GIS-based task scheduling method and device

Abstract

The invention discloses a GIS-based task scheduling method and device, and relates to the technical field of garbage collection. The method comprises the steps of obtaining a road network topological graph of a target area according to a GIS platform; obtaining a first cost matrix and a second cost matrix by using a shortest path algorithm according to the road network topological graph; according to the first cost matrix and the second cost matrix, carrying out attribution division to obtain a transfer station set corresponding to each garbage disposal station and a garbage collection point set corresponding to each transfer station; and for the garbage collection point set corresponding to each transfer station, according to the real-time garbage collection demand, carrying out garbage collection task scheduling of the garbage collection vehicle. The affiliation relation of the garbage disposal stations, the garbage transfer stations and the garbage collection points is divided by minimizing the cost, and reasonable division of resources of the disposal stations is ensured. And according to the real-time garbage collection and transportation requirements, the task arrangement of the garbage collection and transportation vehicle is adjusted, the transportation cost is reduced to the maximum extent, and the efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of garbage removal, and in particular to a task scheduling method and device based on GIS. Background Art

[0002] Garbage collection refers to the process of collecting and transporting domestic garbage or other waste generated by cities, communities, industrial areas, etc. from the source to garbage treatment facilities. Garbage collection is an important part of the urban garbage management system, and plays a vital role in ensuring urban environmental sanitation, promoting resource recycling, reducing pollution and improving the quality of life.

[0003] The existing garbage collection method is a static scheduling with regular routes. The garbage collection truck transports the garbage from the garbage collection points on the route to the transfer station according to the predetermined route, and then transfers it to the terminal processing station from the transfer station. In the traditional static scheduling system, the matching between garbage collection points and transfer stations, and between transfer stations and processing stations is usually fixed. This fixed matching method cannot be flexibly adjusted according to actual conditions, resulting in some processing stations being overloaded for a long time, while other processing stations are idle. For example, with the development of the city, the amount of garbage generated in some areas has increased, and the fixed matching processing stations may not be able to handle the garbage in time, causing garbage backlogs; when they are unable to handle it, the new garbage needs to be transported to an idle processing station farther away, but this cross-station transportation increases the transportation distance, resulting in high garbage collection costs. Summary of the invention

[0004] The purpose of the present invention is to solve the problem of high garbage removal cost mentioned in the above background technology, and to propose a task scheduling method and device based on GIS.

[0005] The first aspect of the present invention provides a task scheduling method based on GIS, the method comprising:

[0006] According to the GIS platform, a road network topology map of the target area is obtained; the road network topology map includes sanitation nodes and road nodes; the sanitation nodes include garbage collection points, garbage transfer stations and garbage treatment stations;

[0007] According to the road network topology diagram, a first cost matrix and a second cost matrix are obtained by using a shortest path algorithm; the first cost matrix is ​​a cost matrix from each garbage transfer station to each garbage treatment station; the second cost matrix is ​​a cost matrix from each garbage collection point to each garbage transfer station;

[0008] According to the first cost matrix and the second cost matrix, the attribution division is performed to obtain a set of transfer stations corresponding to each garbage processing station and a set of garbage collection points corresponding to each transfer station;

[0009] For the set of garbage collection points corresponding to each transfer station, the garbage collection trucks are scheduled for collection tasks based on real-time collection needs.

[0010] Optionally, obtaining the first cost matrix and the second cost matrix by using the shortest path algorithm according to the road network topology graph includes:

[0011] The length of each road section is used as a weight to assign a corresponding edge of the road network topology graph to obtain a first weighted graph;

[0012] The shortest path from each garbage transfer station to each garbage treatment station is calculated through the first weighted graph, and a first cost matrix is ​​obtained according to the weights of the shortest path edges;

[0013] Acquire historical traffic data of the target area; the historical traffic data includes the average traffic speed of each road section;

[0014] According to the average traffic speed and length of each road section, the average passing time of each road section is obtained;

[0015] The average passing time of each road section is used as a weight and assigned to the corresponding edge of the road network topology graph to obtain a second weighted graph;

[0016] The shortest path from each garbage collection point to each garbage transfer station is calculated through the second weighted graph, and a second cost matrix is ​​obtained according to the weights of the shortest path edges.

