Emergency communication equipment scheduling management method and system

Abstract

The invention relates to the technical field of scheduling management, and discloses an emergency communication equipment scheduling management method and system, and the method comprises the steps: obtaining communication demand information corresponding to each task point and resource supply information corresponding to each emergency communication equipment, and carrying out the matching of the communication demand information and the resource supply information based on an emergency dynamic weight, obtaining an initial scheduling scheme; generating an initial scheduling strategy based on the initial scheduling scheme and the real-time road condition information of the emergency area; the initial scheduling strategy comprises the initial scheduling scheme and a scheduling path corresponding to implementation of the initial scheduling scheme; based on a multi-objective optimization algorithm, the initial scheduling strategy is optimized to obtain a target scheduling strategy, a reasonable emergency communication equipment scheduling strategy can be determined in real time according to the communication demand information of the task point and the resource supply information of the emergency communication equipment, and the real-time performance and reliability of emergency scheduling are improved.

Description

Technical Field

[0001] The present disclosure generally relates to the field of dispatching management technology, and in particular to a dispatching management method and system for emergency communication equipment. Background Art

[0002] As my country's requirements for emergency support increase, relevant technologies have provided an emergency communication command system, with the goal of "one map for emergency communications" to achieve "one network access, one screen for overall control, and one-click dispatch" for emergency communication equipment, so that in the event of major disasters, the emergency command center can directly connect to the rescue front line, grasp the location of production and repair personnel and equipment status information in real time, and ensure that communication information and repair personnel are "dual-online".

[0003] However, although the existing technology has achieved the purpose of information centralization and unified scheduling through the "one map for emergency communications", there are complex problems in the scheduling of emergency communication equipment. For example, due to the problems of multi-source heterogeneity of communication equipment, multi-department cooperation, and multi-task collaboration in emergency support, there are problems such as low efficiency of manual coordination, cumbersome processes, and easy errors. Summary of the Invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desired to provide an emergency communication equipment scheduling management method and system that can determine a reasonable emergency communication equipment scheduling strategy in real time based on the communication demand information of the task point and the resource supply information of the emergency communication equipment, thereby improving the real-time and reliability of emergency scheduling.

[0005] In a first aspect, an embodiment of the present application provides a method for dispatching and managing emergency communication equipment, including: 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 emergency dynamic weights to obtain an initial scheduling plan; the initial scheduling plan includes a scheduling mapping relationship between the emergency communication equipment and the task points; the emergency dynamic weights are related to the emergency support stage and the real-time indicator values ​​of the emergency communication equipment; generating an initial scheduling strategy based on the initial scheduling plan and real-time traffic information of the emergency area; the initial scheduling strategy includes the initial scheduling plan and a scheduling path corresponding to the implementation of the initial scheduling plan; Based on a multi-objective optimization algorithm, the initial scheduling strategy is optimized to obtain a target scheduling strategy.

[0006] In some embodiments, it further includes: Determining the basic weights between the emergency communication equipment and the evaluation indicators based on prior expert evaluations; Acquiring real-time indicator data corresponding to the emergency communication equipment, and determining a real-time correction weight corresponding to the emergency communication equipment according to the real-time indicator data; Determine the weight of the emergency support stage according to the emergency support stage of the emergency task; The emergency dynamic weight is determined according to the basic weight, the real-time correction weight and the emergency guarantee stage weight.

[0007] In some embodiments, determining the real-time correction weight corresponding to the emergency communication equipment according to the real-time indicator data includes: For each evaluation indicator, calculating a real-time evaluation value of each evaluation indicator; Determining a real-time evaluation entropy of each evaluation indicator based on the plurality of emergency communication equipment; The real-time correction weight is determined according to the real-time evaluation entropy.

[0008] In some embodiments, the initial scheduling strategy includes scheduling strategies for multiple emergency communication equipment, and optimizing the initial scheduling strategy based on a multi-objective optimization algorithm to obtain a target scheduling strategy includes: Based on each of the task points and the emergency communication equipment, construct an objective function corresponding to the optimization strategy; 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.

