Canal waterway project earthwork scheduling method

Abstract

The invention discloses an earth-rock scheduling method for a canal channel project, and the method comprises the steps: S1, carrying out the collection and preprocessing of trajectory data, and collecting the information of earth-rock; s2, a clustering center is extracted from the slag car tracks of each soil taking area and each soil unloading area, corresponding geographic positions are matched, the actual transportation distance is calculated, and a transportation distance matrix is generated; and S3, processing the input data by using a greedy algorithm, and finally outputting an optimal soil unloading area scheduling scheme of each muck truck. The overall efficiency and economic benefits of earthwork transportation are improved.

Description

Technical Field

[0001] The invention relates to the technical field of construction management, and in particular to a method for dispatching earthwork in a canal waterway project. Background Art

[0002] Canal waterway projects usually involve a large amount of earthwork transportation tasks, and the smooth progress of this process has an important impact on the progress and quality of the project. However, due to the large scale of the project, the variety of earthwork types and the complex transportation routes, how to efficiently and reasonably dispatch muck trucks and select the most suitable unloading area has become a key issue in improving project transportation efficiency, reducing transportation costs and reducing environmental impact.

[0003] Most existing methods of dispatching muck trucks rely on simple rules or experience, ignoring the comprehensive consideration of multiple factors in the transportation process, such as the type of earthwork, transportation distance, load conditions in the unloading area, and transportation costs. This traditional dispatching method not only fails to optimize the transportation efficiency of muck trucks, but also easily leads to problems such as overload in the unloading area, high transportation costs, and inaccurate transportation route planning, which in turn affects the overall progress and economic benefits of the project.

[0004] Therefore, in response to the above problems, a method for earthwork scheduling of canal waterway engineering is provided. Summary of the invention

[0005] The purpose of the present invention is to overcome the existing defects and provide a canal waterway engineering earthwork scheduling method, thereby improving the overall efficiency and economic benefits of earthwork transportation.

[0006] The technical solution to achieve the above purpose is: A method for dispatching earthwork in a canal waterway project, comprising: Step S1, trajectory data collection and preprocessing, and earthwork information collection; Step S2, extracting cluster centers from the tracks of the muck trucks in each soil-taking area and soil-unloading area, matching the corresponding geographical locations, calculating the actual transportation distance, and generating a transportation distance matrix; Step S3, use the greedy algorithm to process the input data, and finally output the optimal unloading area scheduling plan for each muck truck.

[0007] Preferably, in step S1, the trajectory data is collected by the Beidou positioning device equipped on each muck truck, including: data recording frequency and recording content, wherein: The data recording frequency is that each muck truck records data once at the same interval; Record content, including: Latitude and longitude, recording the current location of the vehicle; Timestamp, recording the vehicle’s positioning time; Vehicle speed: records the vehicle's speed and provides a reference for driving efficiency; Direction, records the vehicle's driving direction.

[0008] Preferably, in step S1, data preprocessing includes: Location Anomaly Detection: Use distance threshold and timestamp threshold to detect location anomalies; Outlier detection based on time interval and location changes; If the position change exceeds a certain preset threshold, the trajectory point at that position is marked as abnormal; Outlier correction algorithm: The weighted average method is used to correct abnormal data points. If there are missing or abnormal values ​​in the trajectory data, the coordinate information of the adjacent normal points is used for linear interpolation repair, that is: Assume there are two known points ( x 1, y 1) and ( x 2, y 2), and the points that need to be interpolated x Between these two points, the interpolation result is y Calculated by linear equation: ; Trajectory smoothing: Reduce trajectory data fluctuations caused by system noise or errors through Kalman filtering; Time Series Consistency: Make sure the time interval between each track point is within a reasonable range and check if there are any missing or duplicate timestamps.