[0017] Optionally, performing attribution division according to the first cost matrix and the second cost matrix to obtain a set of transfer stations corresponding to each garbage processing station and a set of garbage collection points corresponding to each transfer station includes:

[0018] According to the first cost matrix, each garbage transfer station is matched with a garbage treatment station with the minimum cost, so as to obtain a garbage transfer station set of each garbage treatment station;

[0019] According to the second cost matrix, each garbage collection point is matched with a garbage transfer station with the minimum cost, so as to obtain an initial garbage collection point set of each garbage transfer station;

[0020] According to the garbage transfer station set of each garbage treatment station and the garbage collection point set of each garbage transfer station, a garbage collection point set corresponding to each garbage treatment station is obtained;

[0021] Obtain the historical garbage volume data of each garbage collection point and calculate the daily average garbage volume of each garbage collection point;

[0022] According to the garbage collection points corresponding to each garbage treatment station and the daily average garbage volume of each garbage collection point, the load of each garbage treatment station is obtained;

[0023] If the load of each garbage processing station does not exceed its maximum processing capacity, the initial garbage collection point set is used as the final garbage collection point set; otherwise, the garbage collection points are redistributed to obtain the final garbage collection point set of each transfer station.

[0024] Optionally, the reallocation of garbage collection points includes:

[0025] Step 1: label each garbage treatment station according to its load and maximum processing capacity, and assign the label of each garbage treatment station to its corresponding garbage transfer station and garbage collection point; the labeling includes Class I, Class II and Class III; Class I labeling indicates that the load of the garbage treatment station exceeds its maximum processing capacity; Class II labeling indicates that the load of the garbage treatment station is lower than its maximum processing capacity; Class III labeling indicates that the load of the garbage treatment station is equal to its maximum processing capacity;

[0026] Step 2: Calculate the difference between the load of each type of waste treatment station and its maximum treatment capacity as the excess value;

[0027] Step 3, taking the first-class waste treatment station with the largest excess value as the target first-class waste treatment station;

[0028] Step 4: According to the second cost matrix, the outlier scores of the first-class garbage collection points corresponding to the target first-class garbage disposal stations and their corresponding second-class transfer stations are calculated:

[0029]

[0030] Among them, S j is the outlier fraction of a type of garbage collection point j; D jK represents the time cost between garbage collection point j and garbage transfer station K; D jF represents the time cost between garbage collection point j and garbage transfer station F, where F is the first-class garbage transfer station corresponding to garbage collection point j; G represents the set of second-class garbage transfer stations;

[0031] Step 5: Sort the first N first-class garbage collection points from large to small according to their outlier scores, and remove them from the garbage collection point set corresponding to the target first-class garbage treatment station, and add them to the garbage collection point set of the corresponding second-class transfer station; where N satisfies:

[0032]

[0033] Among them, Q i is the daily average waste volume of the i-th first-class waste collection point; EV is the excess value of the target first-class waste treatment station;

[0034] Step 6: Modify the label of the target Class I waste treatment station to Class III, and update the label of Class II waste treatment stations and their corresponding waste transfer stations and waste collection points according to the new set division;

[0035] Step 7: If there is a type of garbage disposal station, return to step 2; otherwise, end the reallocation process.

[0036] Optionally, the garbage collection truck departs from the transfer station, collects the garbage and returns to the transfer station;

[0037] For each set of garbage collection points corresponding to the transfer station, the garbage collection truck is dispatched according to the real-time collection demand, including:

[0038] For the set of garbage collection points at the target transfer station, the time cost between each two garbage collection points is calculated according to the road network topology map;

[0039] Get the nodes to be processed;

[0040] According to the remaining capacity of the garbage collection truck that has been assigned the task, determine its processable nodes, delete the processable nodes from the nodes to be processed, and obtain the task nodes;

[0041] According to the time cost between task nodes and taking the capacity of the target garbage collection truck as a constraint, path planning is performed to obtain the collection route of the target garbage collection truck.

