Multi-project parallel optical cable route planning method, device, equipment and medium

Abstract

The invention discloses a multi-project parallel optical cable route planning method, device, equipment and medium, and the method comprises the steps: determining the available space of a bending section of an optical cable pipeline according to the space occupation state, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline; according to the space occupation state, the pipeline deformation data and the available space of the bent section, generating a space occupation model of each section of pipeline by adopting a three-dimensional modeling technology; acquiring a preset optical cable starting and ending point of each project, and based on the space occupation model, performing optical cable path optimization by adopting a genetic algorithm to obtain an initial optical cable routing plan; and analyzing a pipeline resource contention condition among multiple projects according to the initial optical cable routing plan, and adjusting the initial optical cable routing plan according to the pipeline resource contention condition to obtain a final optical cable routing plan result. According to the invention, optical cable pipeline resources can be reasonably planned, and the accuracy of optical cable route planning is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of optical cable planning, and in particular to a method, device, equipment and medium for parallel optical cable routing planning for multiple projects. Background Art

[0002] With the expansion of power networks and the acceleration of urbanization, optical cable routing, as the lifeblood of information transmission, has a direct impact on the stability and future scalability of distribution systems. However, traditional optical cable routing methods rely heavily on manual experience or simple algorithms, resulting in low accuracy and poor adaptability when dealing with multiple parallel projects. Existing technologies also often overlook the impact of pipe bends, leading to irrational and inaccurate pipeline resource planning. Summary of the Invention

[0003] To solve the above technical problems, the present invention provides a multi-project parallel optical cable routing planning method, device, equipment and medium, which can reasonably plan optical cable pipeline resources and effectively improve the accuracy of optical cable routing planning.

[0004] The present invention provides a multi-project parallel optical cable routing planning method, comprising: Obtain the space occupancy status, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline; Determining the available space of the curved section of the optical cable duct according to the space occupancy state, the duct deformation data and the duct geometric parameters; Generate a space occupancy model of each pipeline section using three-dimensional modeling technology according to the space occupancy status, the pipeline deformation data and the available space of the curved section; Obtain the starting and ending points of the optical cable preset for each project, and optimize the optical cable path using a genetic algorithm based on the space occupancy model to obtain an initial optical cable routing plan; According to the initial optical cable routing plan, the pipeline resource contention between multiple projects is analyzed, and the initial optical cable routing plan is adjusted according to the pipeline resource contention to obtain a final optical cable routing plan result.

[0005] As an improvement to the above solution, determining the available space of the curved section of the optical cable duct according to the space occupancy state, the duct deformation data and the duct geometric parameters includes: Calculating the actual available space of the pipeline according to the space occupancy status and the pipeline deformation data; The position of the pipe bending section is determined according to the pipe geometric parameters, and the available space of the bending section of the optical cable pipe is obtained according to the actual available space of the pipe and the position of the pipe bending section.

[0006] As an improvement to the above solution, the method of obtaining the preset starting and ending points of the optical cable for each project, optimizing the optical cable path using a genetic algorithm based on the space occupancy model, and obtaining an initial optical cable routing plan includes: Obtain the service access point and target node for each newly added optical cable in a multi-project scenario; Performing space analysis based on the space occupancy model to identify available optical cable ducts; Based on the available optical cable conduits, the service access points and target nodes of the newly added optical cables, an initial optical cable routing plan is obtained by iterative optimization using a genetic algorithm with the goal of minimizing conduit occupancy, path length and bending section risk; the bending section risk is positively correlated with the degree of curvature of the bending section.

[0007] As an improvement to the above solution, analyzing the pipeline resource contention among multiple projects based on the initial optical cable routing plan includes: Obtaining a pipeline connection point saturation according to the initial optical cable routing plan, and generating a pipeline expansion demand according to the pipeline connection point saturation; Determine the expansion plan based on the pipeline expansion requirements and the preset regional licensing restrictions and environmental conditions; According to the initial optical cable routing plan and the capacity expansion plan, pipeline resource contention analysis is performed on the optical cable routing plans of multiple projects to obtain pipeline resource contention situations among the multiple projects.

[0008] As an improvement to the above solution, the pipeline expansion demand is also determined based on a prediction result of the saturation of the pipeline connection point, and the prediction result is obtained by predicting a historical growth trend of the saturation of the pipeline connection point.

