the scheduling cost evaluation value of the candidate scheduling path based on the length, maximum speed limit, real-time congestion coefficient and damage status of the candidate scheduling path; and selecting the candidate scheduling path with the smallest scheduling cost evaluation value as the scheduling path corresponding to the initial scheduling scheme.

[0079] For example, the scheduling cost evaluation value is calculated using the following formula:

[0080]

[0081] in, Let e ​​be the estimated scheduling cost for candidate scheduling path e. Let e ​​be the length of the candidate scheduling path. The maximum speed limit for candidate scheduling path e. Let e ​​be the real-time congestion coefficient of the candidate scheduling path. For the damage status of candidate scheduling path e, It is 0 or 1. , , These are the weighting coefficients.

[0082] Step 103: Based on the multi-objective optimization algorithm, optimize the initial scheduling strategy to obtain the target scheduling strategy.

[0083] It should be noted that the initial scheduling strategy includes scheduling strategies for multiple emergency communication devices. In other words, an initial scheduling strategy includes the complete scheduling strategy for multiple emergency communication devices at the current moment, including the task points and scheduling paths to which the multiple emergency communication devices need to be scheduled.

[0084] In a feasible embodiment, the initial scheduling strategy is optimized based on a multi-objective optimization algorithm to obtain a target scheduling strategy, including: constructing an objective function corresponding to the optimization strategy based on each task point and emergency communication equipment; the objective function includes total response time, total scheduling cost and total coverage defect; and performing non-dominated sorting genetic optimization based on congestion constraints on the initial scheduling strategy based on the objective function to obtain the target scheduling strategy.

[0085] Specifically, the initial scheduling policy can be expressed as: , This is a binary variable representing whether the j-th emergency communication device has been dispatched to the mission point. , =0 indicates that the j-th emergency communication equipment has not been dispatched to the mission point. , =1 indicates that the j-th emergency communication equipment has been dispatched to the mission point. .

[0086] Based on this, the objective function can be expressed as:

[0087]

[0088]

[0089]

[0090] in, Let the objective function be the total response time. Let the objective function be the total scheduling cost. Let the objective function be the total coverage defect. The j-th emergency communication device was dispatched to the mission point. Response time The j-th emergency communication device was dispatched to the mission point. scheduling costs, For the coverage capability of the j-th emergency communication equipment, For the task point The coverage requirements.

[0091] In a feasible embodiment, based on the objective function, the initial scheduling strategy is subjected to non-dominated sorting genetic optimization based on congestion constraints, including: for each initial scheduling strategy, determining the objective function value corresponding to the initial scheduling strategy; based on the objective function value, performing non-dominated sorting on the initial scheduling strategies to obtain non-dominated front scheduling strategies; using the non-dominated front scheduling strategies as the genetic parent scheduling strategies of the current iteration round; for each non-dominated front scheduling strategy, calculating the congestion degree corresponding to the non-dominated front scheduling strategy; selecting non-dominated front scheduling strategies whose congestion degree meets a preset condition, performing genetic iteration to obtain candidate scheduling strategies for the next iteration round; performing non-dominated sorting on the candidate scheduling strategies to obtain non-dominated front scheduling strategies for the next iteration round, and so on until a preset exit condition is met.

[0092] It should be noted that a non-dominated front scheduling strategy is a scheduling strategy with a high non-dominated level. There can be multiple non-dominated front scheduling strategies, which may belong to the same non-dominated level or to a predetermined number of non-dominated levels. The non-dominated level represents the overall superiority level of a scheduling strategy. For example, if every objective function value of one scheduling strategy is higher than that of another scheduling strategy, then the non-dominated level of that scheduling strategy is higher than that of the other scheduling strategy. All scheduling strategies that are not dominated by any other scheduling strategy constitute the highest-level non-dominated front scheduling strategy. Non-dominated front scheduling strategies can come from the highest N non-dominated levels.

[0093] Crowding degree represents the density between a scheduling strategy and its neighboring scheduling strategies in the objective function space. If a scheduling strategy is relatively "sparsely populated," it indicates that it corresponds to a unique trade-off. Based on this, in this embodiment, scheduling strategies with high crowding degree are preferentially retained, thereby ensuring the diversity of scheduling strategy implementation possibilities and providing a basis for updating the target scheduling strategy based on the current target scheduling strategy in later time. At the same time, it can also effectively avoid concentrating scheduling strategies in a certain target direction during the genetic process and losing other valuable solutions, such as scheduling strategies that are slightly slower but have significantly lower costs.