[0042] A second aspect of the present invention provides a task scheduling device based on GIS, the device comprising:

[0043] A graph structure module is used to obtain a road network topology map of a target area according to a GIS platform; the road network topology map includes sanitation nodes and road nodes; the sanitation nodes include garbage collection points, garbage transfer stations and garbage treatment stations;

[0044] A cost weight calculation module is used to obtain a first cost matrix and a second cost matrix according to the road network topology map by using a shortest path algorithm; the first cost matrix is ​​a cost matrix from each garbage transfer station to each garbage treatment station; the second cost matrix is ​​a cost matrix from each garbage collection point to each garbage transfer station;

[0045] A resource allocation module, configured to perform attribution division according to the first cost matrix and the second cost matrix to obtain a set of transfer stations corresponding to each garbage processing station and a set of garbage collection points corresponding to each transfer station;

[0046] The real-time scheduling module is used to schedule the garbage collection tasks of garbage collection trucks according to the real-time collection needs for each transfer station corresponding to the garbage collection point set.

[0047] Optionally, the cost weight calculation module includes:

[0048] A distance cost weighting module is used to assign the length of each road section as a weight to the corresponding edge of the road network topology graph to obtain a first weighted graph;

[0049] A first cost determination module, configured to calculate the shortest path from each garbage transfer station to each garbage treatment station through the first weighted graph, and obtain a first cost matrix according to the weights of the shortest path edges;

[0050] A first data communication module is used to obtain historical traffic data of a target area; the historical traffic data includes an average traffic speed of each road section;

[0051] A time cost weighting module is used to obtain an average passing time of each road section according to the average traffic speed and length of each road section; the average passing time of each road section is used as a weight to assign the corresponding edge of the road network topology graph to obtain a second weighted graph;

[0052] The second cost determination module is used to calculate the shortest path from each garbage collection point to each garbage transfer station through the second weighted graph, and obtain a second cost matrix according to the weight of the shortest path edge.

[0053] Optionally, the resource allocation module includes:

[0054] A transfer station division module, used for matching each garbage transfer station with a garbage treatment station with the minimum cost according to the first cost matrix, to obtain a garbage transfer station set for each garbage treatment station;

[0055] A collection point division module, used for matching each garbage collection point with a garbage transfer station with the minimum cost according to the second cost matrix, to obtain an initial garbage collection point set of each garbage transfer station;

[0056] The waste source determination module of the waste treatment station is used to obtain the waste collection point set corresponding to each waste treatment station according to the waste transfer station set of each waste treatment station and the waste collection point set of each waste transfer station;

[0057] The second data communication module is used to obtain the historical garbage volume data of each garbage collection point and calculate the daily average garbage volume of each garbage collection point;

[0058] The garbage volume prediction module is used to obtain the load of each garbage processing station according to the garbage collection points corresponding to each garbage processing station and the daily average garbage volume of each garbage collection point;

[0059] The reallocation module is used to use the initial set of garbage collection points as the final set of garbage collection points if the load of each garbage processing station does not exceed its maximum processing capacity; otherwise, the garbage collection points are reallocated to obtain the final set of garbage collection points for each transfer station.

[0060] Optionally, the process of reallocating the garbage collection points by the reallocation module includes:

[0061] Step 1: label each garbage treatment station according to its load and maximum processing capacity, and assign the label of each garbage treatment station to its corresponding garbage transfer station and garbage collection point; the labeling includes Class I, Class II and Class III; Class I labeling indicates that the load of the garbage treatment station exceeds its maximum processing capacity; Class II labeling indicates that the load of the garbage treatment station is lower than its maximum processing capacity; Class III labeling indicates that the load of the garbage treatment station is equal to its maximum processing capacity;

[0062] Step 2: Calculate the difference between the load of each type of waste treatment station and its maximum treatment capacity as the excess value;

[0063] Step 3, taking the first-class waste treatment station with the largest excess value as the target first-class waste treatment station;