[0009] As an improvement to the above solution, the pipeline resource contention analysis is performed on the optical cable routing plans of multiple projects based on the initial optical cable routing plan and the expansion plan to obtain the pipeline resource contention situation among the multiple projects, including: Obtaining an estimated available capacity of the optical cable duct based on the current available capacity of the optical cable duct and the expanded capacity in the expansion plan; Based on the initial optical cable routing plan, the pipeline and fiber core requirements of each project are obtained; For each section of pipeline, the fiber core requirements of each project are accumulated to obtain the expected usage capacity; If the expected usage capacity of the pipeline is greater than the current available capacity and less than the expected available capacity, it is determined that the pipeline is in a first resource contention state; If the estimated usage capacity of the pipeline is greater than the estimated available capacity, determining that the pipeline is in a second resource contention state; The first resource contention status and the second resource contention status are combined to obtain the pipeline resource contention status among multiple projects.

[0010] As an improvement to the above solution, the initial optical cable routing plan is adjusted according to the pipeline resource contention situation to obtain a final optical cable routing plan result, including: According to the pipeline resource contention situation, screening out a first pipeline in the first resource contention state and a second pipeline in the second resource contention state; The priority of each project is obtained, and according to the priority of each project, the paths corresponding to the first pipeline and the second pipeline in the initial optical cable routing plan are adjusted respectively to obtain a final optical cable routing plan result.

[0011] The present invention also provides a multi-project parallel optical cable routing planning device, comprising: A data acquisition module is used to obtain the space occupancy status, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline; a space calculation module, configured to determine the available space of the curved section of the optical cable duct according to the space occupancy status, the duct deformation data and the duct geometric parameters; a model building module for generating a space occupancy model of each pipeline section using a three-dimensional modeling technology according to the space occupancy status, the pipeline deformation data, and the available space of the curved section; A preliminary planning module is used to obtain the starting and ending points of the optical cables preset for each project, and based on the space occupancy model, a genetic algorithm is used to optimize the optical cable path to obtain an initial optical cable routing plan; The planning result module is used to analyze the pipeline resource contention between multiple projects according to the initial optical cable routing plan, and adjust the initial optical cable routing plan according to the pipeline resource contention to obtain a final optical cable routing plan result.

[0012] The present invention also provides a computer device comprising a processor and a memory, wherein a computer program is stored in the memory and the computer program is configured to be executed by the processor, and when the processor executes the computer program, the multi-project parallel optical cable routing planning method described in any one of the above items is implemented.

[0013] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any of the multi-project parallel optical cable routing planning methods described above.

[0014] Compared with the prior art, the beneficial effects of the multi-project parallel optical cable route planning method, device, equipment and medium provided by the present invention are: by obtaining the space occupancy status, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline, the available space of the curved section of the optical cable pipeline is determined according to the space occupancy status, the pipeline deformation data and the pipeline geometric parameters, and then according to the space occupancy status, the pipeline deformation data and the available space of the curved section, a space occupancy model of each pipeline section is generated using three-dimensional modeling technology, thereby achieving high-precision pipeline modeling, being able to accurately evaluate and efficiently utilize pipeline space, and being conducive to improving resource utilization; obtaining the preset optical cable starting point for each project End point, based on the space occupancy model, adopts genetic algorithm to optimize the optical cable path, obtains the initial optical cable route planning, can carry out automatic path optimization in complex pipeline network in parallel and quickly, and improves the efficiency of optical cable route planning; According to the initial optical cable route planning, analyzes the pipeline resource contention among multiple projects, and adjusts the initial optical cable route planning according to the pipeline resource contention to obtain the final optical cable route planning result, which can effectively deal with the resource allocation and resource conflict problems in the multi-project parallel scenario, not only improves the accuracy and efficiency of optical cable route planning, but also significantly reduces the construction risk and comprehensive cost, and is suitable for large-scale, multi-project parallel pipeline and optical cable planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flow chart of a multi-project parallel optical cable routing planning method provided by an embodiment of the present invention; Figure 2 This is a schematic structural diagram of a multi-project parallel optical cable routing planning device provided by an embodiment of the present invention; Figure 3 It is a structural diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] See also Figure 1 , Figure 1 The following is a flow chart of a multi-project parallel optical cable routing planning method provided by an embodiment of the present invention. The multi-project parallel optical cable routing planning method includes: S1: Obtain the space occupancy status, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline; S2: determining the available space of the curved section of the optical cable duct according to the space occupancy status, the duct deformation data and the duct geometric parameters; S3: Generate a space occupancy model of each pipeline section using a three-dimensional modeling technology based on the space occupancy status, the pipeline deformation data, and the available space of the curved section; S4: Obtain the starting and ending points of the optical cable preset for each project, and optimize the optical cable path using a genetic algorithm based on the space occupancy model to obtain an initial optical cable routing plan; S5: Analyze the pipeline resource contention among multiple projects according to the initial optical cable routing plan, and adjust the initial optical cable routing plan according to the pipeline resource contention to obtain a final optical cable routing plan result.