[0009] In some embodiments, performing a non-dominated sorting genetic optimization based on a congestion constraint on the initial scheduling strategy based on the objective function includes: For each of the initial scheduling strategies, determining an objective function value corresponding to the initial scheduling strategy; Based on the objective function value, the initial scheduling strategy is non-dominated sorted to obtain a non-dominated frontier scheduling strategy, and the non-dominated frontier scheduling strategy is used as the inherited parent scheduling strategy of the current iteration round; For each of the non-dominated front scheduling strategies, calculating the congestion degree corresponding to the non-dominated front scheduling strategy; Selecting the non-dominated frontier scheduling strategy whose congestion degree meets the preset conditions, performing genetic iteration, and obtaining a candidate scheduling strategy for the next iteration round; Perform non-dominated sorting on the candidate scheduling strategies to obtain the non-dominated frontier scheduling strategy for the next iteration round, and so on until the preset exit condition is met.

[0010] In some embodiments, further comprising: The congestion degree is determined according to the distance between the non-dominated front scheduling strategies.

[0011] In a second aspect, an embodiment of the present application provides an emergency communication equipment dispatching and management system, including: A matching module is configured to obtain communication demand information corresponding to each task point and resource supply information corresponding to each emergency communication equipment, and 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 a scheduling mapping relationship between the emergency communication equipment and the task points; the emergency dynamic weights are related to the emergency support stage and the real-time indicator values ​​of the emergency communication equipment; A generation module, configured to generate an initial scheduling strategy based on the initial scheduling plan and real-time traffic information of the emergency area; the initial scheduling strategy includes the initial scheduling plan and a scheduling path corresponding to the implementation of the initial scheduling plan; The optimization module is used to optimize the initial scheduling strategy based on a multi-objective optimization algorithm to obtain a target scheduling strategy.

[0012] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the embodiment of the present application when executing the program.

[0013] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored, which, when executed by a processor, implements the method described in the embodiment of the present application.

[0014] In a fifth aspect, an embodiment of the present application provides 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 the embodiment of the present application.

[0015] The emergency communication equipment scheduling management method and system proposed in the embodiment of the present application obtain an initial scheduling plan 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, thereby effectively improving the matching degree between the initial scheduling plan and the real-time data of the emergency communication equipment, thereby improving the reliability of the initial scheduling plan and providing a reliable data basis for the subsequent target scheduling strategy optimization; then, based on the initial scheduling plan 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 the 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 target, and at the same time effectively ensure the feasibility of the scheduling strategy update.

[0016] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Other features, objects and advantages of the present application will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1 A flow chart of a method for dispatching and managing emergency communication equipment provided by an embodiment of the present application is shown; Figure 2 A schematic diagram of the structure of an emergency communication equipment dispatching and management system provided in one embodiment of the present application is shown; Figure 3 A schematic diagram of the structure of a computer system of an electronic device or server suitable for implementing an embodiment of the present application is shown. DETAILED DESCRIPTION

[0018] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the invention are shown in the accompanying drawings.

[0019] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0020] In order to further illustrate the technical solutions provided by the embodiments of the present application, this is described in detail below with reference to the accompanying drawings and specific embodiments. Although the embodiments of the present application provide the method operation instruction steps shown in the following embodiments or drawings, more or fewer operation instruction steps may be included in the method based on conventional or no creative labor. In the steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided by the embodiments of the present application. The method may be executed in the order of the methods shown in the embodiments or drawings or in parallel during the actual processing process or when the device is executed.

[0021] 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 permission, and the acquisition or use of the data complies with the provisions of relevant laws and regulations.

[0022] Please refer to Figure 1 , Figure 1 FIG. 1 shows a flow chart of a method for dispatching and managing emergency communication equipment provided by an embodiment of the present application. Figure 1 As shown, the method includes: Step 101: obtain the communication demand information corresponding to each task point and the resource supply information corresponding to each emergency communication equipment, match the communication demand information and resource supply information based on the emergency dynamic weight, and obtain an initial scheduling plan; the initial scheduling plan includes the scheduling mapping relationship between the emergency communication equipment and the task point; the emergency dynamic weight is related to the real-time indicator value of the emergency support stage and the emergency communication equipment.