[0009] Preferably, in step S1, the earthwork information collected includes: Types of earthwork in the borrowing area and unloading area: Onshore earthwork, onshore stonework, underwater earthwork, underwater stonework; Solidity coefficient: The solidity coefficient is a fixed value. Assume that the solidity coefficient is s ij , where i represents the soil area number, j represents the type of earthwork, then, the looseness coefficient s ij : ; In the formula, V loose,ij is the volume in a loose state, V loose,ij is the volume in the original state; Capacity of unloading area: Each unloading area has a maximum capacity; Shipping cost formula: Different types of earthwork, transportation distances, and characteristics of the unloading area will affect the freight rate. The freight rate is a piecewise function based on distance. The freight rate formula for earthwork type is: Assuming that the relationship between transportation cost, earthwork type and transportation distance d is a piecewise function, the specific formula is as follows: ; Where c jθ (d) Earthwork type j Transport to unloading area i The transportation cost, a1, a2, a3 and b1, b2, b3 are the coefficients related to the distance segments respectively, d1, d2 are the segmentation points of the distance.

[0010] Preferably, in step S2, clustering of trajectory points includes: First, the transportation tracks of all vehicles in a period of time are collected, and the tracks are divided into different areas according to soil collection and unloading. c * z Class, among which, c is the total number of soil borrowing areas, z is the total number of unloading areas; The trajectory points of all the muck trucks in each category are spread out in a coordinate system with the horizontal axis as longitude and the vertical axis as latitude to form a scatter plot; Perform DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering on these scatter plots to find the cluster center; Among them, the cluster center is defined as: Assume that a muck truck has n trajectory points, then ; In the formula, P α For the α The position of the vehicle at each trajectory point, ( x α ，y α ) is the α The coordinates of the trajectory points; Through the clustering algorithm, these points are divided into l clusters, each cluster has a cluster center, namely ; In the formula, C ε For the e The cluster centers of the clusters, ( xε ，y ε ) is the e The coordinates of the clusters; The goal of the clustering algorithm is to minimize the sum of the distances between the cluster centers and the trajectory points. The objective function is: ; In the formula, Ⅱ αε is the indicator function, indicating the trajectory point P α Whether it belongs to cluster center C ε .

[0011] Preferably, in step S2, matching the cluster center point obtained by clustering with the known geographical locations of the soil borrowing area and the soil unloading area includes: Assume that the known geographical locations of the soil borrowing area and the soil unloading area are T α= (x Tα ,y Tα ) and U ε= (x Uε ,y Uε ); Cluster center C ε Matching with known geographic locations of borrowing and unloading areas; If a cluster center C ε The position of a certain unloading area U ε If the distance to the geographical location is within a preset range, the cluster center is classified as the unloading area.

[0012] Preferably, in step S2, calculating the actual transport distance and generating a transport distance matrix includes: Based on the clustering results of the trajectories, determine whether each cluster center is the center of the soil taking area or the center of the soil unloading area; The Euclidean distance after their connection is taken as the minimum actual transportation distance from each soil-taking area to the soil-unloading area, and the transportation distance matrix is ​​generated.

[0013] Preferably, in step S3, the input data includes but is not limited to: Transportation distance matrix: represents the distance from the i-th soil extraction area to the i Actual transportation distance to each unloading area; Earthwork compaction coefficient: the compaction coefficient of each type of earthwork; Capacity of unloading area: the maximum capacity of each unloading area; Transportation costs: The transportation costs for each type of earthwork depend on the transportation distance.

[0014] Preferably, in step S3, a greedy algorithm is used to process the input data, including: Get the transport distance matrix D [ β ][ i ],in, β Number the muck truck. i The number of the unloading area indicates the number of the unloading area from the muck truck. β To the unloading area i Transportation distance; Get the loose solid coefficient matrix of earthwork C [ β ], the looseness coefficient of each type of earthwork; Get the capacity limit of the unloading area Cap [ i ], the maximum capacity of each unloading area; Get the shipping cost calculation formula F ( b, i) , calculate the cost of each transportation based on the transportation distance and the compactness coefficient of the earth and stone; Each muck truck needs to select a dumping area for dumping, and the selection criteria are the minimum comprehensive transportation distance, load balance and minimum transportation cost; Calculate the cost per vehicle: Assume that the muck truck β The amount of earth to be transported Q β To the unloading area i , and its transportation cost is expressed as: ; Load balancing calculation: Set current unloading area i The load is Load [ i ], then the load balance degree of the unloading area is expressed as: ; The goal is to make the load of each unloading area as balanced as possible, that is, to make the load ratio as close to 1 as possible; For each dump truck β , select an unloading area i , so that the total cost is minimized, the following rules are adopted: calculate the cost of each unloading area, select the minimum cost, if the costs of multiple unloading areas are the same, then select the unloading area with a smaller load to achieve load balancing; Result output: The final output is the dispatch result of each muck truck, that is, the unloading area where each truck should go. i , The scheduling result is expressed as: ; In the formula, β n For the nThe number of the dump truck. i n For the n The number of the unloading area where the muck truck should go; After selecting the optimal unloading area, update the load of the unloading area and record the dispatching results of the muck truck; Repeat the above steps to continue allocating unloading areas to the remaining muck trucks until all muck trucks are dispatched.