[0018] Specifically, the space occupancy status of an optical cable duct includes the actual space occupied by the installed optical cables within the duct. For example, if a duct has a total capacity of 10 optical cables and only four are installed, the duct's space occupancy is 40%. The space occupancy status of an optical cable duct can be determined using sensors, such as fiber optic sensing systems and ultrasonic detection equipment, to determine the space occupancy percentage of each duct section.

[0019] Pipeline deformation data can be collected using strain sensors, laser scanners, or other monitoring equipment. This data can reveal changes in the pipeline's cross-sectional area, identify areas with significant deformation, and record the specific location and extent of deformation. For example, soil settlement or external loads may cause a 10% reduction in the pipeline's cross-sectional area in certain areas.

[0020] The pipeline geometric parameters include the diameter, length, bending radius, material properties and other parameters of the optical cable pipeline, which can be obtained through design drawings or on-site measurements.

[0021] As one of the optional embodiments, in step S2, determining the available space of the curved section of the optical cable duct according to the space occupancy state, the duct deformation data, and the duct geometric parameters includes: Calculating the actual available space of the pipeline according to the space occupancy status and the pipeline deformation data; The position of the pipe bending section is determined according to the pipe geometric parameters, and the available space of the bending section of the optical cable pipe is obtained according to the actual available space of the pipe and the position of the pipe bending section.

[0022] Specifically, the actual available space of the optical cable duct is calculated based on the space occupancy status and duct deformation data. The calculation formula is as follows: in, is the actual available space of the pipeline, is the original space of the pipeline, is the space occupied by the optical cable in the duct, It is the ratio of space reduction caused by pipe deformation.

[0023] Then, the location of the bend in the pipeline and its geometric characteristics, including curvature and angle, are obtained based on the pipeline's geometric parameters. Based on the calculated actual available space in the pipeline, the available space in the bend of the optical cable pipeline is determined based on the location and geometric characteristics of the bend. Specifically, because the bend angle of the bend affects the actual available space at the bend, the larger the bend angle, the fewer optical cables can be accommodated within the pipeline. Therefore, for each bend, an availability threshold for the bend space is set based on industry standards or experience, with different thresholds corresponding to bends of varying degrees. Based on the actual available space in the pipeline calculated above, combined with the availability threshold for the bend space, the available space for each bend is determined, thereby improving the accuracy of subsequent modeling.

[0024] In step S3, a spatial occupancy model for each duct segment is generated based on the duct's spatial occupancy, available space in the bends, and the duct's geometric parameters using 3D modeling techniques, such as CAD software or a BIM system. This model visually represents the spatial distribution of the duct. This spatial occupancy model includes the following information: the proportion of space occupied by the optical cables in each duct segment, the actual available space in the bends, and the specific location and impact range of the deformation zone.

[0025] As one of the optional embodiments, in step S4, obtaining the preset starting and ending points of the optical cable for each project, optimizing the optical cable path using a genetic algorithm based on the space occupancy model, and obtaining an initial optical cable routing plan include: Obtain the service access point and target node for each newly added optical cable in a multi-project scenario; Performing space analysis based on the space occupancy model to identify available optical cable ducts; Based on the available optical cable conduits, the service access points and target nodes of the newly added optical cables, an initial optical cable routing plan is obtained by iterative optimization using a genetic algorithm with the goal of minimizing conduit occupancy, path length and bending section risk; the bending section risk is positively correlated with the degree of curvature of the bending section.