[0094] For example, the congestion level can be calculated using the following formula:

[0095]

[0096] in, The congestion level corresponding to scheduling strategy D. and Let be the values ​​of the u-th objective function of the two adjacent scheduling strategies D, and let be the maximum and minimum values ​​of the u-th objective function in the non-dominated front scheduling strategy, where u = 1, 2, 3.

[0097] It should also be noted that the preset exit condition can be that the range of change of the objective function value corresponding to the highest non-dominated level in multiple consecutive genetic iteration rounds is less than the preset error, or that the number of genetic iterations meets the preset number of iterations.

[0098] Therefore, this application utilizes non-dominated sorting genetic optimization based on congestion constraints to find the target scheduling strategy from the initial scheduling strategy. This allows the target scheduling strategy to fully consider the target constraints required at the current time point, achieving a comprehensive goal of speed, quality, and cost-effectiveness. At the same time, it can ensure the amount of space between scheduling strategies, thereby effectively addressing the need to update the scheduling strategy based on new real-time indicator data in later times. This also allows for the derivation of new target scheduling strategies that meet new requirements from the currently executed target scheduling strategy.

[0099] In summary, the emergency communication equipment scheduling and management method proposed in this application matches the communication demand information of each task point with the resource supply information of each emergency communication equipment based on emergency dynamic weights to obtain an initial scheduling scheme. This effectively improves the matching degree between the initial scheduling scheme and the real-time data of the emergency communication equipment, thereby improving the reliability of the initial scheduling scheme and providing a reliable data foundation for subsequent target scheduling strategy optimization. Then, based on the initial scheduling scheme and the real-time road condition information of the emergency area, an initial scheduling strategy is generated, further ensuring the timeliness of the initial scheduling strategy. Finally, based on a multi-objective optimization algorithm, the initial scheduling strategy is optimized to obtain the target scheduling strategy, which can effectively balance the relationship between the scheduling strategy and the scheduling objective, while effectively ensuring the feasibility of updating the scheduling strategy.

[0100] It should be noted that although the operation of the method of the present invention is described in a specific order in the accompanying drawings, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed in order to achieve the desired result.

[0101] Figure 2 A schematic diagram of the structure of an emergency communication equipment dispatch and management system provided in an embodiment of this application is shown.

[0102] like Figure 2 As shown, the emergency communication equipment dispatch and management system 10 includes:

[0103] The matching module 11 is used to obtain communication demand information corresponding to each task point and resource supply information corresponding to each emergency communication equipment, and to match the communication demand information and the resource supply information based on emergency dynamic weights to obtain an initial scheduling scheme; the initial scheduling scheme includes the scheduling mapping relationship between the emergency communication equipment and the task point; the emergency dynamic weights are related to the emergency support stage and the real-time indicator values ​​of the emergency communication equipment.

[0104] The generation module 12 is used to generate an initial scheduling strategy based on the initial scheduling scheme and real-time traffic information of the emergency area; the initial scheduling strategy includes the initial scheduling scheme and the scheduling path corresponding to implementing the initial scheduling scheme;

[0105] The optimization module 13 is used to optimize the initial scheduling strategy based on a multi-objective optimization algorithm to obtain the target scheduling strategy.

[0106] In some embodiments, the matching module 11 is further configured to:

[0107] The basic weights between the emergency communication equipment and the evaluation indicators are determined based on prior expert assessments.

[0108] Obtain real-time indicator data corresponding to the emergency communication equipment, and determine the real-time correction weight corresponding to the emergency communication equipment based on the real-time indicator data;

[0109] The weight of each emergency support phase is determined based on the emergency support phase in which the emergency mission is located.

[0110] The emergency dynamic weight is determined based on the basic weight, the real-time correction weight, and the emergency support phase weight.

[0111] In some embodiments, the matching module 11 is further configured to:

[0112] For each evaluation indicator, calculate the real-time evaluation value for each evaluation indicator;

[0113] Based on the various emergency communication devices mentioned above, determine the real-time evaluation entropy of each evaluation indicator;

[0114] The real-time correction weight is determined based on the real-time evaluation entropy.

[0115] In some embodiments, the initial scheduling strategy includes a scheduling strategy for multiple emergency communication devices, and the optimization module 13 is specifically used for:

[0116] Based on each of the aforementioned task points and the aforementioned emergency communication equipment, an objective function corresponding to the optimization strategy is constructed; the objective function includes total response time, total scheduling cost, and total coverage defect.

[0117] Based on the objective function, the initial scheduling strategy is subjected to non-dominated sorting genetic optimization based on congestion constraints to obtain the target scheduling strategy.

[0118] In some embodiments, the optimization module 13 is specifically used for:

[0119] For each of the initial scheduling strategies, determine the objective function value corresponding to the initial scheduling strategy;

[0120] Based on the objective function value, the initial scheduling strategy is sorted non-dominated to obtain a non-dominated front scheduling strategy, which is then used as the genetic parent scheduling strategy for the current iteration round.