[0015] The beneficial effects of the present invention are as follows: the present invention realizes intelligent analysis of the transportation scheduling of muck trucks by combining cluster analysis of muck truck trajectory data with a greedy algorithm; the actual transportation distance of the muck truck is accurately identified by using the clustering result, and the greedy algorithm fully considers the transportation distance, the looseness coefficient of earth and stone, the capacity of the unloading area, and the weight of the transportation cost configuration to determine the scheduling strategy, thereby significantly improving the scheduling efficiency of muck trucks and reducing the need for manual intervention; it not only solves the problems of low scheduling efficiency, unbalanced load, and high transportation cost of muck trucks in the prior art, but also significantly improves the overall efficiency of earth and stone transportation and reduces transportation costs through intelligent and precise scheduling optimization schemes, providing a more efficient, reasonable and economical solution for engineering projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flow chart of a method for dispatching earthwork in a canal waterway project. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. In the description of the present invention, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside" and the like indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0018] The present invention will be further described below in conjunction with the accompanying drawings.

[0019] like Figure 1 As shown, a method for dispatching earthwork in a canal waterway project includes: Step S1, trajectory data collection and preprocessing, and earthwork information collection.

[0020] In the embodiment, the trajectory data is collected by the Beidou positioning device equipped on each muck truck, including: data recording frequency and recording content, wherein: The data recording frequency is that each muck truck records data once at the same interval; Record content, including: Latitude and longitude, recording the current location of the vehicle; Timestamp, recording the vehicle’s positioning time; Vehicle speed: records the vehicle's speed and provides a reference for driving efficiency; Direction, records the vehicle's driving direction.

[0021] In an embodiment, data preprocessing includes: Location Anomaly Detection: Use distance threshold and timestamp threshold to detect location anomalies; Outlier detection based on time interval and location changes; If the position change exceeds a certain preset threshold, the trajectory point at that position is marked as abnormal; Outlier correction algorithm: The weighted average method is used to correct abnormal data points. If there are missing or abnormal values ​​in the trajectory data, the coordinate information of the adjacent normal points is used for linear interpolation repair, that is: Assume there are two known points ( x 1, y 1) and ( x 2, y 2), and the points that need to be interpolated x Between these two points, the interpolation result is y Calculated by linear equation: ; Trajectory smoothing: Reduce trajectory data fluctuations caused by system noise or errors through Kalman filtering; Time Series Consistency: Make sure the time interval between each track point is within a reasonable range and check if there are any missing or duplicate timestamps.

[0022] In the embodiment, the collected earthwork information includes: Types of earthwork in the borrowing area and unloading area: Onshore earthwork, onshore stonework, underwater earthwork, underwater stonework; Solidity coefficient: The solidity coefficient is a fixed value. Assume that the solidity coefficient is s ij , where i represents the soil area number, j represents the type of earthwork, then, the looseness coefficient s ij : ; In the formula, Vloose,ij is the volume in a loose state, V loose,ij is the volume in the original state; Capacity of unloading area: Each unloading area has a maximum capacity; Shipping cost formula: Different types of earthwork, transportation distances, and characteristics of the unloading area will affect the freight rate. The freight rate is a piecewise function based on distance. The freight rate formula for earthwork type is: Assuming that the relationship between transportation cost, earthwork type and transportation distance d is a piecewise function, the specific formula is as follows: ; Where c jθ (d) Earthwork type j Transport to unloading area i The transportation cost, a1, a2, a3 and b1, b2, b3 are the coefficients related to the distance segments respectively, d1, d2 are the segmentation points of the distance.