[0026] Specifically, a spatial analysis is performed on the space occupancy model. Based on the actual available space in the curved section and the overall occupancy of the pipeline, pipelines with routing capacity are identified, resulting in available optical cable pipelines. Areas with severe deformation or insufficient space are marked as unusable resources. This embodiment quantifies pipeline space occupancy and identifies available resources, facilitating subsequent optical cable routing planning.

[0027] Before using a genetic algorithm for path optimization, the starting and ending points of each new optical cable must be determined: the service access point and the target node. The specific starting and ending points of the optical cable are determined by network planning or customer needs. The starting point is typically the fiber aggregation point / split box, and the ending point is typically a user access point or other aggregation point in the downstream branch. In a multi-project scenario, each project has one or more pairs of starting and ending points, each of which defines a path.

[0028] The genetic algorithm uses the paths corresponding to the start and end points as chromosomes, with each chromosome representing a fiber optic cable route and nodes in the path representing the entry / exit points of each fiber optic cable duct. In a three-dimensional duct network based on a spatial occupancy model, a population of feasible paths is randomly or heuristically constructed to ensure that each path is connected from the start to the end point and does not violate duct availability or deformation constraints. A fitness function is established to calculate a comprehensive cost for each path. This comprehensive cost is a weighted sum of the total length of the path, the occupancy rate of all ducts in the path, and the bend risk value of each bend segment, where the weights can be adjusted based on service priorities. Parent individuals are selected based on the fitness function calculation results, retaining paths with the lowest comprehensive cost. Crossover and mutation operations are performed on the paths, and the optimal paths are selected for the next generation. This iterative process is repeated until the maximum number of iterations is reached, at which point the initial fiber optic cable route plan is derived based on the path with the lowest comprehensive cost in the final population. This embodiment of the present invention automatically identifies available duct resources and selects the path with the lowest occupancy rate that avoids areas with high deformation and bending risks. This allows for global optimization, improves resource efficiency, and ensures network scalability.

[0029] As one of the optional embodiments, in step S5, analyzing pipeline resource contention among multiple projects based on the initial optical cable routing plan includes: Obtaining a pipeline connection point saturation according to the initial optical cable routing plan, and generating a pipeline expansion demand according to the pipeline connection point saturation; Determine the expansion plan based on the pipeline expansion requirements and the preset regional licensing restrictions and environmental conditions; According to the initial optical cable routing plan and the capacity expansion plan, pipeline resource contention analysis is performed on the optical cable routing plans of multiple projects to obtain pipeline resource contention situations among the multiple projects.

[0030] Specifically, the saturation of the conduit connection points is extracted from the initial optical cable routing plan. This saturation represents the ratio of the number of optical cable connections carried by a conduit connection point to the designed capacity. If the conduit connection point saturation in a certain area exceeds a preset threshold, it is considered that there is a need for capacity expansion in that area. Areas with conduit connection point saturation greater than the preset threshold are considered areas with capacity expansion needs, and the capacity expansion requirements are generated.

[0031] As one of the optional embodiments, the pipeline expansion demand is also determined based on a prediction result of pipeline connection point saturation, and the prediction result is obtained by predicting a historical growth trend of the pipeline connection point saturation.

[0032] Specifically, the pipeline connection point saturation data of the connection point in several historical periods is collected and input into a preset time series prediction model, such as the LSTM model, to predict the connection point saturation in future periods. When the predicted connection point saturation is greater than the set threshold, an expansion demand is generated for the connection point.

[0033] Furthermore, for areas with expansion needs, expansion plans are generated by combining regional licensing restrictions with environmental conditions. Regional licensing restrictions refer to the impact of regional policies on construction. For example, policy restrictions may prevent immediate construction in a city center, limiting the construction time of the expansion plan. Environmental conditions refer to the impact of the construction environment on construction. For example, winter construction in cold regions may be affected by frozen soil, or progress may be affected during the rainy season. Therefore, it is necessary to formulate a construction plan based on environmental conditions and meteorological data, and schedule expansion plans for appropriate seasons. Based on regional licensing restrictions and environmental conditions, the expansion time for each expansion plan can be determined.

