Intelligent earth-rock filling and digging balance optimization method and system for water conservancy project

Abstract

The invention relates to an intelligent earth-rock filling and digging balance optimization method and system for a water conservancy project. According to the method, firstly, a laser scanner, unmanned aerial vehicle aerial survey equipment and a GPS positioning device are used for carrying out data collection on a construction site, and detailed topographic data and earth-rock distribution information are obtained; subsequently, construction requirements related to the hydraulic engineering are determined, including construction progress, construction sequence, resource availability, environmental limitation, and cost control. And based on the collected data and set construction requirements, a genetic algorithm is used for optimization, and an optimal earth-rock filling and digging balance scheme is generated. The optimization scheme covers a construction route, an equipment scheduling plan and a resource allocation scheme. And finally, hydraulic engineering construction is guided according to the optimization scheme, and efficient balanced filling and excavation of the earthwork are achieved. The construction efficiency is effectively improved, the cost is reduced, reasonable utilization of resources is ensured, and the method is suitable for various complex hydraulic engineering projects.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy engineering, and in particular to a method and system for optimizing the intelligent excavation and filling balance of earth and stone in water conservancy engineering. Background Art

[0002] In the prior art, earthwork construction in water conservancy projects usually relies on traditional manual experience and mechanical operation. These methods usually include topographic survey, earthwork volume estimation, construction planning and mechanical scheduling. Traditional topographic survey mainly relies on manual measurement or simple GPS equipment, and the calculation of earthwork volume also relies on manual estimation or low-precision software tools. In addition, construction planning and mechanical scheduling are usually based on the experience of construction personnel, lack of scientific optimization methods, and low overall efficiency.

[0003] However, the existing technology has some significant shortcomings. First, the traditional topographic survey and data collection methods have limited accuracy, which easily leads to errors and waste of resources in subsequent construction. Secondly, the balance of earthwork excavation and filling often lacks a systematic optimization strategy, resulting in unreasonable transportation distances, long construction time and low equipment utilization. In addition, environmental factors and resource scheduling issues during the construction process cannot be effectively resolved, resulting in difficulties in cost control and project progress management.

[0004] Therefore, there is an urgent need for a method and system that can improve the accuracy and efficiency of earthwork construction to solve these problems. Summary of the invention

[0005] The present application provides a method and system for optimizing the balance of intelligent filling and excavation of earth and stone in a water conservancy project, so as to improve the construction efficiency of the water conservancy project.

[0006] The present application provides a method for optimizing the balance of earthwork and excavation in a water conservancy project, comprising:

[0007] Use laser scanners, drone aerial survey equipment and GPS positioning devices to collect data at the construction site of the water conservancy project to obtain terrain data and earthwork distribution information;

[0008] Determine construction requirements associated with water projects, including construction schedule, construction sequence, resource availability, environmental constraints, and cost control;

[0009] Based on the collected terrain data, earthwork distribution information and set construction requirements, a genetic algorithm is used to optimize the earthwork excavation balance to obtain an optimal earthwork excavation balance plan, wherein the optimal earthwork excavation balance plan includes a construction route, an equipment scheduling plan and a resource allocation plan;

[0010] The water conservancy project is constructed according to the optimal earthwork excavation and filling balance plan.

[0011] Furthermore, the laser scanner, drone aerial survey equipment and GPS positioning device are used to collect data from the construction site of the water conservancy project to obtain terrain data and earthwork distribution information, including:

[0012] A laser scanner is used to perform high-precision terrain scanning of the construction site. The laser scanner emits laser pulses and measures their reflection time. Based on the reflection time, an initial three-dimensional terrain model is generated that includes terrain undulations, slopes, and boundary information within the construction area.

[0013] Use drones equipped with aerial survey equipment to take aerial photos of the construction site, and use aerial photography equipment to capture high-resolution images; use image stitching technology to generate a two-dimensional orthophoto map and a three-dimensional image model of the construction site; fuse the generated three-dimensional image model with the initial three-dimensional terrain model to form a comprehensive three-dimensional terrain model;

[0014] Use GPS positioning devices to accurately locate key points on the construction site; synchronize the GPS positioning information obtained with the comprehensive three-dimensional terrain model to establish a unified geographic coordinate system to ensure the spatial consistency of all terrain data;

[0015] Comprehensively process laser scanning data, aerial image data and GPS positioning data to generate a high-precision, high-resolution digital terrain model of the construction site;

[0016] The terrain data and earthwork distribution information are extracted based on the digital terrain model.

[0017] Furthermore, the use of a laser scanner to perform high-precision terrain scanning on the construction site includes:

[0018] Before laser scanning, the construction site is divided into several scanning sub-areas, and scanning parameters are set for each sub-area, including scanning angle, scanning density and scanning range, to adapt to the terrain characteristics and earthwork distribution characteristics of each sub-area;

[0019] After completing the scanning of each sub-area, the scanned data of all sub-areas are spliced ​​and integrated to generate an initial 3D terrain model of the construction site, thereby ensuring the integrity and accuracy of the model.

[0020] Furthermore, the laser scanning data, aerial image data and GPS positioning data are comprehensively processed to generate a high-precision, high-resolution digital terrain model of the construction site, including:

[0021] Perform precision correction on laser scanning data, and adjust the elevation and position information in the laser scanning data by comparing the key point positions obtained by the GPS positioning device;

[0022] Perform geometric correction on aerial image data to correct the distortion and projection errors in the image so that it is consistent with the coordinate system of laser scanning data and GPS positioning data;

[0023] In the comprehensive processing process, the location information of high-precision data sources is preferentially used to improve the accuracy and reliability of the final generated digital terrain model of the construction site.

[0024] Furthermore, the earthwork excavation and filling balance optimization is performed using a genetic algorithm based on the collected terrain data, earthwork distribution information and set construction requirements to obtain the optimal earthwork excavation and filling balance solution, including:

[0025] Step P101: Initialize a population, the population includes a plurality of individuals; each individual represents a specific earthwork excavation and filling balance scheme, the earthwork excavation and filling balance scheme takes into account the construction route, equipment scheduling plan and resource allocation plan;

[0026] Step P102: Performing performance evaluation on each individual in the population, wherein the performance evaluation is performed based on a predefined multi-objective fitness function, wherein the multi-objective fitness function comprehensively considers the cut-fill balance, construction efficiency, resource utilization, and cost control objectives;

[0027] Step P103: Perform non-dominated sorting, sorting the individuals in the population according to their performance on each optimization goal, and comparing the individuals based on their multi-objective fitness scores; based on the non-dominated sorting, select excellent individuals to enter the next generation population;

[0028] Step P104: performing crossover and mutation operations on the next generation population to generate a new earthwork excavation and filling balance scheme;

[0029] Step P105: Repeat steps P102 to P104 until a predetermined number of iterations is reached or a specified performance indicator satisfies a stop condition.

[0030] Furthermore, the predefined multi-objective fitness function adopts the following formula 1:

[0031]

[0032] Among them, Fitness represents the fitness score; W balance Indicates the balance degree of earthwork excavation and filling; W efficiency Indicates construction efficiency; W utilization Indicates resource utilization; W cost represents cost control; K, α, β, γ and δ are weight coefficients;

[0033] Among them, the balance degree of earthwork excavation and filling W balanceIt is calculated by the following formula 2:

[0034]

[0035] Among them, V fill,i represents the filling volume of the i-th construction area; V cut,i represents the excavation volume of the i-th construction area; n represents the total number of construction areas; D i represents the average transportation distance of earth and stone from the excavation point to the designated landfill point in the i-th construction area; D max It represents the maximum average transportation distance of earth and stone from the excavation point to the designated landfill point in all construction areas;

[0036] Construction efficiency efficiency It is calculated by the following formula 3:

[0037]

[0038] T actual is the actual construction time; T planned is the planned construction time; U j represents the utilization rate of the jth device; N is the total number of devices;

[0039] Resource utilization W utilization It is calculated by the following formula 4:

[0040]

[0041] Among them, R actual,j represents the actual amount of the jth resource used during the construction process; R available,j represents the available amount of the jth resource; M is the total number of resources;

[0042] Indicates cost control W cost It is calculated by the following formula 5:

[0043]

[0044] Among them, C actual is the actual construction cost; C budget is the budget cost; C transport,j represents the cost of the j-th transportation task; C transport,max is the highest transportation cost among all transportation tasks; P represents the total number of transportation tasks.