[0023] It should be noted that a mission point is a location where emergency communication equipment needs to be deployed. The mission point can be the direct site of the disaster or a surrounding area affected by the disaster, and this application does not impose specific restrictions. The communication demand information corresponding to the mission point can be the mission point's demand for multiple communication indicators, including but not limited to required bandwidth, coverage radius, user capacity, etc.

[0024] Emergency communication equipment may be 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, ultra-short wave portable base stations, ultra-short wave fixed base stations, drones, etc. The resource supply information corresponding to emergency communication equipment may include the supply status of multiple communication indicators provided by the emergency communication equipment, including but not limited to the bandwidth provided by the equipment, maximum coverage radius, and maximum user capacity.

[0025] The initial scheduling plan includes a scheduling mapping relationship between emergency communication equipment and task points. Specifically, the initial scheduling plan is a matching plan for scheduling emergency communication equipment to the task points.

[0026] In a feasible embodiment, communication demand information and resource supply information are matched based on emergency dynamic weights to obtain an initial scheduling plan, including: based on the emergency dynamic weights, 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, constructing a scheduling mapping relationship between the emergency communication equipment with the highest matching degree and the task point, and obtaining an initial scheduling plan.

[0027] For example, the following formula may be used to calculate the matching degree between the communication demand information corresponding to each task point and the resource supply information corresponding to each emergency communication equipment:

[0028] in, Communication demand information corresponding to the task point Resource supply information corresponding to emergency communication equipment The matching degree between , , n is the number of evaluation indicators, , is the emergency dynamic weight corresponding to the i-th evaluation index.

[0029] In a feasible embodiment, the basic weight between the emergency communication equipment and the evaluation index is determined based on the prior expert evaluation, the real-time index data corresponding to the emergency communication equipment is obtained, and the real-time correction weight corresponding to the emergency communication equipment is determined based on the real-time index data. The emergency support stage weight is determined according to the emergency support stage of the emergency task, and the emergency dynamic weight is determined based on the basic weight, the real-time correction weight and the emergency support stage weight.

[0030] Specifically, experts can be organized to build an expert evaluation system based on emergency communications, including emergency communications indicators and indicator weights, and the basic weights between emergency communications equipment and evaluation indicators can be determined through expert evaluation. .

[0031] Then, during the application process, real-time indicator data corresponding to the emergency communication equipment is obtained in real time, such as the real-time indicator data that each emergency communication equipment can play in the environment under the scheduling strategy. 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 location, and the remaining battery life, etc.

[0032] In a feasible embodiment, the real-time correction weight corresponding to the emergency communication equipment is determined based on the real-time indicator data, including: 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.

[0033] Specifically, assuming there are m emergency communication equipment and n evaluation indicators, a matrix is ​​formed:

[0034] in, is the real-time indicator data of the jth application communication equipment of the ith evaluation indicator, m is the total number of emergency communication equipment, and n is the total number of evaluation indicators.

[0035] Then, the real-time evaluation value corresponding to the jth emergency communication equipment under the i-th evaluation index is calculated using the following formula:

[0036] in, is the real-time evaluation value corresponding to the jth emergency communication equipment under the i-th evaluation index, It is the real-time indicator data of the j-th application communication device of the i-th evaluation indicator.

[0037] The following formula is used to determine the real-time evaluation entropy of each evaluation indicator:

[0038] in, is the real-time evaluation entropy of the i-th evaluation index, is the real-time evaluation value corresponding to the jth emergency communication equipment under the i-th evaluation index, m is the total number of emergency communication equipment, and k is the index correction coefficient.

[0039] Furthermore, the real-time correction weight is determined based on the real-time evaluation entropy of the evaluation index:

[0040] in, is the real-time correction weight of the i-th evaluation index, is the real-time evaluation entropy of the i-th evaluation indicator, and n is the total number of evaluation indicators.

[0041] Finally, the weights of multiple evaluation indicators are combined into a real-time correction weight matrix .

[0042] Then, the following formula is used to determine the emergency dynamic weight based on the basic weight, real-time correction weight and emergency support stage weight:

[0043] in, is the emergency dynamic weight matrix, is the basic weight matrix, To modify the weight matrix in real time, It is the weight of the emergency support stage.