[0121] For each of the non-dominated front scheduling strategies, calculate the congestion degree corresponding to the non-dominated front scheduling strategy;

[0122] Select the non-dominated front scheduling strategy that meets the preset congestion condition, perform genetic iteration, and obtain the candidate scheduling strategy for the next iteration round;

[0123] The candidate scheduling strategies are sorted by non-dominated order to obtain the non-dominated front scheduling strategy for the next iteration round, and so on until the preset exit condition is met.

[0124] In some embodiments, the optimization module 13 is specifically used for:

[0125] The congestion level is determined based on the distance between the non-dominated front scheduling strategies.

[0126] It should be understood that the modules or modules recorded in the Emergency Communication Equipment Dispatch and Management System 10 are similar to those in the reference. Figure 1 The steps in the described method correspond accordingly. Therefore, the operations and features described above for the method also apply to the emergency communication equipment dispatch management system 10 and its included modules, and will not be repeated here. The emergency communication equipment dispatch management system 10 can be pre-implemented in the browser or other security applications of an electronic device, or it can be loaded into the browser or its security applications of an electronic device through download or other means. The corresponding modules in the emergency communication equipment dispatch management system 10 can cooperate with the modules in the electronic device to implement the solutions of the embodiments of this application.

[0127] The division of modules or units mentioned in the detailed description above is not mandatory. In fact, according to the embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0128] The following is for reference.Figure 3 , Figure 3 A schematic diagram of the structure of a computer system suitable for implementing the embodiments of this application is shown.

[0129] like Figure 3 As shown, the computer system 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 302 or programs loaded from storage section 308 into random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the system's operating instructions. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0130] The following components are connected to I / O interface 305: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0131] Specifically, according to embodiments of this application, the flowchart above refers to... Figure 2 The described process can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such an embodiment, the computer program contains program code for performing the methods shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the functions defined in the system of this application.

[0132] It should be noted that the computer-readable medium shown in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0133] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operational instructions of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two connected blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified functions or operational instructions, or using a combination of dedicated hardware and computer instructions.

[0134] In another aspect, this application also provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiments, or may exist independently and not assembled into the electronic device. The aforementioned computer-readable storage medium stores one or more programs that, when used by one or more processors, execute the emergency communication equipment scheduling and management method described in this application.

[0135] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing disclosed concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for dispatching and managing emergency communication equipment, characterized in that, include: The system acquires communication demand information for each task point and resource supply information for each emergency communication device. Based on emergency dynamic weights, it matches the communication demand information and resource supply information to obtain an initial scheduling scheme. The initial scheduling scheme includes the scheduling mapping relationship between the emergency communication devices and the task points. The emergency dynamic weights are related to the emergency support phase and the real-time indicator values ​​of the emergency communication devices. The resource supply information refers to the supply status of multiple communication indicators by the emergency communication devices. The real-time indicator values ​​are the real-time indicator data that the emergency communication devices can perform in the environment under the scheduling strategy, including the real-time user capacity of the emergency communication devices at the task point, the maximum actual coverage radius affected by environmental or other factors at that location, and the remaining battery life. Based on the initial scheduling scheme and real-time traffic information of the emergency area, an initial scheduling strategy is generated; The initial scheduling strategy includes the initial scheduling scheme and the scheduling path corresponding to implementing the initial scheduling scheme; The initial scheduling strategy is optimized based on a multi-objective optimization algorithm to obtain the target scheduling strategy. The initial scheduling strategy includes scheduling strategies for multiple emergency communication equipment. The optimization of the initial scheduling strategy based on a multi-objective optimization algorithm to obtain the target scheduling strategy includes: Based on each of the aforementioned task points and the aforementioned emergency communication equipment, an objective function corresponding to the optimization strategy is constructed; the objective function includes total response time, total scheduling cost, and total coverage defect. Based on the objective function, the initial scheduling strategy is subjected to non-dominated sorting genetic optimization based on congestion constraints to obtain the target scheduling strategy. The step of performing non-dominated sorting genetic optimization of the initial scheduling strategy based on the objective function includes: For each of the initial scheduling strategies, determine the objective function value corresponding to the initial scheduling strategy; Based on the objective function value, the initial scheduling strategy is sorted non-dominated to obtain a non-dominated front scheduling strategy, which is then used as the genetic parent scheduling strategy for the current iteration round. For each of the non-dominated front scheduling strategies, calculate the congestion degree corresponding to the non-dominated front scheduling strategy; The non-dominated front scheduling strategy that meets the preset congestion condition is selected and subjected to genetic iteration to obtain candidate scheduling strategies for the next iteration round; wherein, the scheduling strategy with high congestion is retained. The candidate scheduling strategies are sorted by non-dominated order to obtain the non-dominated front scheduling strategy for the next iteration round, and so on until the preset exit condition is met. The congestion level is calculated using the following formula: in, The congestion level corresponding to scheduling strategy D. and Let be the values ​​of the u-th objective function of the two adjacent scheduling strategies D, and let be the maximum and minimum values ​​of the u-th objective function in the non-dominated front scheduling strategy, where u = 1, 2, 3.