[0034] As one of the optional embodiments, performing pipeline resource contention analysis on the optical cable routing plans of multiple projects based on the initial optical cable routing plan and the capacity expansion plan to obtain pipeline resource contention status among the multiple projects includes: Obtaining an estimated available capacity of the optical cable duct based on the current available capacity of the optical cable duct and the expanded capacity in the expansion plan; Based on the initial optical cable routing plan, the pipeline and fiber core requirements of each project are obtained; For each section of pipeline, the fiber core requirements of each project are accumulated to obtain the expected usage capacity; If the expected usage capacity of the pipeline is greater than the current available capacity and less than the expected available capacity, it is determined that the pipeline is in a first resource contention state; If the estimated usage capacity of the pipeline is greater than the estimated available capacity, determining that the pipeline is in a second resource contention state; The first resource contention status and the second resource contention status are combined to obtain the pipeline resource contention status among multiple projects.

[0035] As one of the optional embodiments, adjusting the initial optical cable routing plan according to the pipeline resource contention situation to obtain a final optical cable routing plan result includes: According to the pipeline resource contention situation, screening out a first pipeline in the first resource contention state and a second pipeline in the second resource contention state; The priority of each project is obtained, and according to the priority of each project, the paths corresponding to the first pipeline and the second pipeline in the initial optical cable routing plan are adjusted respectively to obtain a final optical cable routing plan result.

[0036] Specifically, based on the aforementioned space occupancy model, the current available capacity of the optical cable ducts involved in the initial optical cable routing plan is obtained. Combined with the expansion capacity in the expansion plan, the current available capacity of each duct is summed with the expansion capacity to obtain the estimated available capacity of each duct. Based on the initial optical cable routing plan, the fiber core requirements for each project's path on each duct are listed. The total requirements for all projects on each duct are then calculated, i.e., the fiber core requirements on each duct are summed to obtain the estimated capacity.

[0037] Furthermore, based on the initial optical cable routing plan, the pipeline resource contention state is determined according to the expected usage capacity. If the expected usage capacity of a pipeline is less than the current available capacity of the pipeline, there is no resource contention for the pipeline, and the path corresponding to the pipeline does not need to be adjusted. If the expected usage capacity of a pipeline is between the current available capacity of the pipeline and the expected available capacity, the pipeline is in a first resource contention state, i.e., there is a short-term overload. Paths passing through the first pipeline in high-priority projects need to be adjusted. Specifically, a genetic algorithm is used to recalculate the paths passing through the first pipeline and adjust them to adjacent paths or backup paths that meet resource conditions to meet the needs of high-priority projects. Medium- and low-priority paths are not adjusted. If the expected usage capacity of a pipeline is greater than the expected available capacity, the pipeline is in a second resource contention state. After expansion, there will still be resource shortages. Paths planned in the second pipeline need to be retained in order of priority until the expected usage capacity of the pipeline exceeds the expected available capacity. Paths exceeding the expected available capacity are then replanned and adjusted to adjacent paths or backup paths that meet resource conditions. Finally, a conflict-coordinated optical cable routing plan result is obtained. When making path adjustments, it is also necessary to consider the constraints between the time of each project and the expansion time of the expansion plan to ensure that there is no resource conflict.

[0038] The embodiment of the present invention obtains the space occupancy status, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline, determines the available space of the curved section of the optical cable pipeline according to the space occupancy status, the pipeline deformation data and the pipeline geometric parameters, and then uses three-dimensional modeling technology to generate a space occupancy model of each pipeline section according to the space occupancy status, the pipeline deformation data and the available space of the curved section, thereby achieving high-precision pipeline modeling, being able to accurately evaluate and efficiently utilize pipeline space, and being conducive to improving resource utilization; obtains the preset starting and ending points of the optical cable for each project, and uses a genetic algorithm based on the space occupancy model to perform The optical cable path is optimized to obtain an initial optical cable routing plan, which can perform automated path optimization in a complex pipeline network in parallel and quickly, thereby improving the efficiency of optical cable routing planning; based on the initial optical cable routing plan, the pipeline resource contention between multiple projects is analyzed, and the initial optical cable routing plan is adjusted according to the pipeline resource contention to obtain the final optical cable routing planning result, which can effectively handle the resource allocation and resource conflict problems in the multi-project parallel scenario, not only improving the accuracy and efficiency of optical cable routing planning, but also significantly reducing construction risks and comprehensive costs, and is suitable for large-scale, multi-project parallel pipeline optical cable planning. Accordingly, the present invention also provides a multi-project parallel optical cable routing planning device that can implement all processes of the multi-project parallel optical cable routing planning method in the above embodiment.