[0045] Furthermore, the crossover operation includes:

[0046] Select at least two preferred earthwork excavation and filling balance solutions as parent individuals;

[0047] Based on the construction routes, equipment scheduling plans and resource allocation plans of each parent individual, the location of the intersection is dynamically adjusted by analyzing the terrain complexity and earthwork distribution characteristics of the construction area to generate new child individuals, so that the construction routes of the child individuals can better adapt to specific terrain conditions and optimize the efficiency of transportation routes and resource scheduling.

[0048] Furthermore, the mutation operation includes:

[0049] The variation of construction route parameters adapts to local terrain changes by fine-tuning the locations of key nodes in the route while maintaining the overall structure of the original route;

[0050] The variation of equipment scheduling plan and resource allocation scheme optimizes the parts with low resource utilization by adjusting resource priorities and reallocating resources to improve the overall resource utilization.

[0051] Furthermore, the mutation operation includes:

[0052] Improve the mutation rate in complex terrain and increase the possibility of exploring new paths;

[0053] Reduce the mutation rate in simple terrain to maintain the stability of the current solution.

[0054] The present application provides a water conservancy project earthwork intelligent filling and excavation balance optimization system, comprising:

[0055] The acquisition unit is used to collect data from the construction site of the water conservancy project using laser scanners, drone aerial survey equipment and GPS positioning devices to obtain terrain data and earthwork distribution information;

[0056] Identification unit for determining construction requirements associated with water projects, including construction schedule, construction sequence, resource availability, environmental constraints, and cost control;

[0057] An acquisition unit is used to optimize the earthwork excavation and filling balance by using a genetic algorithm based on the collected terrain data, earthwork distribution information and set construction requirements, so as to obtain an optimal earthwork excavation and filling balance scheme, wherein the optimal earthwork excavation and filling balance scheme includes a construction route, an equipment scheduling plan and a resource allocation plan;

[0058] The execution unit is used to carry out water conservancy project construction according to the optimal earthwork excavation and filling balance plan.

[0059] The beneficial effects of the technical solution provided by this application include:

[0060] (1) By using laser scanners, drone aerial survey equipment and GPS positioning devices to collect high-precision data on the construction site, the present invention can accurately obtain terrain data and earth and stone distribution information. This high-precision data collection greatly improves the accuracy of the earth and stone filling and excavation balance plan, ensures that the construction process can closely fit the actual terrain conditions, and reduces errors and rework. (2) The present invention uses genetic algorithms to perform multi-objective optimization by comprehensively considering factors such as construction progress, resource availability and cost control to generate the optimal earth and stone filling and excavation balance plan. The optimized plan can not only improve construction efficiency, but also maximize resource utilization, avoid resource waste and reduce construction costs. (3) The optimization method of the present invention can dynamically adjust the construction route and resource allocation plan according to the terrain complexity of different construction areas. Through a highly adaptable optimization strategy, a more effective construction plan can be found in complex terrain, while maintaining the stability of the plan in simple terrain, ensuring the continuity and overall efficiency of construction. (4) Through precise construction planning and optimized equipment scheduling, the present invention effectively reduces the earth and stone transportation distance and construction time, thereby reducing construction costs. In addition, reasonable resource allocation and equipment usage planning can help reduce energy consumption and environmental impact and improve the sustainability of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a flow chart of a method for intelligent excavation and filling balance optimization of earth and stone in a water conservancy project provided in the first embodiment of the present application.

[0062] Figure 2 It is a schematic diagram of an intelligent excavation and filling balance optimization system for earthwork in a water conservancy project provided in the second embodiment of the present application. DETAILED DESCRIPTION

[0063] Many specific details are described in the following description to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present application, so the present application is not limited by the specific implementation disclosed below.

[0064] The first embodiment of the present application provides a method for optimizing the balance of earthwork and excavation in a water conservancy project. Figure 1 , which is a schematic diagram of the first embodiment of the present application. Figure 1 The first embodiment of the present application provides a method for optimizing the intelligent excavation and filling balance of earth and stone in a water conservancy project, which is described in detail.

[0065] Step S101: using laser scanners, drone aerial survey equipment and GPS positioning devices to collect data on the construction site of the water conservancy project to obtain terrain data and earthwork distribution information.

[0066] In step S101, first, a high-precision laser scanner is used to perform a comprehensive terrain scan of the construction site of the water conservancy project. The laser scanner emits laser pulses to the surface and calculates the distance of the scanning point by measuring the reflection time of the laser pulses. The specific operation includes arranging the laser scanner at different locations on the construction site to ensure that the entire construction area is covered. After each scan, the device will generate a large amount of point cloud data, which can accurately reflect the height changes, slopes and surface features of the terrain. In order to improve the integrity and accuracy of the data, multiple scans can be performed under different weather conditions and time periods, and all scan results can be integrated to generate a detailed three-dimensional terrain model.

[0067] Next, the construction site is photographed using a drone equipped with aerial survey equipment. The drone automatically flies along a predetermined flight path, and the aerial survey equipment captures high-resolution images. The operator needs to set the flight altitude, speed, and shooting interval according to the specific conditions of the construction site to ensure that the drone can capture a panoramic view of the construction area. After the shooting is completed, multiple images are stitched together using professional image processing software to generate a two-dimensional orthophoto map and a three-dimensional image model of the construction site. These image data will be matched and integrated with the three-dimensional terrain model generated by laser scanning to further improve the accuracy of the model.

[0068] At the same time, the GPS positioning device is used to accurately locate the key points of the construction site. The GPS positioning device can provide high-precision geographic coordinates. By locating multiple key points in the construction area, its specific latitude, longitude and elevation information can be obtained. When positioning, the operator should ensure the stability of the GPS device receiving the signal, and select a higher-precision device or perform differential correction to eliminate possible errors. The acquired GPS data will be synchronized with the laser scanning and drone aerial photography data. Specifically, the GPS positioning data will be used to calibrate the location information in the three-dimensional terrain model to ensure that all data is in the same geographic coordinate system, thereby maintaining the spatial consistency of the entire construction area.

[0069] After completing the above operations, the laser scanning data, aerial image data and GPS positioning data are processed comprehensively. During the processing, data sources with higher accuracy are preferred, such as elevation data from laser scanning and geographic location data from GPS, to ensure that the generated 3D terrain model has a high degree of accuracy and resolution. The final 3D terrain model should contain all terrain undulations, slopes, boundary information, and specific distribution of earthwork in the construction area. These data will serve as the basis for subsequent steps and provide detailed terrain and earthwork information support for intelligent cut and fill balance optimization of earthwork.

[0070] Furthermore, the laser scanner, drone aerial survey equipment and GPS positioning device are used to collect data from the construction site of the water conservancy project to obtain terrain data and earthwork distribution information, including:

[0071] A laser scanner is used to perform high-precision terrain scanning of the construction site. The laser scanner emits laser pulses and measures their reflection time. Based on the reflection time, an initial three-dimensional terrain model is generated that includes terrain undulations, slopes, and boundary information within the construction area.

[0072] Use drones equipped with aerial survey equipment to take aerial photos of the construction site, and use aerial photography equipment to capture high-resolution images; use image stitching technology to generate a two-dimensional orthophoto map and a three-dimensional image model of the construction site; fuse the generated three-dimensional image model with the initial three-dimensional terrain model to form a comprehensive three-dimensional terrain model;

[0073] Use GPS positioning devices to accurately locate key points on the construction site; synchronize the GPS positioning information obtained with the comprehensive three-dimensional terrain model to establish a unified geographic coordinate system to ensure the spatial consistency of all terrain data;

[0074] Comprehensively process laser scanning data, aerial image data and GPS positioning data to generate a high-precision, high-resolution digital terrain model of the construction site;

[0075] The terrain data and earthwork distribution information are extracted based on the digital terrain model.