[0064] Step 4: According to the second cost matrix, the outlier scores of the first-class garbage collection points corresponding to the target first-class garbage disposal stations and their corresponding second-class transfer stations are calculated:

[0065]

[0066] Among them, S j is the outlier fraction of a type of garbage collection point j; D jK represents the time cost between garbage collection point j and garbage transfer station K; D jF represents the time cost between garbage collection point j and garbage transfer station F, where F is the first-class garbage transfer station corresponding to garbage collection point j; G represents the set of second-class garbage transfer stations;

[0067] Step 5: Sort the first N first-class garbage collection points from large to small according to their outlier scores, and remove them from the garbage collection point set corresponding to the target first-class garbage treatment station, and add them to the garbage collection point set of the corresponding second-class transfer station; where N satisfies:

[0068]

[0069] Among them, Q i is the daily average waste volume of the i-th first-class waste collection point; EV is the excess value of the target first-class waste treatment station;

[0070] Step 6: Modify the label of the target Class I waste treatment station to Class III, and update the label of Class II waste treatment stations and their corresponding waste transfer stations and waste collection points according to the new set division;

[0071] Step 7: If there is a type of garbage disposal station, return to step 2; otherwise, end the reallocation process.

[0072] Optionally, the garbage collection truck departs from the transfer station, collects the garbage and returns to the transfer station;

[0073] The real-time scheduling module includes:

[0074] The garbage collection cost calculation module is used to calculate the time cost between each two garbage collection points according to the road network topology map for the garbage collection point set of the target transfer station;

[0075] A third data communication module, used to obtain a node to be processed;

[0076] The task node determination module is used to determine the processable nodes of the garbage collection trucks assigned with the task according to the remaining capacity, delete the processable nodes from the nodes to be processed, and obtain the task nodes;

[0077] The path planning module is used to perform path planning based on the time cost between task nodes and the capacity of the target garbage collection truck as a constraint to obtain the collection route of the target garbage collection truck.

[0078] Beneficial effects of the present invention:

[0079] The present invention proposes a task scheduling method based on GIS, which comprises: obtaining a road network topology map of a target area according to a GIS platform; the road network topology map comprises sanitation nodes and road nodes; the sanitation nodes comprise garbage collection points, garbage transfer stations and garbage treatment stations; according to the road network topology map, using a shortest path algorithm, obtaining a first cost matrix and a second cost matrix; the first cost matrix is ​​a cost matrix from each garbage transfer station to each garbage treatment station; the second cost matrix is ​​a cost matrix from each garbage collection point to each garbage transfer station; according to the first cost matrix and the second cost matrix, performing attribution division to obtain a transfer station set corresponding to each garbage treatment station and a garbage collection point set corresponding to each transfer station; for the garbage collection point set corresponding to each transfer station, performing garbage collection task scheduling of a garbage collection vehicle according to real-time transportation needs.

[0080] By minimizing the cost of dividing the ownership of garbage treatment stations, garbage transfer stations and garbage collection points, when the amount of garbage in some areas increases, the reasonable division of treatment station resources is ensured, and unnecessary cross-site transportation and cost increases are reduced. And according to the real-time garbage collection needs, the task arrangement of garbage collection trucks is dynamically adjusted. This flexibility enables garbage collection trucks to optimize routes according to the actual situation at the time, thereby minimizing transportation costs and improving efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] The present invention will be further described below in conjunction with the accompanying drawings.

[0082] Figure 1 A flowchart of a task scheduling method based on GIS is provided for an embodiment of the present invention;

[0083] Figure 2 A structural diagram of a GIS-based task scheduling device is provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0084] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0085] The embodiment of the present invention provides a task scheduling method based on GIS. Figure 1 , Figure 1 A flowchart of a GIS-based task scheduling method provided in an embodiment of the present invention. The method comprises the following steps:

[0086] S101, obtaining a road network topology map of the target area based on the GIS platform.

[0087] S102, according to the road network topology map, using the shortest path algorithm to obtain a first cost matrix and a second cost matrix.

[0088] S103, performing attribution division according to the first cost matrix and the second cost matrix to obtain a set of transfer stations corresponding to each garbage processing station and a set of garbage collection points corresponding to each transfer station.