[0039] See also Figure 2 , Figure 2 1 is a schematic diagram of a multi-project parallel optical cable routing planning device provided by an embodiment of the present invention. The multi-project parallel optical cable routing planning device includes: The data acquisition module 201 is used to obtain the space occupancy status, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline; a space calculation module 202 for determining the available space of the curved section of the optical cable duct according to the space occupancy status, the duct deformation data and the duct geometric parameters; A model building module 203 is configured to generate a space occupancy model of each pipeline section using a three-dimensional modeling technology according to the space occupancy status, the pipeline deformation data, and the available space of the curved section; The preliminary planning module 204 is used to obtain the starting and ending points of the optical cables preset for each project, and optimize the optical cable paths using a genetic algorithm based on the space occupancy model to obtain an initial optical cable routing plan; The planning result module 205 is used to analyze the pipeline resource contention between multiple projects based on the initial optical cable routing plan, and adjust the initial optical cable routing plan according to the pipeline resource contention to obtain a final optical cable routing plan result.

[0040] Preferably, determining the available space of the curved section of the optical cable duct according to the space occupancy state, the duct deformation data and the duct geometric parameters includes: Calculating the actual available space of the pipeline according to the space occupancy status and the pipeline deformation data; The position of the pipe bending section is determined according to the pipe geometric parameters, and the available space of the bending section of the optical cable pipe is obtained according to the actual available space of the pipe and the position of the pipe bending section.

[0041] Preferably, the obtaining of the preset starting and ending points of the optical cable for each project, and optimizing the optical cable path using a genetic algorithm based on the space occupancy model to obtain an initial optical cable routing plan, includes: Obtain the service access point and target node for each newly added optical cable in a multi-project scenario; Performing space analysis based on the space occupancy model to identify available optical cable ducts; Based on the available optical cable conduits, the service access points and target nodes of the newly added optical cables, an initial optical cable routing plan is obtained by iterative optimization using a genetic algorithm with the goal of minimizing conduit occupancy, path length and bending section risk; the bending section risk is positively correlated with the degree of curvature of the bending section.

[0042] Preferably, analyzing pipeline resource contention among multiple projects based on the initial optical cable routing plan includes: Obtaining a pipeline connection point saturation according to the initial optical cable routing plan, and generating a pipeline expansion demand according to the pipeline connection point saturation; Determine the expansion plan based on the pipeline expansion requirements and the preset regional licensing restrictions and environmental conditions; According to the initial optical cable routing plan and the capacity expansion plan, pipeline resource contention analysis is performed on the optical cable routing plans of multiple projects to obtain pipeline resource contention situations among the multiple projects.

[0043] Preferably, the pipeline expansion demand is also determined based on a prediction result of pipeline connection point saturation, and the prediction result is obtained by predicting a historical growth trend of the pipeline connection point saturation.

[0044] Preferably, performing pipeline resource contention analysis on the optical cable routing plans of multiple projects based on the initial optical cable routing plan and the capacity expansion plan to obtain pipeline resource contention status among the multiple projects includes: Obtaining an estimated available capacity of the optical cable duct based on the current available capacity of the optical cable duct and the expanded capacity in the expansion plan; Based on the initial optical cable routing plan, the pipeline and fiber core requirements of each project are obtained; For each section of pipeline, the fiber core requirements of each project are accumulated to obtain the expected usage capacity; If the expected usage capacity of the pipeline is greater than the current available capacity and less than the expected available capacity, it is determined that the pipeline is in a first resource contention state; If the estimated usage capacity of the pipeline is greater than the estimated available capacity, determining that the pipeline is in a second resource contention state; The first resource contention status and the second resource contention status are combined to obtain the pipeline resource contention status among multiple projects.

[0045] Preferably, the adjusting the initial optical cable routing plan according to the pipeline resource contention situation to obtain a final optical cable routing plan result includes: According to the pipeline resource contention situation, screening out a first pipeline in the first resource contention state and a second pipeline in the second resource contention state; The priority of each project is obtained, and according to the priority of each project, the paths corresponding to the first pipeline and the second pipeline in the initial optical cable routing plan are adjusted respectively to obtain a final optical cable routing plan result.