[0076] In this implementation, in order to obtain accurate terrain data and earthwork distribution information at the construction site of the water conservancy project, it is first necessary to use a laser scanner to perform a high-precision terrain scan of the construction site. The laser scanner calculates the distance of each point by emitting laser pulses and measuring their reflection time. The specific operation includes arranging the laser scanner at different locations on the construction site and ensuring that the scan covers the entire construction area. During the scanning process, the laser pulse is reflected back to the device when it hits the surface, and the measurement system inside the device calculates the distance to the surface point based on the round-trip time of the laser pulse. Through a large number of such measurement points, an initial three-dimensional terrain model containing terrain undulations, slopes, and boundary information is generated.

[0077] In order to further enrich and refine the terrain data, drones equipped with aerial survey equipment were used to take aerial photos of the construction site. The drones took photos at different heights and angles according to the predetermined flight path. The high-resolution images collected by the aerial photography equipment can record the surface features and landforms of the construction site in detail. Subsequently, these aerial images were processed using image stitching technology to generate two-dimensional orthophotos and three-dimensional image models of the construction site. The orthophotos provide a plan view of the construction area and eliminate the perspective distortion in traditional images, while the three-dimensional image model reconstructs the three-dimensional terrain of the site by superimposing and matching multiple images.

[0078] On this basis, the generated 3D image model is fused with the initial 3D terrain model obtained by laser scanning. Through data fusion, the data obtained by two different methods can be combined to form a more comprehensive and accurate integrated 3D terrain model. This model not only contains the detailed ups and downs and boundary information of the terrain, but also integrates image data from different perspectives and heights, making the terrain representation more realistic and accurate.

[0079] At the same time, in order to ensure the accuracy of the terrain data in space, the key points of the construction site are accurately located using GPS positioning devices. The geographic coordinate information provided by the GPS positioning device can ensure that each important point in the construction site has accurate location information. These GPS positioning information are synchronized with the comprehensive three-dimensional terrain model to unify the geographic coordinate system and ensure that all data are consistent within the same spatial reference frame. This step is very critical because it ensures that all collected data are accurately aligned in spatial position, eliminating possible deviations or errors.

[0080] After completing the above data collection and processing steps, the laser scanning data, aerial image data and GPS positioning data are processed comprehensively. The purpose of comprehensive processing is to integrate various types of data into a high-precision, high-resolution digital terrain model of the construction site. This model should not only reflect the terrain undulations, slopes, boundaries and other information of the construction site, but also accurately display the distribution of earth and stone. In the process of generating the digital terrain model, high-precision data processing algorithms need to be applied to ensure that the data of the model meet the highest standards in resolution and accuracy.

[0081] Finally, terrain data and earthwork distribution information are extracted from the generated digital terrain model. This information will be used in subsequent construction planning and optimization, including the design of earthwork excavation, landfill and transportation routes.

[0082] Furthermore, the use of a laser scanner to perform high-precision terrain scanning on the construction site includes:

[0083] Before laser scanning, the construction site is divided into several scanning sub-areas, and scanning parameters are set for each sub-area, including scanning angle, scanning density and scanning range, to adapt to the terrain characteristics and earthwork distribution characteristics of each sub-area;

[0084] After completing the scanning of each sub-area, the scanned data of all sub-areas are spliced ​​and integrated to generate an initial 3D terrain model of the construction site, thereby ensuring the integrity and accuracy of the model.

[0085] In this embodiment, the use of a laser scanner to perform high-precision terrain scanning of the construction site requires special attention to the comprehensiveness and accuracy of the scan. To this end, before starting the laser scanning, it is first necessary to perform a detailed regional division of the construction site. Specifically, the construction area should be divided into several sub-areas, and the division of each sub-area should take into account the terrain characteristics of the area, the distribution of earth and stone, and the complexity of the construction. The purpose of dividing the sub-areas is to optimize the scanning process so that each area can be accurately captured without affecting the scanning effect due to the breadth or complexity of the area.

[0086] After dividing the sub-areas, you need to set the corresponding scanning parameters for each sub-area. These parameters include scanning angle, scanning density, and scanning range to ensure that the scanner can fully adapt to the specific terrain characteristics of each sub-area. For example, for areas with large terrain changes, you may need to set a higher scanning density to capture more detailed terrain undulations; while for relatively flat areas, you can appropriately reduce the scanning density to improve scanning efficiency. In addition, the setting of the scanning angle is also crucial. Different sub-areas may require different scanning angles to minimize shadow areas and ensure comprehensive capture of the terrain. The scanning range needs to be adjusted according to the size and shape of each sub-area to ensure that the entire area is within the scanning range to avoid missing or repeated scanning.

[0087] Once the scanning parameters of all sub-areas are set, laser scanning can be performed on each sub-area one by one. During the scanning process, the laser scanner emits laser pulses and calculates the distance based on the time of the reflected pulses, thereby obtaining high-precision point cloud data of the terrain. To ensure the accuracy of the data, the scanning should be repeated at different times and weather conditions, and the results of multiple scans should be compared and calibrated to eliminate possible errors.

[0088] After all sub-areas are scanned, the scanned data of each sub-area needs to be spliced ​​and integrated. The splicing process requires the coordinate alignment of the scanned data of adjacent sub-areas and the processing of the overlapping data to ensure seamless connection. The accuracy of the splicing is directly related to the integrity and accuracy of the final generated initial 3D terrain model. To this end, the splicing process may require the application of special algorithms to ensure the consistency of the data in spatial position and eliminate the errors that may be caused by improper splicing of sub-area boundaries.

[0089] Finally, by splicing and integrating the scanned data of each sub-area, a complete initial 3D terrain model of the construction site is generated. This model should be able to accurately reflect the terrain undulations, slopes, and boundary information of the entire construction site, providing reliable basic data for subsequent optimization of earthwork excavation and filling balance.

[0090] Furthermore, the laser scanning data, aerial image data and GPS positioning data are comprehensively processed to generate a high-precision, high-resolution digital terrain model of the construction site, including:

[0091] Perform precision correction on laser scanning data, and adjust the elevation and position information in the laser scanning data by comparing the key point positions obtained by the GPS positioning device;

[0092] Perform geometric correction on aerial image data to correct the distortion and projection errors in the image so that it is consistent with the coordinate system of laser scanning data and GPS positioning data;

[0093] In the comprehensive processing process, the location information of high-precision data sources is preferentially used to improve the accuracy and reliability of the final generated digital terrain model of the construction site.

[0094] In this embodiment, the laser scanning data needs to be calibrated for accuracy first. Although the point cloud data generated by laser scanning has high accuracy, there may be a certain degree of deviation due to environmental conditions, equipment errors or other factors. To ensure the accuracy of the data, the key points in the laser scanning data are first compared with the corresponding positions provided by the GPS positioning device. The GPS positioning device can usually provide very accurate geographic coordinate information. By comparing these known precise positions with the corresponding points in the laser scanning data, the elevation error or position deviation in the scanning data can be identified. After identifying these errors, the elevation and position information in the laser scanning data are adjusted in a targeted manner to ensure that each data point can accurately reflect its true geographical location and elevation. This step is crucial to ensuring the accuracy of the final digital terrain model, because the laser scanning data forms the basis of the terrain model.

[0095] Next, the aerial image data is geometrically corrected. Although the aerial photography equipment carried by the drone can take high-resolution images, the images may be distorted or projected due to the influence of flight altitude, angle and other external factors. These errors will cause the position, size and shape of objects in the image to change, thus affecting the accuracy of the data. In order to eliminate these errors, the aerial images need to be geometrically corrected. The process of geometric correction involves adjusting the geometric relationships in the image so that each point in the image corresponds to its true geographical location. At this point, the corrected aerial image data needs to be matched with the laser scanning data and GPS positioning data so that they have consistent spatial positions in the same coordinate system. Through this correction, data from different sources can be seamlessly integrated to avoid model errors caused by differences in data sources.