[0044] Optional, emergency support stage weight It gradually increases with the time stage of the emergency disaster, for example, the early stage of emergency response < the middle stage of emergency disposal < the post-disaster recovery period, so that the initial scheduling plan is more dependent on the objective weight of real-time data in the early stage of emergency response to cope with the real-time variability of the disaster situation, and more dependent on the basic weight of expert experience in the post-disaster recovery period to improve the stability of the initial scheduling plan and reduce the frequency of post-disaster emergency equipment scheduling.

[0045] Therefore, the embodiment of the present application dynamically corrects the matching relationship between emergency communication equipment and task points by utilizing the 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 realizing adaptive adjustment of weights, highlighting the scarce and critical capabilities of emergency communication equipment, and thus realizing a more accurate and adaptive matching relationship between emergency communication equipment and task points.

[0046] Step 102: Generate an initial scheduling strategy based on the initial scheduling plan and real-time traffic information of the emergency area; the initial scheduling strategy includes the initial scheduling plan and a scheduling path corresponding to the implementation of the initial scheduling plan.

[0047] In a feasible embodiment, an initial scheduling strategy is generated based on the initial scheduling plan and real-time traffic information of the emergency area, including: obtaining at least one candidate scheduling path corresponding to the initial scheduling plan, and for each candidate scheduling path, obtaining the length, maximum speed limit, real-time congestion coefficient and damage condition 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 condition of the candidate scheduling path, and taking the candidate scheduling path with the smallest scheduling cost evaluation value as the scheduling path corresponding to the initial scheduling plan.

[0048] For example, the scheduling cost evaluation value is calculated using the following formula:

[0049] in, is the scheduling cost evaluation value corresponding to the candidate scheduling path e, is the length of the candidate scheduling path e, is the maximum speed limit of candidate scheduling path e, is the real-time congestion coefficient of the candidate scheduling path e, is the damage condition of candidate scheduling path e, is 0 or 1, 、 、 is the weight coefficient.

[0050] Step 103: Optimize the initial scheduling strategy based on a multi-objective optimization algorithm to obtain a target scheduling strategy.

[0051] It should be noted that the initial scheduling strategy includes scheduling strategies for multiple emergency communication equipment. In other words, an initial scheduling strategy includes the complete scheduling strategy for multiple emergency communication equipment at the current moment, that is, including the task points and scheduling paths to which multiple emergency communication equipment need to be scheduled.

[0052] 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 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.

[0053] Specifically, the initial scheduling strategy can be expressed as , is a binary variable indicating whether the jth emergency communication equipment is dispatched to the mission point , =0 means the jth emergency communication equipment has not been dispatched to the mission point , =1 means the jth emergency communication equipment is dispatched to the mission point .

[0054] Based on this, the objective function can be expressed as:

[0055]

[0056]

[0057] in, is the objective function corresponding to the total response time, is the objective function corresponding to the total scheduling cost, is the objective function corresponding to the total coverage defect, The jth emergency communication equipment is dispatched to the mission point Response time, The jth emergency communication equipment is dispatched to the mission point The scheduling cost, is the coverage capability of the jth emergency communication equipment, For mission points coverage needs.

[0058] 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 strategy to obtain a non-dominated frontier scheduling strategy; using the non-dominated frontier scheduling strategy as the genetic parent scheduling strategy of the current iteration round; for each non-dominated frontier scheduling strategy, calculating the congestion corresponding to the non-dominated frontier scheduling strategy; selecting a non-dominated frontier scheduling strategy whose congestion meets a preset condition, performing genetic iteration, and obtaining a candidate scheduling strategy for the next iteration round; performing non-dominated sorting on the candidate scheduling strategies to obtain a non-dominated frontier scheduling strategy for the next iteration round, and so on until a preset exit condition is met.