[0046] In specific implementation, the working principle, control process and technical effects achieved by the multi-project parallel optical cable routing planning device provided in the embodiment of the present invention are the same as those of the multi-project parallel optical cable routing planning method in the above embodiment, and will not be repeated here.

[0047] See also Figure 3 , Figure 3 This is a block diagram of a computer device provided in an embodiment of the present invention. The computer device includes a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program, the steps of the aforementioned multi-project parallel optical cable routing planning method embodiment are implemented. Alternatively, when the processor 301 executes the computer program, the functions of the modules / units in the aforementioned device embodiments are implemented.

[0048] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 302 and executed by the processor 301 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in the computer device.

[0049] The computer device may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that the schematic diagram is merely an example of a computer device and does not limit the computer device. The computer device may include more or fewer components than shown, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, and the like.

[0050] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor. The processor 301 is the control center of the computer device, connecting various parts of the entire computer device using various interfaces and lines.

[0051] The memory 302 can be used to store the computer programs and / or modules. The processor 301 implements the various functions of the computer device by running or executing the computer programs and / or modules stored in the memory 302 and accessing the data stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function (such as a sound playback function or an image playback function); the data storage area may store data generated based on the use of the mobile phone (such as audio data, a phone book, etc.). In addition, the memory 302 may include high-speed random access memory and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0052] If the module / unit integrated into the computer device is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention can also implement all or part of the process steps in the above-mentioned method embodiments by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by the processor 301, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, software distribution medium, etc.

[0053] An embodiment of the present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the multi-project parallel optical cable routing planning method described in any of the above embodiments.

[0054] The present invention provides a multi-project parallel optical cable routing planning method, device, equipment and medium, the beneficial effects of which are: by obtaining the space occupancy status, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline, determining the available space of the curved section of the optical cable pipeline according to the space occupancy status, the pipeline deformation data and the pipeline geometric parameters, and then using three-dimensional modeling technology to generate a space occupancy model of each pipeline section according to the space occupancy status, the pipeline deformation data and the available space of the curved section, achieving high-precision pipeline modeling, capable of accurately evaluating and efficiently utilizing pipeline space, and conducive to improving resource utilization; obtaining the preset starting and ending points of the optical cable for each project, based on Based on the space occupancy model, a genetic algorithm is used to optimize the optical cable path to obtain an initial optical cable route plan. This can perform automated path optimization in a complex pipeline network in parallel and quickly, thereby improving the efficiency of optical cable route planning. Based on the initial optical cable route plan, the pipeline resource contention between multiple projects is analyzed, and the initial optical cable route plan is adjusted according to the pipeline resource contention to obtain the final optical cable route planning result. This can effectively handle resource allocation and resource conflict issues in multi-project parallel scenarios, not only improving the accuracy and efficiency of optical cable route planning, but also significantly reducing construction risks and overall costs. This method is suitable for large-scale, multi-project parallel pipeline and optical cable planning.

[0055] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A multi-project parallel optical cable routing planning method, characterized in that: include: Obtain the space occupancy status, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline; Determining the available space of the curved section of the optical cable duct according to the space occupancy state, the duct deformation data and the duct geometric parameters; Generate a space occupancy model of each pipeline section using three-dimensional modeling technology according to the space occupancy status, the pipeline deformation data and the available space of the curved section; Obtain the starting and ending points of the optical cable preset for each project, and optimize the optical cable path using a genetic algorithm based on the space occupancy model to obtain an initial optical cable routing plan; According to the initial optical cable routing plan, the pipeline resource contention between multiple projects is analyzed, and the initial optical cable routing plan is adjusted according to the pipeline resource contention to obtain a final optical cable routing plan result.

2. The multi-project parallel optical cable routing planning method according to claim 1, characterized in that: The determining of the available space of the curved section of the optical cable duct according to the space occupancy state, the duct deformation data and the duct geometric parameters includes: Calculating the actual available space of the pipeline according to the space occupancy status and the pipeline deformation data; The position of the pipe bending section is determined according to the pipe geometric parameters, and the available space of the bending section of the optical cable pipe is obtained according to the actual available space of the pipe and the position of the pipe bending section.