[0096] Throughout the comprehensive processing, the location information of data sources with higher accuracy is given priority to guide the generation of the model. Usually, GPS positioning data is used as the main reference for position calibration due to its high accuracy. Laser scanning data has advantages in elevation and three-dimensional structure, and can provide detailed terrain undulation information, while the geometrically corrected aerial image data supplements the details of surface texture and cover. When integrating this data, the system automatically selects the most accurate location information to maximize the accuracy and reliability of the final digital terrain model. This priority processing ensures that the accuracy of the performance of various types of data in the model is consistent, so that the final digital terrain model of the construction site is not only high-resolution, but also truly and accurately reflects the actual terrain conditions of the construction site.

[0097] Through these implementation steps, laser scanning data, aerial imaging data and GPS positioning data can be effectively integrated and processed to generate a high-precision, high-resolution digital terrain model of the construction site, providing a solid data foundation for the intelligent filling and excavation balance optimization of earth and stone in water conservancy projects.

[0098] Step S102: Determine construction requirements related to the water conservancy project, including construction progress, construction sequence, resource availability, environmental constraints and cost control.

[0099] In step S102, first, it is necessary to comprehensively analyze and determine the construction requirements related to the water conservancy project. This process should be planned in detail from multiple key aspects to ensure that the intelligent excavation and filling balance optimization of earthwork can be efficiently implemented in subsequent construction.

[0100] First, the construction schedule needs to be clear. This includes developing a detailed construction schedule that specifies the start and scheduled completion time of each construction phase. When developing the construction schedule, factors such as the scale of the project, seasonal changes, and climatic conditions should be taken into account, and a reasonable buffer period should be built into the schedule to cope with possible delays. The construction schedule should also include the sequence of each construction link to ensure that each stage can proceed in an orderly manner.

[0101] Next, it is particularly important to determine the construction sequence. The construction sequence refers to the order of the various operating steps in earthwork operations, such as excavation first, then transportation and landfill. According to the site topography and the distribution of earthwork, optimizing the construction sequence can reduce transportation distance, reduce equipment idle time, and improve overall construction efficiency. The planning of the construction sequence needs to be combined with the construction progress to ensure that each step of the operation can be seamlessly connected after the previous step is completed.

[0102] Resource availability is another aspect that requires detailed planning. Resource availability includes the configuration of machinery and equipment, manpower, and materials. First, an inventory of currently available machinery and equipment should be conducted to understand the quantity, status, and available time of each type of equipment. Then, according to the construction requirements, these equipment should be reasonably scheduled to ensure that the equipment is fully utilized during the construction process and to avoid equipment idleness or scheduling conflicts. The scheduling of human resources is equally important. It is necessary to arrange an appropriate number of workers according to the needs of different construction stages, while considering the workers' skill matching and working hours. In terms of materials, it is necessary to arrange the procurement and transportation of materials according to the construction schedule to ensure that there is no stoppage due to material shortages during the construction process.

[0103] Environmental restrictions are an important part of construction requirements. Environmental restrictions include natural and social environmental factors at the construction site. Natural environmental restrictions mainly refer to climate conditions, geological conditions, ecological protection requirements, etc. For example, construction in the rainy season may lead to the loss of earth and stone, so specific protective measures need to be set in the construction requirements. In addition, geological conditions such as soft soil or rock geology will also have an impact on construction and need to be specially considered in planning. Social environmental restrictions include noise control, dust management, and the impact on surrounding residents. These factors need to be specified in detail in the construction requirements, and corresponding response measures should be formulated to meet the requirements of environmental protection and social responsibility.

[0104] Finally, cost control is an important part of ensuring the economic benefits of the project. When determining the construction requirements, it is necessary to make a detailed budget for the cost of the entire project, including manpower, equipment, materials, transportation, and various unforeseen expenses. The key to cost control is to reduce various expenses as much as possible while ensuring the quality and progress of construction. To this end, it is necessary to establish a strict cost monitoring mechanism to track every expenditure in real time and make adjustments based on actual conditions. In addition, possible unexpected expenses, such as equipment failure, material price fluctuations, etc., should also be taken into account, and a certain amount of emergency funds should be reserved in the budget.

[0105] By planning the construction progress, construction sequence, resource availability, environmental constraints and cost control, the smooth implementation of the earthwork balance optimization process of the entire water conservancy project can be ensured. These construction requirements will provide a clear parameter basis for the subsequent genetic algorithm optimization, ensuring that the optimization plan not only meets the actual needs of the project, but also has the characteristics of high efficiency, economy and environmental protection.

[0106] Step S103: Based on the collected terrain data, earthwork distribution information and set construction requirements, a genetic algorithm is used to optimize the earthwork excavation and filling balance to obtain an optimal earthwork excavation and filling balance plan, wherein the optimal earthwork excavation and filling balance plan includes a construction route, an equipment scheduling plan and a resource allocation plan.

[0107] In step S103, the terrain data collected in the early stage, the earthwork distribution information and the construction requirements determined in step S102 need to be input into the genetic algorithm to start the optimization process of earthwork excavation and fill balance. As an evolutionary algorithm, the core of the genetic algorithm is to gradually optimize the solution of the problem under given constraints by simulating natural selection and genetic mechanisms. Therefore, when applying the algorithm, it is necessary to clearly define key links such as individuals, populations, fitness functions, selection, crossover and mutation.

[0108] First, define each individual to represent an earthwork excavation and filling scheme, which includes a specific construction route, equipment scheduling plan, and resource allocation plan. Each individual can be represented by a multidimensional vector, and each dimension in the vector corresponds to a decision variable, such as the length of a construction route, the scheduling time of a certain equipment, or the allocation ratio of a certain resource. The initial population consists of multiple randomly generated individuals, which should be as diverse as possible to cover a wide range of solution spaces.

[0109] Next, in order to evaluate the pros and cons of these individuals, a fitness function must be set. The fitness function evaluates the performance of each individual based on predetermined construction requirements (such as construction progress, resource utilization, cost control, etc.). Specifically, the fitness function should consider the following aspects: the balance of earthwork excavation and filling, that is, the volume difference between fill and excavation; the total length and complexity of the construction route to reduce transportation costs and time; optimization of equipment utilization to ensure efficient machinery scheduling; and cost control, by evaluating the costs of materials, labor, and equipment use. When defining the fitness function, different objectives may need to be weighted to reflect the priorities in the project. For example, in a time-sensitive project, the weight of construction progress can be higher than cost control.

[0110] As the genetic algorithm proceeds, individuals in the population are selected, crossover, and mutated. The selection process is based on the results of the fitness function, and methods such as roulette wheel selection or tournament selection are usually used to ensure that individuals with higher fitness are more likely to be selected. Then, a crossover operation is performed, which is to generate new offspring individuals by combining the characteristics of two or more preferred individuals. The crossover method can use single-point crossover or multi-point crossover, and the specific operation depends on the structure of the individual vector and the complexity of the problem. In order to maintain the diversity of the population while avoiding local optimal solutions, mutation operations are also required. Mutation operations enable offspring individuals to explore new solution spaces by randomly changing certain variables in the individual vector. The mutation rate can be dynamically adjusted according to the fitness distribution of the population to balance the exploration and development capabilities of the algorithm.

[0111] After each iteration, the fitness of the offspring population needs to be evaluated, and individuals with higher fitness are selected to enter the next generation population. This process will be repeated until the predetermined stopping condition is met. The stopping condition can be reaching a certain maximum number of iterations, or the fitness of the population tends to be stable in multiple iterations, indicating that the algorithm has approached the optimal solution.

[0112] Ultimately, through multiple generations of iterative optimization using genetic algorithms, one or more excavation and fill balance solutions with the highest fitness will be obtained. These solutions will include detailed construction route planning, equipment scheduling plans, and resource allocation plans, which can be applied in actual projects to ensure efficient implementation of the project.