[0059] It should be noted that a non-dominated frontier scheduling strategy is a scheduling strategy with a higher non-dominated level. There are multiple non-dominated frontier scheduling strategies, which can belong to the same non-dominated level or to a preset number of non-dominated levels. The non-dominated level is the overall superiority level of the scheduling strategy. For example, if each objective function value of a scheduling strategy is higher than that of another scheduling strategy, then the non-dominated level of the 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 frontier scheduling strategy. The non-dominated frontier scheduling strategy can come from the highest N non-dominated levels.

[0060] The congestion degree indicates the density between a certain scheduling strategy and its adjacent scheduling strategies in the objective function space. If a certain scheduling strategy is relatively "empty" around it, it means that it corresponds to a unique trade-off orientation. Based on this, in the embodiment of the present application, scheduling strategies with high congestion are retained first, thereby ensuring the diversity of scheduling strategy implementation possibilities and providing a basis for updating new target scheduling strategies based on the current target scheduling strategy at a later time. At the same time, it can also effectively avoid concentrating scheduling strategies on a certain target direction during the inheritance process and losing other valuable solutions, such as losing scheduling strategies that are slightly slower in time but greatly reduce costs.

[0061] For example, the congestion degree can be calculated using the following formula:

[0062] in, is the congestion degree corresponding to scheduling strategy D, and is the value of the u-th objective function of the two adjacent scheduling strategies of scheduling strategy D, is the maximum and minimum value of the u-th objective function in the non-dominated frontier scheduling strategy, u=1, 2, 3.

[0063] It should also be noted that the preset exit condition can be that the variation range of the objective function value corresponding to the highest non-dominated level in multiple consecutive genetic iteration rounds is less than a preset error, or the number of genetic iterations meets the preset number of iterations.

[0064] Therefore, the present application utilizes non-dominated sorting genetic optimization based on congestion constraints to find the target scheduling strategy from the initial scheduling strategy, so that the target scheduling strategy can fully take into account the target constraints required by the current time node, and achieve the comprehensive goals of fast, good, and economical. At the same time, it can ensure the amount of space between scheduling strategies, so as to effectively respond to the demand for scheduling strategy updates based on new real-time indicator data in the future, that is, to derive a new target scheduling strategy that meets new needs from the currently executed target scheduling strategy.

[0065] To sum up, the emergency communication equipment scheduling management method proposed in the embodiment of the present application obtains an initial scheduling plan 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, thereby effectively improving the matching degree between the initial scheduling plan and the real-time data of the emergency communication equipment, thereby improving the reliability of the initial scheduling plan and providing a reliable data basis for the subsequent target scheduling strategy optimization; then, based on the initial scheduling plan 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 the 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 target, and at the same time effectively ensure the feasibility of the scheduling strategy update.

[0066] It should be noted that although the operations of the present method are described in a particular order in the drawings, this does not require or imply that the operations must be performed in this particular order, or that all illustrated operations must be performed to achieve desirable results.

[0067] Figure 2 A structural diagram of an emergency communication equipment dispatching and management system provided by an embodiment of the present application is shown.

[0068] like Figure 2 As shown, the emergency communication equipment dispatching and management system 10 includes: 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 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 a scheduling mapping relationship between the emergency communication equipment and the task points; the emergency dynamic weights are related to the emergency support stage and the real-time indicator values ​​of the emergency communication equipment; A generating module 12 is configured to generate an initial scheduling strategy based on the initial scheduling plan and real-time traffic information of the emergency area; the initial scheduling strategy includes the initial scheduling plan and a scheduling path corresponding to the implementation of the initial scheduling plan; The optimization module 13 is used to optimize the initial scheduling strategy based on a multi-objective optimization algorithm to obtain a target scheduling strategy.

[0069] In some embodiments, the matching module 11 is further configured to: Determining the basic weights between the emergency communication equipment and the evaluation indicators based on prior expert evaluations; Acquiring real-time indicator data corresponding to the emergency communication equipment, and determining a real-time correction weight corresponding to the emergency communication equipment according to the real-time indicator data; Determine the weight of the emergency support stage according to the emergency support stage of the emergency task; The emergency dynamic weight is determined according to the basic weight, the real-time correction weight and the emergency guarantee stage weight.