[0023] Step S2, extracting cluster centers from the tracks of the muck trucks in each soil taking area and soil unloading area, matching the corresponding geographical locations, calculating the actual transportation distance, and generating a transportation distance matrix.

[0024] In the embodiment, clustering of trajectory points includes: First, the transportation tracks of all vehicles in a period of time are collected, and the tracks are divided into different areas according to soil collection and unloading. c * z Class, among which, c is the total number of soil borrowing areas, z is the total number of unloading areas; The trajectory points of all the muck trucks in each category are spread out in a coordinate system with the horizontal axis as longitude and the vertical axis as latitude to form a scatter plot; Perform DBSCAN clustering on these scatter plots to find the cluster center; Among them, the cluster center is defined as: Assume that a muck truck has n trajectory points, then ; In the formula, P α For the α The position of the vehicle at each trajectory point, ( x α ，y α ) is the α The coordinates of the trajectory points; Through the clustering algorithm, these points are divided into l clusters, each cluster has a cluster center, namely ; In the formula, C ε For the e The cluster centers of the clusters, ( x ε ，y ε ) is the e The coordinates of the clusters; The goal of the clustering algorithm is to minimize the sum of the distances between the cluster centers and the trajectory points. The objective function is: ; In the formula, Ⅱ αε is the indicator function, indicating the trajectory point P α Whether it belongs to cluster center C ε .

[0025] In the embodiment, matching the cluster center point obtained by clustering with the known geographical locations of the soil borrowing area and the soil unloading area includes: Assume that the known geographical locations of the soil borrowing area and the soil unloading area are T α= (x Tα ,y Tα ) and U ε= (x Uε ,y Uε ); Cluster center C ε Matching with known geographic locations of borrowing and unloading areas; If a cluster center C ε The position of a certain unloading area U ε If the distance to the geographical location is within a preset range, the cluster center is classified as the unloading area.

[0026] In the embodiment, calculating the actual transport distance and generating the transport distance matrix includes: Based on the clustering results of the trajectories, determine whether each cluster center is the center of the soil taking area or the center of the soil unloading area; The Euclidean distance after their connection is taken as the minimum actual transportation distance from each soil-taking area to the soil-unloading area, and the transportation distance matrix is ​​generated.

[0027] Step S3, use the greedy algorithm to process the input data, and finally output the optimal unloading area scheduling plan for each muck truck.

[0028] In the embodiment, the input data includes but is not limited to: Transportation distance matrix: represents the distance from the i-th soil extraction area to the i Actual transportation distance to each unloading area; Earthwork compaction coefficient: the compaction coefficient of each type of earthwork; Capacity of unloading area: the maximum capacity of each unloading area; Transportation costs: The transportation costs for each type of earthwork depend on the transportation distance.

[0029] Preferably, in step S3, a greedy algorithm is used to process the input data, including: Get the transport distance matrix D [ β ][ i ],in, β Number the muck truck. i The number of the unloading area indicates the number of the unloading area from the muck truck. β To the unloading area i Transportation distance; Get the loose solid coefficient matrix of earthwork C [ β ], the looseness coefficient of each type of earthwork; Get the capacity limit of the unloading area Cap [ i ], the maximum capacity of each unloading area; Get the shipping cost calculation formula F ( b, i) , calculate the cost of each transportation based on the transportation distance and the compactness coefficient of the earth and stone; Each muck truck needs to select a dumping area for dumping, and the selection criteria are the minimum comprehensive transportation distance, load balance and minimum transportation cost; Calculate the cost per vehicle: Assume that the muck truck β The amount of earth to be transported Q β To the unloading area i , and its transportation cost is expressed as: ; Load balancing calculation: Set current unloading area i The load is Load [ i ], then the load balance degree of the unloading area is expressed as: ; The goal is to make the load of each unloading area as balanced as possible, that is, to make the load ratio as close to 1 as possible; For each dump truck β , select an unloading area i, so that the total cost (considering the transportation distance, compaction coefficient, load balance and transportation cost) is minimized, the following rules are adopted: calculate the cost of each unloading area, select the minimum cost, if the costs of multiple unloading areas are the same, then select the unloading area with a smaller load to achieve load balance; Result output: The final output is the dispatch result of each muck truck, that is, the unloading area where each truck should go. i , The scheduling result is expressed as: ; In the formula, β n For the n The number of the dump truck. i n For the n The number of the unloading area where the muck truck should go; After selecting the optimal unloading area, update the load of the unloading area and record the dispatching results of the muck truck; Repeat the above steps to continue allocating unloading areas to the remaining muck trucks until all muck trucks are dispatched.