[0113] Furthermore, the earthwork excavation and filling balance optimization is performed using a genetic algorithm based on the collected terrain data, earthwork distribution information and set construction requirements to obtain the optimal earthwork excavation and filling balance solution, including:

[0114] Step P101: Initialize a population, the population includes a plurality of individuals; each individual represents a specific earthwork excavation and filling balance scheme, the earthwork excavation and filling balance scheme takes into account the construction route, equipment scheduling plan and resource allocation plan;

[0115] Step P102: Performing performance evaluation on each individual in the population, wherein the performance evaluation is performed based on a predefined multi-objective fitness function, wherein the multi-objective fitness function comprehensively considers the cut-fill balance, construction efficiency, resource utilization, and cost control objectives;

[0116] Step P103: Perform non-dominated sorting, sorting the individuals in the population according to their performance on each optimization goal, and comparing the individuals based on their multi-objective fitness scores; based on the non-dominated sorting, select excellent individuals to enter the next generation population;

[0117] Step P104: performing crossover and mutation operations on the next generation population to generate a new earthwork excavation and filling balance scheme;

[0118] Step P105: Repeat steps P102 to P104 until a predetermined number of iterations is reached or a specified performance indicator satisfies a stop condition.

[0119] In this embodiment, it is first necessary to perform an initialization step for optimizing the balance of earthwork excavation and filling. The first step of the process is to initialize a population, in which each individual represents a specific balance scheme for earthwork excavation and filling. These schemes include the design of construction routes, the scheduling plan of equipment, and the allocation of resources. Specifically, each individual can be represented by a code, which includes the order of earthwork excavation and filling in the construction area, the transportation route, the use time and location of mechanical equipment, and the allocation scheme of materials and human resources. When initializing the population, it is necessary to generate multiple such individuals to ensure the diversity of the population, thereby providing a wide solution space for the optimization process of the genetic algorithm.

[0120] After the population is initialized, the performance of these individuals needs to be evaluated. The performance evaluation is based on a predefined multi-objective fitness function, which takes into account multiple key objectives, including earthwork cut-and-fill balance, construction efficiency, resource utilization, and cost control. Specifically, the fitness function analyzes each individual's earthwork cut-and-fill scheme and evaluates its performance on different objectives. For example, the cut-and-fill balance objective focuses on whether the amount of excavated and filled earthwork is matched to reduce unnecessary earthwork transportation. The construction efficiency objective evaluates the time schedule of the entire construction process to ensure that each construction stage can be completed efficiently. The resource utilization objective focuses on the utilization of machinery and human resources to ensure that resources are used in the most optimal way. The cost control objective evaluates the economy of the entire construction process to ensure that the project cost is within the budget. Through these evaluations, the fitness score of each individual can be determined.

[0121] After the performance evaluation is completed, the individuals in the population need to be non-dominated sorted. Non-dominated sorting is a common method in multi-objective optimization, which can classify individuals in the population according to their performance on each optimization goal. Specifically, non-dominated sorting compares the fitness scores between individuals, and classifies those individuals that perform better on all goals into the first category, that is, the best individuals, while other individuals are sorted in order of suboptimality. Through this sorting, individuals with excellent performance can be effectively screened out, and these individuals can be retained as a priority to enter the next generation of population, thereby improving the overall fitness of the population.

[0122] After obtaining the sorting results, it is necessary to perform crossover and mutation operations on the next generation population. The crossover operation generates new offspring individuals by combining the characteristics of two or more preferred individuals, usually using a single-point or multi-point crossover method, so that the offspring individuals can inherit the excellent characteristics of the parent individuals. The mutation operation randomly modifies certain parameters in the offspring individuals, with the aim of introducing new solution spaces to prevent the algorithm from falling into local optimality. The mutation operation can be achieved by changing the construction route, adjusting the equipment scheduling plan, or reallocating resources. The combination of crossover and mutation operations enables the population to evolve gradually and produce a better excavation and filling balance solution.

[0123] This optimization process is iterative, and each iteration repeats the steps of performance evaluation, non-dominated sorting, crossover and mutation operations until the predetermined number of iterations is reached or the fitness of the population stabilizes after multiple iterations and no longer shows significant improvement. At this time, the algorithm will output the optimal earthwork balance plan, which will include the optimal configuration of construction routes, equipment scheduling plans and resource allocation, to ensure efficient and economical earthwork processing in actual construction.

[0124] Furthermore, the predefined multi-objective fitness function adopts the following formula 1:

[0125]

[0126] Among them, Fitness represents the fitness score; W balance Indicates the balance degree of earthwork excavation and filling; W efficiency Indicates construction efficiency; W utilization Indicates resource utilization; W cost represents cost control; K, α, β, γ and δ are weight coefficients;

[0127] Among them, the balance degree of earthwork excavation and filling W balance It is calculated by the following formula 2:

[0128]

[0129] Among them, V fill,i represents the filling volume of the i-th construction area; V cut,i represents the excavation volume of the i-th construction area; n represents the total number of construction areas; D i represents the average transportation distance of earth and stone from the excavation point to the designated landfill point in the i-th construction area; D max It represents the maximum average transportation distance of earth and stone from the excavation point to the designated landfill point in all construction areas;

[0130] Construction efficiency efficiency It is calculated by the following formula 3:

[0131]

[0132] T actual is the actual construction time; T planned is the planned construction time; U j represents the utilization rate of the jth device; N is the total number of devices;

[0133] Resource utilization W utilization It is calculated by the following formula 4:

[0134]

[0135] Among them, R actual,j represents the actual amount of the jth resource used during the construction process; R available,j represents the available amount of the jth resource; M is the total number of resources;

[0136] Indicates cost control W cost It is calculated by the following formula 5:

[0137]

[0138] Among them, Cactual is the actual construction cost; C budget is the budget cost; C transport,j represents the cost of the j-th transportation task; C transport,max is the highest transportation cost among all transportation tasks; P represents the total number of transportation tasks.

[0139] In this embodiment, in order to perform intelligent excavation and filling balance optimization of water conservancy projects, it is necessary to first define a multi-objective fitness function, which is used to evaluate and compare the advantages and disadvantages of different excavation and filling schemes. The fitness function is expressed as Formula 1:

[0140]

[0141] Among them, Fitness represents the fitness score, which indicates the comprehensive performance of a specific excavation and filling scheme. The higher the fitness score, the greater the superiority of the scheme. This score is composed of four main factors, each of which is measured by a corresponding parameter, namely, the excavation and filling balance W balance , Construction efficiency W efficiency , Resource Utilization W utilization and cost control cost Among them, α, β, γ and δ are weight coefficients of each target, which are used to adjust the influence of each factor in the fitness score. The specific weight value is set by the project requirements and priorities. Parameter K is a proportional coefficient in the construction efficiency calculation, which is used to adjust the impact of this item on the overall fitness and can be obtained through experimental data.

[0142] First, the earthwork excavation balance W balance It is used to measure the balance between cut and fill during construction. It is calculated using Formula 2:

[0143]

[0144] In this formula, V fill,i represents the filling volume of the i-th construction area, V cut,i represents the excavation volume of the i-th construction area. By calculating the difference between the fill volume and the excavation volume of each construction area and dividing it by the sum, the degree of fill-excavation balance can be obtained. The smaller the difference between the fill-excavation volume, the higher the balance. The second term involves the transportation distance, where D i represents the average transportation distance of earth and stone from the excavation point to the designated landfill point in the i-th construction area, and D max It is the maximum average transportation distance of earth and stone from the excavation point to the designated landfill point in all construction areas. This part is used to evaluate the rationality of transportation. Shorter transportation distance helps to reduce construction costs and improve efficiency.