[0089] S104: For each set of garbage collection points corresponding to the transfer station, the garbage collection trucks are dispatched according to the real-time collection demand.

[0090] Among them, the road network topology map includes sanitation nodes and road nodes; sanitation nodes include garbage collection points, garbage transfer stations and garbage treatment stations; the first cost matrix is ​​the cost matrix from each garbage transfer station to each garbage treatment station; the second cost matrix is ​​the cost matrix from each garbage collection point to each garbage transfer station.

[0091] A GIS-based task scheduling method provided by an embodiment of the present invention divides the ownership relationship of garbage treatment stations, garbage transfer stations and garbage collection points by minimizing costs. When the amount of garbage in some areas increases, it ensures the reasonable division of treatment station resources, reduces unnecessary cross-site transportation and cost increases. And dynamically adjusts the task arrangement of garbage collection vehicles according to real-time garbage collection needs. This flexibility enables garbage collection vehicles to optimize routes according to actual conditions at the time, thereby minimizing transportation costs and improving efficiency.

[0092] In one implementation, as a city or region develops, the method can adapt to new nodes (such as newly added garbage collection points or garbage disposal stations) and road network changes, and has good scalability and adaptability.

[0093] In one embodiment, step S102 includes:

[0094] Step 1: Use the length of each road section as a weight and assign it to the corresponding edge of the road network topology map to obtain the first weighted graph; and use the first weighted graph to calculate the shortest path from each garbage transfer station to each garbage treatment station, and obtain the first cost matrix based on the weight of the shortest path edge.

[0095] Step 2: Obtain historical traffic data of the target area; the historical traffic data includes the average traffic speed of each road section; and according to the average traffic speed and length of each road section, the average passing time of each road section is obtained.

[0096] Step three, taking the average passing time of each road section as the weight, assigning it to the corresponding edge of the road network topology map to obtain the second weighted graph; and through the second weighted graph, calculating the shortest path from each garbage collection point to each garbage transfer station, and obtaining the second cost matrix based on the weight of the shortest path edge.

[0097] In one implementation, in the stage from the transfer station to the treatment station, more attention is paid to the economic cost. The driving distance is positively correlated with the economic cost, and the economic cost is reflected by the driving distance. This helps to reduce the economic cost of transporting garbage from a smaller transfer station to a treatment station.

[0098] In one implementation, in the stage from the collection point to the transfer station, more attention is paid to the time cost, and the garbage at the overflowing garbage collection point is cleared as quickly as possible to improve the comfort of citizens. By evaluating the traffic conditions of the road section through historical data and introducing the average passing time of each road section as a weight, the time cost of each path can be calculated more accurately, rather than simply relying on distance or the theoretical shortest distance. This helps to effectively avoid traffic congestion and reduce transportation time.

[0099] In one implementation, the shortest path algorithm may adopt the Dijkstra algorithm.

[0100] In one embodiment, step S103 includes:

[0101] Step 1: According to the first cost matrix, each garbage transfer station is matched with the garbage treatment station with the minimum cost to obtain the garbage transfer station set of each garbage treatment station.

[0102] Step 2: According to the second cost matrix, each garbage collection point is matched with the garbage transfer station with the minimum cost, so as to obtain the initial garbage collection point set of each garbage transfer station.

[0103] Step three: according to the set of garbage transfer stations of each garbage treatment station and the set of garbage collection points of each garbage transfer station, obtain the set of garbage collection points corresponding to each garbage treatment station.

[0104] Step 4: Obtain the historical garbage volume data of each garbage collection point and calculate the daily average garbage volume of each garbage collection point.

[0105] Step 5: Obtain the load of each garbage disposal station according to the garbage collection points corresponding to each garbage disposal station and the daily average garbage volume of each garbage collection point.

[0106] Step 6: If the load of each garbage processing station does not exceed its maximum processing capacity, the initial garbage collection point set is used as the final garbage collection point set; otherwise, the garbage collection points are redistributed to obtain the final garbage collection point set of each transfer station.