[0030] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some or all of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for dispatching earthwork in a canal waterway project, characterized in that: include: Step S1, trajectory data collection and preprocessing, and earthwork information collection; Step S2, extracting cluster centers from the tracks of the muck trucks in each soil-taking area and soil-unloading area, matching the corresponding geographical locations, calculating the actual transportation distance, and generating a transportation distance matrix; Step S3, use the greedy algorithm to process the input data, and finally output the optimal unloading area scheduling plan for each muck truck.

2. A method for dispatching earthwork in a canal waterway project according to claim 1, characterized in that: In step S1, the trajectory data is collected by the Beidou positioning device equipped on each muck truck, including: data recording frequency and recording content, wherein: The data recording frequency is that each muck truck records data once at the same interval; Record content, including: Latitude and longitude, recording the current location of the vehicle; Timestamp, recording the vehicle’s positioning time; Vehicle speed: records the vehicle's speed and provides a reference for driving efficiency; Direction, records the vehicle's driving direction.

3. A method for dispatching earthwork in a canal waterway project according to claim 1, characterized in that: In step S1, data preprocessing includes: Location Anomaly Detection: Use distance threshold and timestamp threshold to detect location anomalies; Outlier detection based on time interval and location changes; If the position change exceeds a certain preset threshold, the trajectory point at that position is marked as abnormal; Outlier correction algorithm: The weighted average method is used to correct abnormal data points. If there are missing or abnormal values ​​in the trajectory data, the coordinate information of the adjacent normal points is used for linear interpolation repair, that is: Assume there are two known points ( x 1, y 1) and ( x 2, y 2), and the points that need to be interpolated x Between these two points, the interpolation result is y Calculated by linear equation: ； Trajectory smoothing: Reduce trajectory data fluctuations caused by system noise or errors through Kalman filtering; Time Series Consistency: Make sure the time interval between each track point is within a reasonable range and check if there are any missing or duplicate timestamps.

4. A method for dispatching earthwork in a canal waterway project according to claim 1, characterized in that: In step S1, the earthwork information collected includes: Types of earthwork in the borrowing area and unloading area: Onshore earthwork, onshore stonework, underwater earthwork, underwater stonework; Solidity coefficient: The solidity coefficient is a fixed value. Assume that the solidity coefficient is s ij , where i represents the soil area number, j represents the type of earthwork, then, the looseness coefficient s ij : ； In the formula, V loose,ij is the volume in a loose state, V loose,ij is the volume in the original state; Capacity of unloading area: Each unloading area has a maximum capacity; Shipping cost formula: Different types of earthwork, transportation distances, and characteristics of the unloading area will affect the freight rate. The freight rate is a piecewise function based on distance. The freight rate formula for earthwork type is: Assuming that the relationship between transportation cost, earthwork type and transportation distance d is a piecewise function, the specific formula is as follows: ； Where c jθ (d) Transport to the unloading area for earthwork type j θ The transportation cost, a1, a2, a3 and b1, b2, b3 are the coefficients related to the distance segments respectively, d1, d2 are the segmentation points of the distance.