[0145] Next, the construction efficiency W efficiencyIt is an important indicator to measure construction time and equipment utilization, and is calculated by formula 3:

[0146]

[0147] Among them, T actual Represents the actual construction time, T planned represents the planned construction time. A lower actual construction time ratio indicates an efficient construction schedule. j represents the utilization rate of the jth equipment. By averaging the utilization rates of all equipment, we can get the resource utilization of the entire project. Optimizing equipment utilization is key because efficient equipment use can not only shorten construction time but also save costs.

[0148] Resource utilization W utilization is calculated by formula 4, which is used to measure the relationship between actual resource usage and available resources:

[0149]

[0150] In the formula, R actual,j represents the actual amount of the jth resource used in the construction process, and R available,j The actual usage of all resources is compared with the available amount to evaluate whether the resources are fully and effectively used. A higher resource utilization rate means that the allocation and use of resources are more reasonable, avoiding waste.

[0151] Finally, cost control cost It is used to evaluate the economic feasibility of the project and is calculated using Formula 5:

[0152]

[0153] Among them, C actual represents the actual construction cost, C budget The ratio of the former to the latter reflects whether the project cost is overspent. The second item is the assessment of transportation cost, C transport,j is the cost of the jth transport task, and C transport,max It is the largest transportation cost among all transportation tasks. This part is used to measure the economic efficiency of transportation. Lower transportation cost can effectively control the overall construction expenditure.

[0154] By calculating the above formula item by item, the fitness score of each earthwork excavation and filling scheme can be obtained, and then the optimal scheme can be selected for actual construction.

[0155] Furthermore, the crossover operation includes:

[0156] Select at least two preferred earthwork excavation and filling balance solutions as parent individuals;

[0157] Based on the construction routes, equipment scheduling plans and resource allocation plans of each parent individual, the location of the intersection is dynamically adjusted by analyzing the terrain complexity and earthwork distribution characteristics of the construction area to generate new child individuals, so that the construction routes of the child individuals can better adapt to specific terrain conditions and optimize the efficiency of transportation routes and resource scheduling.

[0158] In this embodiment, the crossover operation is a key optimization step for generating a new earthwork excavation balance scheme. The core of this step is to select at least two preferred earthwork excavation balance schemes as parent individuals. These parent individuals are usually the schemes that have performed well in the previous generations of genetic algorithm iterations, and they show high fitness in construction route planning, equipment scheduling and resource allocation.

[0159] In the crossover operation, the parent individual's construction route, equipment scheduling plan, and resource allocation plan are first analyzed. The focus of this analysis is the terrain complexity of the construction area and the distribution characteristics of earthwork. These two factors are important factors in determining the efficiency of the construction plan. The terrain complexity may include slope changes, soil stability, and hydrological conditions in the construction area, while the distribution of earthwork involves the relative positions of excavation and landfill points, differences in earthwork volume, etc. Through a detailed analysis of these factors, it is possible to determine which parts of the construction route may have bottlenecks or optimization space, such as whether the possible transportation routes will affect efficiency due to complex terrain, or whether the equipment scheduling can match the needs of resource allocation.

[0160] After clarifying these key factors, the next step of the crossover operation is to dynamically adjust the position of the intersection. The intersection refers to the specific location or section where information is exchanged between two parent individuals. Dynamic adjustment means that the location of the intersection is not fixed, but is flexibly set according to the specific conditions of each construction area. For example, in areas with high terrain complexity, you can choose to cross over in front of or behind the area, so that the offspring individuals can inherit the parts of the parent that perform better under complex terrain; in areas with relatively flat terrain and relatively uniform distribution of earth and stone, the intersection can be set more freely to explore more optimization possibilities.

[0161] By dynamically adjusting the position of the intersection, the generated offspring individuals can achieve better coordination and optimization in construction route planning, equipment scheduling and resource allocation. This crossover operation based on terrain complexity and earthwork distribution characteristics enables the new offspring individuals to not only retain the excellent characteristics of the parent individuals, but also better adapt to the specific conditions in actual construction, thereby improving overall construction efficiency and resource utilization.

[0162] For example, suppose there are two parent individuals A and B in a water conservancy project. The construction route of individual A performs well in the steep slope section of the mountainous area, but the resource scheduling efficiency in the plain area is low; while individual B has high construction efficiency in the plain area, but the transportation path planning in the mountainous area is more complicated. Through the crossover operation, the system analyzes the terrain characteristics of the two areas and decides to keep the route design of individual A in the steep slope section of the mountainous area, and adopt the resource scheduling plan of individual B in the plain area. At this time, the setting of the intersection may be located at the transition point between the hillside section and the plain area. By exchanging the designs of these two sections, the generated offspring individual C can maintain an efficient transportation path in the mountainous section and achieve more efficient resource scheduling in the plain area. In this way, individual C, as a new generation of solutions, may be better than its parent individuals in overall fitness.

[0163] Furthermore, the mutation operation includes:

[0164] The variation of construction route parameters adapts to local terrain changes by fine-tuning the locations of key nodes in the route while maintaining the overall structure of the original route;

[0165] The variation of equipment scheduling plan and resource allocation scheme optimizes the parts with low resource utilization by adjusting resource priorities and reallocating resources to improve the overall resource utilization.

[0166] In this embodiment, the mutation operation is an important optimization method for further improving the adaptability and efficiency of the earthwork excavation and filling balance scheme. The mutation operation makes subtle adjustments to some parameters in the existing scheme to explore new possibilities, thereby generating a new scheme with higher adaptability.

[0167] First, for the variation of construction route parameters, the focus is on fine-tuning the positions of key nodes in the path. These key nodes usually refer to the core positions in the construction route that determine the overall direction of the path, such as turning points, intersections, or areas with large slope changes. In the mutation operation, fine-tuning the positions of these key nodes can make the construction route better adapt to changes in local terrain, such as adjusting the position of a turning point to avoid sudden obstacles, or slightly changing the slope of the path to better suit the driving capacity of transportation equipment. Although the key nodes are adjusted, the overall structure of the entire path remains unchanged. This means that the mutation operation will not significantly change the overall layout of the construction route, but through fine-tuning, optimize the details of the route to make it more in line with the requirements of actual terrain conditions.

[0168] Next, mutation operations are also applied to the optimization of equipment scheduling plans and resource allocation plans. Specifically, by adjusting the priority of resources, mutation operations can reallocate resources that have low utilization in the original plan. Resource priority refers to the order or importance of a resource in the construction process. In mutation operations, if a resource (such as a specific type of equipment or manpower) is found to be underutilized in the current plan, the system will re-evaluate and adjust its priority. By increasing the priority of low-utilization resources, resources can be allocated more reasonably, thereby avoiding waste and increasing overall resource utilization. This reallocation of resources can significantly improve construction efficiency without changing the overall construction schedule and goals.

[0169] For example, in an actual water conservancy project, suppose that in the current earthwork excavation plan, a construction route passes through an area with complex terrain, and the key node in the original plan is a turning point located on a steep slope. When performing a variation operation, by fine-tuning the position of this turning point, it may be found that moving the turning point slightly downward can avoid a protruding rock, making it easier for construction machinery to pass. This adjustment will not change the general direction of the entire route, but it can significantly reduce delays or equipment losses caused by obstacles.

[0170] At the same time, in the same project, suppose the equipment scheduling plan shows that the utilization rate of a large excavator is not high at a certain stage. The mutation operation can adjust the priority of this excavator so that it can also participate in the operation in other construction areas, or rearrange its work order so that it can play a greater role in other time periods. This adjustment not only avoids idle resources, but also may shorten the construction time and improve the resource utilization and economy of the entire project.

[0171] By implementing the variation operation method provided in this embodiment, it is possible to ensure that the optimal earthwork excavation and filling balance plan is generated under complex construction conditions, thereby achieving a more efficient and economical construction effect.

[0172] Furthermore, the mutation operation includes:

[0173] Improve the mutation rate in complex terrain and increase the possibility of exploring new paths;

[0174] Reduce the mutation rate in simple terrain to maintain the stability of the current solution.

[0175] In this embodiment, a key strategy of the mutation operation is to dynamically adjust the mutation rate according to the terrain complexity of the construction area. This adjustment helps to achieve the best balance of optimization solutions under different terrain conditions, ensuring that new paths can be effectively explored while maintaining the stability of the solution.