[0107] In one implementation, the matching relationship between each garbage transfer station and garbage treatment station and garbage collection point is optimized to ensure that each transfer station and treatment station can be associated with the station with the lowest cost, thereby optimizing resource allocation and reducing unnecessary transportation costs and time.

[0108] In one implementation, the load of each waste treatment station can be accurately predicted by calculating the daily average amount of waste at each waste collection point. If the load is too high, the allocation of waste collection points is automatically adjusted, and load balancing is achieved by reallocating waste collection points. This allows waste treatment stations to reasonably allocate resources based on the specific amount of waste, avoiding situations where the treatment station is overloaded or idle.

[0109] In one embodiment, reallocating garbage collection points includes:

[0110] Step 1: label each garbage treatment station according to its load and maximum processing capacity, and assign the label of each garbage treatment station to its corresponding garbage transfer station and garbage collection point; the labeling includes Class I, Class II and Class III; Class I labeling indicates that the load of the garbage treatment station exceeds its maximum processing capacity; Class II labeling indicates that the load of the garbage treatment station is lower than its maximum processing capacity; Class III labeling indicates that the load of the garbage treatment station is equal to its maximum processing capacity;

[0111] Step 2: Calculate the difference between the load of each type of waste treatment station and its maximum treatment capacity as the excess value;

[0112] Step 3, taking the first-class waste treatment station with the largest excess value as the target first-class waste treatment station;

[0113] Step 4: According to the second cost matrix, calculate the outlier scores of the first-class garbage collection points corresponding to the target first-class garbage treatment stations and their corresponding second-class transfer stations:

[0114]

[0115] Among them, S j is the outlier score of a type of garbage collection point j; D jK represents the time cost between garbage collection point j and garbage transfer station K; D jF represents the time cost between garbage collection point j and garbage transfer station F, where F is the first-class garbage transfer station corresponding to garbage collection point j; G represents the set of second-class garbage transfer stations;

[0116] Step 5: Sort the first N first-class garbage collection points from large to small according to their outlier scores, and remove them from the garbage collection point set corresponding to the target first-class garbage treatment station, and add them to the garbage collection point set of the corresponding second-class transfer station; where N satisfies:

[0117]

[0118] Among them, Q i is the average daily garbage volume of the i-th first-class garbage collection point; EV is the excess value of the target first-class garbage treatment station.

[0119] Step 6: Modify the label of the target Class I waste treatment station to Class III, and update the label of Class II waste treatment stations and their corresponding waste transfer stations and waste collection points according to the new set division;

[0120] Step 7: If there is a type of garbage disposal station, return to step 2; otherwise, end the reallocation process.

[0121] In one implementation, the difference between the cost of the garbage collection point to the existing transfer station and the cost to other transfer stations is calculated. The smaller the difference, the smaller the cost change caused by changing the collection point ownership, and the smaller the impact. The higher the outlier score, the higher the priority of scheduling. By transferring the garbage from these collection points with high outlier scores to other processing stations, the pressure on overloaded garbage processing stations is relieved, and the cost increase caused by the adjustment is also reduced. The reallocation process is repeated until the load of all garbage processing stations is within an acceptable range. Such a mechanism ensures the efficiency and flexibility of the garbage collection system and can cope with changes in demand in different periods.

[0122] In one embodiment, the garbage collection truck departs from the transfer station, collects the garbage and returns to the transfer station;

[0123] Step S104 includes:

[0124] Step 1: For the set of garbage collection points of the target transfer station, the time cost between every two garbage collection points is calculated according to the road network topology map.

[0125] Step 2: Get the node to be processed.

[0126] Step three, according to the remaining capacity of the garbage collection truck to which the task has been assigned, determine its processable nodes, delete the processable nodes from the nodes to be processed, and obtain the task nodes.

[0127] Step 4: According to the time cost between task nodes and with the capacity of the target garbage collection truck as a constraint, path planning is performed to obtain the collection route of the target garbage collection truck.

[0128] In one implementation, the garbage collection point is equipped with a capacity sensor, and the garbage collection point with a garbage volume greater than a preset threshold is regarded as a node to be processed. The preset threshold can be set to 80%.