2. The emergency communication equipment dispatch and management method according to claim 1, characterized in that, Also includes: The basic weights between the emergency communication equipment and the evaluation indicators are determined based on prior expert assessments. Obtain real-time indicator data corresponding to the emergency communication equipment, and determine the real-time correction weight corresponding to the emergency communication equipment based on the real-time indicator data; The weight of each emergency support phase is determined based on the emergency support phase in which the emergency mission is located. The emergency dynamic weight is determined based on the basic weight, the real-time correction weight, and the emergency support phase weight.

3. The emergency communication equipment dispatch and management method according to claim 2, characterized in that, The step of determining the real-time correction weight corresponding to the emergency communication equipment based on the real-time indicator data includes: For each of the evaluation indicators, calculate the real-time evaluation value for each of the evaluation indicators; Based on the various emergency communication devices mentioned above, determine the real-time evaluation entropy of each evaluation indicator; The real-time correction weight is determined based on the real-time evaluation entropy.

4. An emergency communication equipment dispatch and management system, characterized in that, include: The matching module is used to obtain communication demand information corresponding to each task point and resource supply information corresponding to each emergency communication equipment. Based on emergency dynamic weights, the communication demand information and resource supply information are matched to obtain an initial scheduling scheme. The initial scheduling scheme includes the scheduling mapping relationship between the emergency communication equipment and the task points. The emergency dynamic weights are related to the emergency support phase and the real-time indicator values ​​of the emergency communication equipment. The resource supply information refers to the supply status of multiple communication indicators by the emergency communication equipment. The real-time indicator values ​​are the real-time indicator data that the emergency communication equipment can perform in the environment under the scheduling strategy, including the real-time user capacity of the emergency communication equipment at the task point, the maximum actual coverage radius affected by environmental or other factors at that location, and the remaining battery life. The generation module is used to generate an initial scheduling strategy based on the initial scheduling scheme and real-time traffic information of the emergency area; The initial scheduling strategy includes the initial scheduling scheme and the scheduling path corresponding to implementing the initial scheduling scheme; The optimization module is used to optimize the initial scheduling strategy based on a multi-objective optimization algorithm to obtain the target scheduling strategy. The initial scheduling strategy includes scheduling strategies for multiple emergency communication equipment. The optimization of the initial scheduling strategy based on a multi-objective optimization algorithm to obtain the target scheduling strategy includes: Based on each of the aforementioned task points and the aforementioned emergency communication equipment, an objective function corresponding to the optimization strategy is constructed; the objective function includes total response time, total scheduling cost, and total coverage defect. Based on the objective function, the initial scheduling strategy is subjected to non-dominated sorting genetic optimization based on congestion constraints to obtain the target scheduling strategy. The step of performing non-dominated sorting genetic optimization of the initial scheduling strategy based on the objective function includes: For each of the initial scheduling strategies, determine the objective function value corresponding to the initial scheduling strategy; Based on the objective function value, the initial scheduling strategy is sorted non-dominated to obtain a non-dominated front scheduling strategy, which is then used as the genetic parent scheduling strategy for the current iteration round. For each of the non-dominated front scheduling strategies, calculate the congestion degree corresponding to the non-dominated front scheduling strategy; The non-dominated front scheduling strategy that meets the preset congestion condition is selected and subjected to genetic iteration to obtain candidate scheduling strategies for the next iteration round; wherein, the scheduling strategy with high congestion is retained. The candidate scheduling strategies are sorted by non-dominated order to obtain the non-dominated front scheduling strategy for the next iteration round, and so on until the preset exit condition is met. The congestion level is calculated using the following formula: in, The congestion level corresponding to scheduling strategy D. and Let be the values ​​of the u-th objective function of the two adjacent scheduling strategies D, and let be the maximum and minimum values ​​of the u-th objective function in the non-dominated front scheduling strategy, where u = 1, 2, 3.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the emergency communication equipment scheduling and management method as described in any one of claims 1-3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the emergency communication equipment scheduling and management method as described in any one of claims 1-3.

7. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the emergency communication equipment scheduling and management method as described in any one of claims 1-3.

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