[0176] In complex terrain, it is very important to adopt a higher mutation rate due to the variety of terrain changes and the large number of unforeseen situations. A higher mutation rate means that in each iteration, certain parameters in the construction plan (such as construction routes, equipment scheduling, or resource allocation) are adjusted more and change more frequently. This strategy can significantly increase the possibility of exploring new construction paths and scheme combinations, thereby discovering construction plans that are more suitable for complex terrain. For example, in steep slopes, canyons, or areas with complex geological structures, by increasing the mutation rate, more fine-tuning and corrections can be introduced in the construction route, making the generated new plan better able to cope with the challenges of the terrain.

[0177] On the contrary, in areas with relatively simple and flat terrain, since the terrain changes less and the construction conditions are relatively stable, reducing the mutation rate is a more reasonable choice. Reducing the mutation rate means that in each iteration, the scheme changes less and the parameter adjustment is smaller. This strategy can effectively maintain the stability of the current scheme and avoid unnecessary adjustments that cause reduced construction efficiency or waste of resources. In simple terrain, since the current scheme is already more adapted to the existing conditions, large or frequent adjustments may bring unnecessary risks. Therefore, by reducing the mutation rate, the consistency and efficiency of the construction process can be maintained.

[0178] For example, suppose that in a water conservancy project, the construction area includes both mountainous areas with complex terrain and flat river valleys. In the construction route planning in mountainous areas, due to the undulating terrain and rugged roads, it may be necessary to frequently adjust the construction route, equipment scheduling and resource allocation plan. In this case, increasing the mutation rate can prompt the algorithm to explore possible plan adjustments in a larger range, such as trying different transportation routes, adjusting the order of equipment use, etc., so as to find a plan that is more suitable for construction in steep mountains.

[0179] On the other hand, in the river valley, the terrain is flat and the construction conditions are stable, and the existing construction routes and resource allocation plans may already be very suitable. In this case, by reducing the mutation rate, it is possible to ensure that the overall structure of the plan remains unchanged during each generation of optimization, avoiding disrupting the existing effective plan due to excessive adjustments. This approach can not only maintain the stability of the construction progress, but also ensure the efficient use of resources and avoid waste due to unnecessary adjustments.

[0180] By implementing the variation operation method provided in this embodiment, it is ensured that the variation rate is flexibly adjusted under different terrain conditions, thereby achieving the best effect of optimizing the balance of earthwork excavation and filling in water conservancy projects.

[0181] Step S104: constructing a water conservancy project according to the optimal earthwork and excavation balance plan.

[0182] In step S104, the optimal earthwork balance solution generated by the genetic algorithm needs to be applied to the actual water conservancy project construction. This process starts with the specific implementation of the solution to ensure that all construction activities are carried out strictly in accordance with the optimization solution to achieve the best utilization of resources and maximize project efficiency.

[0183] Before construction begins, the optimal solution should be analyzed in detail, and the construction route, equipment scheduling plan, and resource allocation plan in the plan should be refined into specific operating instructions. This includes determining the specific tasks, schedules, and operation paths of each piece of construction equipment. For example, according to the construction route in the plan, determine the specific travel path and operation area of ​​the excavator, and arrange the operation sequence of the excavator in different time periods according to the equipment scheduling plan of the plan. In order to ensure the accuracy of the construction route, a site survey should be conducted based on the terrain data before construction, and ground marking should be performed when necessary to guide the actual operation of the construction equipment.

[0184] In terms of resource scheduling, resources need to be allocated according to the resource allocation plan of the optimal solution. This includes allocating earthwork transportation vehicles, arranging operators, and preparing necessary construction materials. All kinds of resources should be in place before construction begins to avoid resource shortages or scheduling confusion during the construction process. At the same time, human resources need to be reasonably arranged according to the construction schedule to ensure sufficient labor at each construction stage.

[0185] During the actual construction process, construction management personnel should closely monitor the progress of various construction activities to ensure that all operations are strictly carried out in accordance with the optimal plan. Particular attention should be paid to the implementation of the construction route to ensure that excavation, landfill and transportation operations are carried out according to the predetermined route and sequence. Any deviation from the plan should be corrected in a timely manner to avoid affecting the overall efficiency and resource utilization of the project. Equipment scheduling should be carried out strictly according to the plan to ensure that each equipment performs the correct task at the right time and location, and to avoid idling or waiting of equipment.

[0186] At the same time, construction data should be monitored and recorded in real time during the construction process, especially construction progress, resource usage and environmental conditions. This data not only helps to ensure that the construction is carried out according to plan, but can also be used to adjust the construction plan at any time to deal with unexpected situations. For example, when encountering sudden weather changes or geological problems, the construction sequence and equipment scheduling can be appropriately adjusted according to the actual situation to reduce the impact on the project progress.

[0187] After each stage of construction is completed, a quality check should be carried out in a timely manner to ensure that the construction results meet the requirements of the plan. This includes measuring the topography of the construction area, checking the balance of the excavation and fill volume, and ensuring that the volume difference between the fill and the excavation is within an acceptable range. If deviations are found between the construction results and the predetermined plan, the reasons must be analyzed immediately and corrective measures must be taken to prevent the problem from further expansion in subsequent construction.

[0188] In addition, to ensure the smooth progress of construction, construction management personnel should maintain close communication with each construction team to ensure timely communication of information and rapid resolution of problems. Especially in the case of simultaneous operations in multiple construction areas, coordination between the teams is particularly important, and regular on-site meetings should be held to discuss construction progress and solve practical problems.

[0189] Through these specific steps, the earthwork balance optimization of water conservancy projects can be effectively implemented according to the optimal solution generated by the genetic algorithm. The implementation of this step ensures the optimization of construction efficiency, resource utilization and cost control, and ultimately achieves high-quality water conservancy project construction.

[0190] In the above-mentioned embodiment, a method for optimizing the balance between earthwork and filling in water conservancy projects is provided. Correspondingly, the present application also provides a system for optimizing the balance between earthwork and filling in water conservancy projects. Figure 2 , which is a schematic diagram of an embodiment of an intelligent excavation and filling balance optimization system for water conservancy projects of the present application. Since this embodiment, i.e., the second embodiment, is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The system embodiment described below is only illustrative.

[0191] The second embodiment of the present application provides a water conservancy project earthwork intelligent filling and excavation balance optimization system, including:

[0192] The acquisition unit 201 is used to collect data from the construction site of the water conservancy project using a laser scanner, an unmanned aerial survey device, and a GPS positioning device to obtain terrain data and earthwork distribution information;

[0193] A determination unit 202 for determining construction requirements related to the water conservancy project, including construction progress, construction sequence, resource availability, environmental constraints and cost control;

[0194] The obtaining unit 203 is used to optimize the earthwork excavation and filling balance by using a genetic algorithm based on the collected terrain data, earthwork distribution information and the set construction requirements, and obtain an optimal earthwork excavation and filling balance plan, wherein the optimal earthwork excavation and filling balance plan includes a construction route, an equipment scheduling plan and a resource allocation plan;

[0195] The execution unit 204 is used to carry out water conservancy project construction according to the optimal earthwork excavation and filling balance plan.

[0196] A third embodiment of the present application provides an electronic device, the electronic device comprising:

[0197] processor;

[0198] The memory is used to store a program, and when the program is read and executed by the processor, it executes the intelligent filling and excavation balance optimization method for earthwork in water conservancy projects provided in the first embodiment of the present application.

[0199] The fourth embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the intelligent filling and excavation balance optimization method for earth and stone in a water conservancy project provided in the first embodiment of the present application is executed.

[0200] Although the present application is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present application. Any technical personnel in this field may make possible changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims of the present application.