[0070] In some embodiments, the matching module 11 is further configured to: For each evaluation indicator, calculating a real-time evaluation value of each evaluation indicator; Determining a real-time evaluation entropy of each evaluation indicator based on the plurality of emergency communication equipment; The real-time correction weight is determined according to the real-time evaluation entropy.

[0071] In some embodiments, the initial scheduling strategy includes a scheduling strategy for multiple emergency communication equipment, and the optimization module 13 is specifically configured to: Based on each of the task points and the emergency communication equipment, construct an objective function corresponding to the optimization strategy; 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.

[0072] In some embodiments, the optimization module 13 is specifically configured to: For each of the initial scheduling strategies, determining an objective function value corresponding to the initial scheduling strategy; Based on the objective function value, the initial scheduling strategy is non-dominated sorted to obtain a non-dominated frontier scheduling strategy, and the non-dominated frontier scheduling strategy is used as the inherited parent scheduling strategy of the current iteration round; For each of the non-dominated front scheduling strategies, calculating the congestion degree corresponding to the non-dominated front scheduling strategy; Selecting the non-dominated frontier scheduling strategy whose congestion degree meets the preset conditions, performing genetic iteration, and obtaining a candidate scheduling strategy for the next iteration round; Perform non-dominated sorting on the candidate scheduling strategies to obtain the non-dominated frontier scheduling strategy for the next iteration round, and so on until the preset exit condition is met.

[0073] In some embodiments, the optimization module 13 is specifically configured to: The congestion degree is determined according to the distance between the non-dominated front scheduling strategies.

[0074] It should be understood that the modules or modules recorded in the emergency communication equipment dispatch management system 10 are similar to those in the reference Figure 1The various steps in the described method correspond to each other. Therefore, the operations and features described above for the method are also applicable to the emergency communication equipment scheduling and management system 10 and the modules contained therein, and will not be repeated here. The emergency communication equipment scheduling and management system 10 can be pre-implemented in the browser or other security applications of the electronic device, or loaded into the browser or its security application of the electronic device by downloading or other means. The corresponding modules in the emergency communication equipment scheduling and management system 10 can cooperate with the modules in the electronic device to implement the solution of the embodiment of the present application.

[0075] The several modules or units mentioned in the detailed description above are not necessarily divided into one module or unit. In fact, according to the embodiments of the present 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 into multiple modules or units to be embodied.

[0076] Reference below Figure 3 , Figure 3 A schematic diagram of the structure of a computer system of an electronic device or server suitable for implementing the embodiments of the present application is shown. like Figure 3 As shown, computer system 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to programs stored in read-only memory (ROM) 302 or programs loaded from storage 308 into random access memory (RAM) 303. RAM 303 also stores various programs and data required for the system's operating instructions. CPU 301, ROM 302, and RAM 303 are connected to each other via bus 304. An input / output (I / O) interface 305 is also connected to bus 304.

[0077] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, mouse, and the like; an output section 307 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and speakers; a storage section 308 including devices such as a hard disk; and a communication section 309 including a network interface card such as a LAN card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 310 as needed, so that computer programs read from the media can be installed in the storage section 308 as needed.

[0078] In particular, according to the embodiment of the present application, the above reference flow chart Figure 2The described processes can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for executing the method illustrated in the flowchart. In such an embodiment, the computer program contains program code for executing the method illustrated in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 309 and / or installed from removable media 311. When the computer program is executed by the central processing unit (CPU) 301, the aforementioned functions defined in the system of the present application are performed.

[0079] It should be noted that the computer-readable medium described herein may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may 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 computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, 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, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may 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 may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. This propagated data signal may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical cable, RF, or any suitable combination thereof.

[0080] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operating instructions of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the aforementioned module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than the order marked in the accompanying drawings. For example, the boxes represented by two connections can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operating instruction, or can be implemented using a combination of dedicated hardware and computer instructions.

[0081] As another aspect, the present application further 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 be incorporated into the electronic device. The computer-readable storage medium stores one or more programs, which, when used by one or more processors, execute the emergency communication equipment dispatch management method described in the present application.