5. A method for dispatching earthwork in a canal waterway project according to claim 4, characterized in that: In step S2, clustering of trajectory points includes: First, the transportation tracks of all vehicles in a period of time are collected, and the tracks are divided into different areas according to soil collection and unloading. c * z Class, among which, c is the total number of soil borrowing areas, z is the total number of unloading areas; The trajectory points of all the muck trucks in each category are spread out in a coordinate system with the horizontal axis as longitude and the vertical axis as latitude to form a scatter plot; Perform DBSCAN clustering on these scatter plots to find the cluster center; Among them, the cluster center is defined as: Assume that a muck truck has n trajectory points, then ； In the formula, P α For the α The position of the vehicle at each trajectory point, ( x α ，y α ) is the α The coordinates of the trajectory points; Through the clustering algorithm, these points are divided into l clusters, each cluster has a cluster center, namely ； In the formula, C ε For the ε The cluster centers of the clusters, ( x ε ，y ε ) is the ε The coordinates of the clusters; The goal of the clustering algorithm is to minimize the sum of the distances between the cluster centers and the trajectory points. The objective function is: ; In the formula, Ⅱ αε is the indicator function, indicating the trajectory point P α Whether it belongs to cluster center C ε .

6. A method for dispatching earthwork in a canal waterway project according to claim 5, characterized in that: In step S2, the cluster center point obtained by clustering is matched with the known geographical locations of the soil borrowing area and the soil unloading area, including: Assume that the known geographical locations of the soil borrowing area and the soil unloading area are T α= (x Tα ,y Tα ) and U ε= (x Uε ,y Uε ); Cluster center C ε Matching with known geographic locations of borrowing and unloading areas; If a cluster center C ε The position of a certain unloading area U ε If the distance to the geographical location is within a preset range, the cluster center is classified as the unloading area.

7. A method for dispatching earthwork in a canal waterway project according to claim 6, characterized in that: In step S2, the actual transport distance is calculated to generate a transport distance matrix, including: Based on the clustering results of the trajectories, determine whether each cluster center is the center of the soil taking area or the center of the soil unloading area; The Euclidean distance after their connection is taken as the minimum actual transportation distance from each soil-taking area to the soil-unloading area, and the transportation distance matrix is ​​generated.

8. A method for dispatching earthwork in a canal waterway project according to claim 7, characterized in that: In step S3, input data includes but is not limited to: Transportation distance matrix: represents the distance from the i-th soil extraction area to the θ Actual transportation distance to each unloading area; Earthwork compaction coefficient: the compaction coefficient of each type of earthwork; Capacity of unloading area: the maximum capacity of each unloading area; Transportation costs: The transportation costs for each type of earthwork depend on the transportation distance.

9. A method for dispatching earthwork in a canal waterway project according to claim 8, characterized in that: In step S3, the input data is processed using a greedy algorithm, including: Get the transport distance matrix D [ β ][ θ ],in, β Number the muck truck. θ The number of the unloading area indicates the number of the unloading area from the muck truck. β To the unloading area θ Transportation distance; Get the loose solid coefficient matrix of earthwork C [ β ], the looseness coefficient of each type of earthwork; Get the capacity limit of the unloading area Cap [ θ ], the maximum capacity of each unloading area; Get the shipping cost calculation formula F ( β, θ) , calculate the cost of each transportation based on the transportation distance and the compactness coefficient of the earth and stone; Each muck truck needs to select an unloading area for unloading scheduling. The selection criteria are the minimum comprehensive transportation distance, load balance and minimum transportation cost. Calculate the cost per vehicle: Assume that the muck truck β The amount of earth to be transported Q β To the unloading area θ , and its transportation cost is expressed as: ； Load balancing calculation: Set current unloading area θ The load is Load [ θ ], then the load balance degree of the unloading area is expressed as: ； The goal is to make the load of each unloading area as balanced as possible, that is, to make the load ratio as close to 1 as possible; For each dump truck β , select an unloading area θ , so that the total cost is minimized, the following rules are adopted: calculate the cost of each unloading area, select the minimum cost, if the costs of multiple unloading areas are the same, then select the unloading area with a smaller load to achieve load balancing; Result output: The final output is the dispatch result of each muck truck, that is, the unloading area where each truck should go. θ , The scheduling result is expressed as: ； In the formula, β n For the n The number of the dump truck. θ n For the n The number of the unloading area where the muck truck should go; After selecting the optimal unloading area, update the load of the unloading area and record the dispatching results of the muck truck; Repeat the above steps to continue allocating unloading areas for the remaining muck trucks until all muck trucks are dispatched.

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