[0129] In one implementation, the garbage collection point is equipped with a communication QR code, allowing the user to scan the code to send garbage overflow information to the sanitation system, thereby obtaining the node to be processed.

[0130] In one implementation, the garbage truck departs from the transfer station according to the route of the transportation task, returns to the transfer station after being fully loaded, and can depart from the transfer station again after unloading. In this process, due to the real-time increase in the amount of garbage, the garbage truck may return to the transfer station in advance, thus failing to process all the nodes of this task. When planning the path for the target garbage truck ready to depart in the transfer station, according to the remaining capacity of the garbage truck in the task at that time and the real-time amount of garbage at the garbage collection points remaining on the transportation task route, it is determined which nodes to be processed will be processed by the garbage truck in the task, so that when planning the path for the target garbage truck, these nodes do not need to be considered, but the nodes to be processed that are already in the task but not processed need to be considered. For example, the cleaning tasks of vehicle A are A, B, C, D, and E. After it cleans B, on the way to C, vehicle B in the transfer station has completed unloading and is ready to depart. At this time, the nodes to be processed include C, D, and E. At this point, the actual remaining capacity of vehicle A can only carry garbage from C and D, and it is expected to return fully loaded at D. Therefore, when planning the route for vehicle B, the task nodes do not include C and D, but include E, although E was previously planned for vehicle A. This method can re-evaluate the task nodes and route planning to ensure that the tasks of the garbage collection vehicles are reasonably allocated and adjusted in a timely manner. This makes the entire collection process more flexible and can adapt to real-time changes and dynamic task requirements.

[0131] In one implementation, path planning can be performed using a conservation algorithm, the process of which is as follows:

[0132] For each pair of garbage collection points i and j, calculate the total cost of collecting i and j from transfer station T, 2C(T,i)+2C(T,j), minus the cost of going directly from i to j, C(T,i)+C(i,j)+C(T,j), to get the savings value:

[0133] Saving(i,j)=C(T,i)+C(T,j)-C(i,j)

[0134] Where C(x,y) represents the transportation time cost between node x and node y, and C(x,y) = C(y,x). Saving(i,j) represents the degree of saving by directly connecting two points i and j instead of starting from transfer stations separately.

[0135] Sort all point pairs (i, j) whose savings value is greater than 0 by the size of the savings value, from large to small.

[0136] Starting from the transfer station, garbage collection points are selected and merged according to the sorted savings value, and the path is gradually constructed. When merging, check whether the maximum capacity limit of the garbage collection truck is met, and only when it is met can it be merged.

[0137] After the merging is completed, the path is locally optimized. Local optimization algorithms such as 2-opt can be used to further optimize the path.

[0138] In general, the conservation algorithm can give multiple sub-paths that traverse all task nodes. In the embodiment of the present invention, the dynamic change of the garbage volume is considered, and the path is planned in real time when setting off. If there are multiple garbage collection trucks (for example, m trucks) ready to set off, the first m sub-paths are taken as the collection task routes of the m garbage collection trucks.

[0139] The embodiment of the present invention provides a task scheduling device based on GIS. Figure 2 , Figure 2 The structure diagram of a GIS-based task scheduling device provided in an embodiment of the present invention. The device includes:

[0140] The graph structure module is used to obtain the road network topology map of the target area based on the GIS platform.

[0141] The cost weight calculation module is used to obtain the first cost matrix and the second cost matrix according to the road network topology map using the shortest path algorithm.

[0142] The resource allocation module is used to perform attribution division according to the first cost matrix and the second cost matrix to obtain a set of transfer stations corresponding to each garbage processing station and a set of garbage collection points corresponding to each transfer station.

[0143] The real-time scheduling module is used to schedule the garbage collection tasks of garbage collection trucks according to the real-time collection needs for each transfer station corresponding to the garbage collection point set.