Claims

1. A method for optimizing the balance of earthwork and excavation in a water conservancy project, characterized in that: include: Use laser scanners, drone aerial survey equipment and GPS positioning devices to collect data at the construction site of the water conservancy project to obtain terrain data and earthwork distribution information; Determine construction requirements associated with water projects, including construction schedule, construction sequence, resource availability, environmental constraints, and cost control; Based on the collected terrain data, earthwork distribution information and set construction requirements, a genetic algorithm is used to optimize the earthwork excavation balance to obtain an optimal earthwork excavation balance plan, wherein the optimal earthwork excavation balance plan includes a construction route, an equipment scheduling plan and a resource allocation plan; The water conservancy project is constructed according to the optimal earthwork excavation and filling balance plan.

2. The intelligent excavation and filling balance optimization method for earthwork in water conservancy projects according to claim 1 is characterized in that: The laser scanner, drone aerial survey equipment and GPS positioning device are used to collect data from the construction site of the water conservancy project to obtain terrain data and earthwork distribution information, including: A laser scanner is used to perform high-precision terrain scanning of the construction site. The laser scanner emits laser pulses and measures their reflection time. Based on the reflection time, an initial three-dimensional terrain model is generated that includes terrain undulations, slopes, and boundary information within the construction area. Use drones equipped with aerial survey equipment to take aerial photos of the construction site, and use aerial photography equipment to capture high-resolution images; use image stitching technology to generate a two-dimensional orthophoto map and a three-dimensional image model of the construction site; fuse the generated three-dimensional image model with the initial three-dimensional terrain model to form a comprehensive three-dimensional terrain model; Use GPS positioning devices to accurately locate key points on the construction site; synchronize the GPS positioning information obtained with the comprehensive three-dimensional terrain model to establish a unified geographic coordinate system to ensure the spatial consistency of all terrain data; Comprehensively process laser scanning data, aerial image data and GPS positioning data to generate a high-precision, high-resolution digital terrain model of the construction site; The terrain data and earthwork distribution information are extracted based on the digital terrain model.

3. The intelligent excavation and filling balance optimization method for earthwork in water conservancy projects according to claim 2 is characterized in that: The use of a laser scanner to perform high-precision terrain scanning on the construction site includes: Before laser scanning, the construction site is divided into several scanning sub-areas, and scanning parameters are set for each sub-area, including scanning angle, scanning density and scanning range, to adapt to the terrain characteristics and earthwork distribution characteristics of each sub-area; After completing the scanning of each sub-area, the scanned data of all sub-areas are spliced ​​and integrated to generate an initial 3D terrain model of the construction site, thereby ensuring the integrity and accuracy of the model.

4. The intelligent excavation and filling balance optimization method for water conservancy engineering earthwork according to claim 2 is characterized in that: The laser scanning data, aerial image data and GPS positioning data are processed comprehensively to generate a high-precision and high-resolution digital terrain model of the construction site, including: Perform precision correction on laser scanning data, and adjust the elevation and position information in the laser scanning data by comparing the key point positions obtained by the GPS positioning device; Perform geometric correction on aerial image data to correct the distortion and projection errors in the image so that it is consistent with the coordinate system of laser scanning data and GPS positioning data; In the comprehensive processing process, the location information of high-precision data sources is preferentially used to improve the accuracy and reliability of the final generated digital terrain model of the construction site.

5. The intelligent excavation and filling balance optimization method for water conservancy engineering earthwork according to claim 1 is characterized in that: The method of optimizing earthwork excavation and filling balance by using a genetic algorithm based on the collected terrain data, earthwork distribution information and set construction requirements to obtain an optimal earthwork excavation and filling balance solution includes: Step P101: Initialize a population, the population includes a plurality of individuals; each individual represents a specific earthwork excavation and filling balance scheme, the earthwork excavation and filling balance scheme takes into account the construction route, equipment scheduling plan and resource allocation plan; Step P102: Performing performance evaluation on each individual in the population, wherein the performance evaluation is performed based on a predefined multi-objective fitness function, wherein the multi-objective fitness function comprehensively considers the cut-fill balance, construction efficiency, resource utilization, and cost control objectives; Step P103: Perform non-dominated sorting, sorting the individuals in the population according to their performance on each optimization goal, and comparing the individuals based on their multi-objective fitness scores; based on the non-dominated sorting, select excellent individuals to enter the next generation population; Step P104: performing crossover and mutation operations on the next generation population to generate a new earthwork excavation and filling balance scheme; Step P105: Repeat steps P102 to P104 until a predetermined number of iterations is reached or a specified performance indicator satisfies a stop condition.

6. The intelligent excavation and filling balance optimization method for earthwork in water conservancy projects according to claim 5 is characterized in that: The predefined multi-objective fitness function adopts the following formula 1: Among them, Fitness represents the fitness score; W balance Indicates the balance degree of earthwork excavation and filling; W efficiency Indicates construction efficiency; W utilization Indicates resource utilization; W cost represents cost control; K, α, β, γ and δ are weight coefficients; Among them, the balance degree of earthwork excavation and filling W balance It is calculated by the following formula 2: Among them, V fill,i V represents the filling volume of the i-th construction area; cut,i represents the excavation volume of the i-th construction area; n represents the total number of construction areas; D i represents the average transportation distance of earth and stone from the excavation point to the designated landfill point in the i-th construction area; D max It represents the maximum average transportation distance of earth and stone from the excavation point to the designated landfill point in all construction areas; Construction efficiency efficiency It is calculated by the following formula 3: T actual is the actual construction time; T planned is the planned construction time; U j represents the utilization rate of the jth device; N is the total number of devices; Resource utilization W utilization It is calculated by the following formula 4: Among them, R actual,j represents the actual amount of the jth resource used during the construction process; R available,j represents the available amount of the jth resource; M is the total number of resources; Indicates cost control W cost It is calculated by the following formula 5: Among them, C actual is the actual construction cost; C budget is the budget cost; C transport,j represents the cost of the j-th transportation task; C transport,max is the highest transportation cost among all transportation tasks; P represents the total number of transportation tasks.

7. The intelligent excavation and filling balance optimization method for earthwork in water conservancy projects according to claim 5 is characterized in that: The crossover operation includes: Select at least two preferred earthwork excavation and filling balance solutions as parent individuals; Based on the construction routes, equipment scheduling plans and resource allocation plans of each parent individual, the location of the intersection is dynamically adjusted by analyzing the terrain complexity and earthwork distribution characteristics of the construction area to generate new child individuals, so that the construction routes of the child individuals can better adapt to specific terrain conditions and optimize the efficiency of transportation routes and resource scheduling.

8. The intelligent excavation and filling balance optimization method for water conservancy engineering earthwork according to claim 5 is characterized in that: The mutation operation includes: The variation of construction route parameters adapts to local terrain changes by fine-tuning the locations of key nodes in the route while maintaining the overall structure of the original route; The variation of equipment scheduling plan and resource allocation scheme adjusts resource priority, optimizes the parts with low resource utilization, and reallocates resources to improve overall resource utilization.

9. The intelligent excavation and filling balance optimization method for water conservancy engineering earthwork according to claim 5 is characterized in that: The mutation operation includes: Improve the mutation rate in complex terrain and increase the possibility of exploring new paths; Reduce the mutation rate in simple terrain to maintain the stability of the current solution.

10. An intelligent excavation and filling balance optimization system for earthwork in water conservancy projects, characterized in that: include: The acquisition unit is used to collect data from the construction site of the water conservancy project using laser scanners, drone aerial survey equipment and GPS positioning devices to obtain terrain data and earthwork distribution information; Identification unit for determining construction requirements associated with water projects, including construction schedule, construction sequence, resource availability, environmental constraints, and cost control; An acquisition unit is used to optimize the earthwork excavation and filling balance by using a genetic algorithm based on the collected terrain data, earthwork distribution information and set construction requirements, so as to obtain an optimal earthwork excavation and filling balance scheme, wherein the optimal earthwork excavation and filling balance scheme includes a construction route, an equipment scheduling plan and a resource allocation plan; The execution unit is used to carry out water conservancy project construction according to the optimal earthwork excavation and filling balance plan.

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