[0082] The above description is merely a preferred embodiment of the present application and an illustration 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 a specific combination of the aforementioned technical features. It also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the aforementioned disclosed concepts. For example, a technical solution formed by replacing the aforementioned 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: 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 emergency dynamic weights to obtain an initial scheduling plan; the initial scheduling plan includes a scheduling mapping relationship between the emergency communication equipment and the task points; the emergency dynamic weights are related to the emergency support stage and the real-time indicator values ​​of the emergency communication equipment; generating an initial dispatching strategy based on the initial dispatching plan and real-time traffic information of the emergency area; The initial scheduling strategy includes the initial scheduling plan and a scheduling path corresponding to the implementation of the initial scheduling plan; Based on a multi-objective optimization algorithm, the initial scheduling strategy is optimized to obtain a target scheduling strategy.

2. The method for dispatching and managing emergency communication equipment according to claim 1, wherein: Also includes: Determining the basic weights between the emergency communication equipment and the evaluation indicators based on prior expert evaluations; Acquiring real-time indicator data corresponding to the emergency communication equipment, and determining a real-time correction weight corresponding to the emergency communication equipment according to the real-time indicator data; Determine the weight of the emergency support stage according to the emergency support stage of the emergency task; The emergency dynamic weight is determined according to the basic weight, the real-time correction weight and the emergency guarantee stage weight.

3. The method for dispatching and managing emergency communication equipment according to claim 2, characterized in that: The determining, according to the real-time indicator data, a real-time correction weight corresponding to the emergency communication equipment includes: For each of the evaluation indicators, calculating a real-time evaluation value of each of the evaluation indicators; Determining a real-time evaluation entropy of each evaluation indicator based on the plurality of emergency communication equipment; The real-time correction weight is determined according to the real-time evaluation entropy.

4. The method for dispatching and managing emergency communication equipment according to claim 1, wherein: The initial scheduling strategy includes scheduling strategies for multiple emergency communication equipment. The initial scheduling strategy is optimized based on a multi-objective optimization algorithm to obtain a target scheduling strategy, including: Based on each of the task points and the emergency communication equipment, construct an objective function corresponding to the optimization strategy; 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.

5. The method for dispatching and managing emergency communication equipment according to claim 4, characterized in that: The performing of a non-dominated sorting genetic optimization based on a congestion constraint on the initial scheduling strategy based on the objective function includes: For each of the initial scheduling strategies, determining an objective function value corresponding to the initial scheduling strategy; Based on the objective function value, the initial scheduling strategy is non-dominated sorted to obtain a non-dominated frontier scheduling strategy, and the non-dominated frontier scheduling strategy is used as the inherited parent scheduling strategy of the current iteration round; For each of the non-dominated front scheduling strategies, calculating the congestion degree corresponding to the non-dominated front scheduling strategy; Selecting the non-dominated frontier scheduling strategy whose congestion degree meets the preset conditions, performing genetic iteration, and obtaining a candidate scheduling strategy for the next iteration round; Perform non-dominated sorting on the candidate scheduling strategies to obtain the non-dominated frontier scheduling strategy for the next iteration round, and so on until the preset exit condition is met.

6. The method for dispatching and managing emergency communication equipment according to claim 5, characterized in that: Also includes: The congestion degree is determined according to the distance between the non-dominated front scheduling strategies.

7. An emergency communication equipment dispatching and management system, characterized in that: include: A matching module is configured to obtain communication demand information corresponding to each task point and resource supply information corresponding to each emergency communication equipment, and 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 a scheduling mapping relationship between the emergency communication equipment and the task points; the emergency dynamic weights are related to the emergency support stage and the real-time indicator values ​​of the emergency communication equipment; A generation module, configured to generate an initial dispatching strategy based on the initial dispatching plan and real-time traffic information of the emergency area; The initial scheduling strategy includes the initial scheduling plan and a scheduling path corresponding to the implementation of the initial scheduling plan; The optimization module is used to optimize the initial scheduling strategy based on a multi-objective optimization algorithm to obtain a target scheduling strategy.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, it implements the emergency communication equipment scheduling and management method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the emergency communication equipment dispatching and management method as described in any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the emergency communication equipment dispatching and management method according to any one of claims 1 to 6 is implemented.

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