3. The multi-project parallel optical cable routing planning method according to claim 1, wherein: The method of obtaining the preset starting and ending points of the optical cable for each project and optimizing the optical cable path using a genetic algorithm based on the space occupancy model to obtain an initial optical cable routing plan includes: Obtain the service access point and target node for each newly added optical cable in a multi-project scenario; Performing space analysis based on the space occupancy model to identify available optical cable ducts; Based on the available optical cable conduits, the service access points and target nodes of the newly added optical cables, an initial optical cable routing plan is obtained by iterative optimization using a genetic algorithm with the goal of minimizing conduit occupancy, path length and bending section risk; the bending section risk is positively correlated with the degree of curvature of the bending section.

4. The multi-project parallel optical cable routing planning method according to claim 1, wherein: Analyzing pipeline resource contention among multiple projects based on the initial optical cable routing plan includes: Obtaining a pipeline connection point saturation according to the initial optical cable routing plan, and generating a pipeline expansion demand according to the pipeline connection point saturation; Determine the expansion plan based on the pipeline expansion requirements and the preset regional licensing restrictions and environmental conditions; According to the initial optical cable routing plan and the capacity expansion plan, pipeline resource contention analysis is performed on the optical cable routing plans of multiple projects to obtain pipeline resource contention situations among the multiple projects.

5. The multi-project parallel optical cable routing planning method according to claim 4, characterized in that: The pipeline expansion demand is also determined based on a prediction result of the pipeline connection point saturation, and the prediction result is obtained by predicting the historical growth trend of the pipeline connection point saturation.

6. The multi-project parallel optical cable routing planning method according to claim 4, characterized in that: The performing of pipeline resource contention analysis on the optical cable routing plans of multiple projects based on the initial optical cable routing plan and the expansion plan to obtain pipeline resource contention status among the multiple projects includes: Obtaining an estimated available capacity of the optical cable duct based on the current available capacity of the optical cable duct and the expanded capacity in the expansion plan; Based on the initial optical cable routing plan, the pipeline and fiber core requirements of each project are obtained; For each section of pipeline, the fiber core requirements of each project are accumulated to obtain the expected usage capacity; If the expected usage capacity of the pipeline is greater than the current available capacity and less than the expected available capacity, it is determined that the pipeline is in a first resource contention state; If the estimated usage capacity of the pipeline is greater than the estimated available capacity, determining that the pipeline is in a second resource contention state; The first resource contention status and the second resource contention status are combined to obtain the pipeline resource contention status among multiple projects.

7. The multi-project parallel optical cable routing planning method according to claim 6, characterized in that: The adjusting the initial optical cable routing plan according to the pipeline resource contention situation to obtain a final optical cable routing plan result includes: According to the pipeline resource contention situation, screening out a first pipeline in the first resource contention state and a second pipeline in the second resource contention state; The priority of each project is obtained, and according to the priority of each project, the paths corresponding to the first pipeline and the second pipeline in the initial optical cable routing plan are adjusted respectively to obtain a final optical cable routing plan result.

8. A multi-project parallel optical cable routing planning device, characterized in that: include: A data acquisition module is used to obtain the space occupancy status, pipeline deformation data and pipeline geometric parameters of each optical cable pipeline; a space calculation module, configured to determine the available space of the curved section of the optical cable duct according to the space occupancy status, the duct deformation data and the duct geometric parameters; a model building module for generating a space occupancy model of each pipeline section using a three-dimensional modeling technology according to the space occupancy status, the pipeline deformation data, and the available space of the curved section; A preliminary planning module is used to obtain the starting and ending points of the optical cables preset for each project, and based on the space occupancy model, a genetic algorithm is used to optimize the optical cable path to obtain an initial optical cable routing plan; The planning result module is used to analyze the pipeline resource contention between multiple projects according to the initial optical cable routing plan, and adjust the initial optical cable routing plan according to the pipeline resource contention to obtain a final optical cable routing plan result.

9. A computer device, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory and configured to be executed by the processor, and wherein the processor implements the multi-project parallel optical cable routing planning method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the device where the computer-readable storage medium is located executes the computer program, the multi-project parallel optical cable routing planning method according to any one of claims 1 to 7 is implemented.

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