[0144] Among them, the road network topology map includes sanitation nodes and road nodes; sanitation nodes include garbage collection points, garbage transfer stations and garbage treatment stations; the first cost matrix is ​​the cost matrix from each garbage transfer station to each garbage treatment station; the second cost matrix is ​​the cost matrix from each garbage collection point to each garbage transfer station.

[0145] A GIS-based task scheduling device provided by an embodiment of the present invention divides the ownership relationship of garbage treatment stations, garbage transfer stations and garbage collection points by minimizing costs. When the amount of garbage in some areas increases, it ensures the reasonable division of treatment station resources, reduces unnecessary cross-site transportation and cost increases. And dynamically adjusts the task arrangement of garbage collection vehicles according to real-time garbage collection needs. This flexibility enables garbage collection vehicles to optimize routes according to actual conditions at the time, thereby minimizing transportation costs and improving efficiency.

[0146] In one embodiment, the cost weight calculation module includes:

[0147] The distance cost weighting module is used to use the length of each road section as a weight to assign the corresponding edge of the road network topology graph to obtain the first weighted graph.

[0148] The first cost determination module is used to calculate the shortest path from each garbage transfer station to each garbage treatment station through the first weighted graph, and obtain a first cost matrix according to the weight of the shortest path edge.

[0149] The first data communication module is used to obtain historical traffic data of the target area; the historical traffic data includes the average traffic speed of each road section.

[0150] The time cost weighting module is used to obtain the average passing time of each road section according to the average traffic speed and length of each road section; the average passing time of each road section is used as a weight to assign the corresponding edge of the road network topology diagram to obtain the second weighted graph.

[0151] The second cost determination module is used to calculate the shortest path from each garbage collection point to each garbage transfer station through the second weighted graph, and obtain a second cost matrix according to the weight of the shortest path edge.

[0152] In one embodiment, the resource allocation module includes:

[0153] The transfer station division module is used to match each garbage transfer station with the garbage treatment station with the minimum cost according to the first cost matrix, so as to obtain the garbage transfer station set of each garbage treatment station.

[0154] The collection point division module is used to match each garbage collection point with the garbage transfer station with the minimum cost according to the second cost matrix, so as to obtain the initial garbage collection point set of each garbage transfer station.

[0155] The waste source determination module of the waste treatment station is used to obtain the waste collection point set corresponding to each waste treatment station according to the waste transfer station set of each waste treatment station and the waste collection point set of each waste transfer station.

[0156] The second data communication module is used to obtain the historical garbage volume data of each garbage collection point and calculate the daily average garbage volume of each garbage collection point.

[0157] The garbage volume prediction module is used to obtain the load of each garbage processing station according to the garbage collection points corresponding to each garbage processing station and the daily average garbage volume of each garbage collection point.

[0158] The reallocation module is used to use the initial set of garbage collection points as the final set of garbage collection points if the load of each garbage processing station does not exceed its maximum processing capacity; otherwise, the garbage collection points are reallocated to obtain the final set of garbage collection points for each transfer station.

[0159] In one embodiment, the process of reallocating the garbage collection points by the reallocation module includes:

[0160] Step 1: Label each garbage treatment station according to its load and maximum processing capacity, and assign the label of each garbage treatment station to its corresponding garbage transfer station and garbage collection point; the labels include Class I, Class II and Class III; Class I labels indicate that the load of the garbage treatment station exceeds its maximum processing capacity; Class II labels indicate that the load of the garbage treatment station is lower than its maximum processing capacity; Class III labels indicate that the load of the garbage treatment station is equal to its maximum processing capacity.

[0161] Step 2: Calculate the difference between the load of each type of garbage treatment station and its maximum processing capacity as the excess value.

[0162] Step three, taking the Class I waste treatment station with the largest excess value as the target Class I waste treatment station.

[0163] Step 4: According to the second cost matrix, calculate the outlier scores of the first-class garbage collection points corresponding to the target first-class garbage treatment stations and their corresponding second-class transfer stations:

[0164]

[0165] Among them, S j is the outlier score of a type of garbage collection point j; D jK represents the time cost between garbage collection point j and garbage transfer station K; D jF represents the time cost between garbage collection point j and garbage transfer station F, where F is the first-class garbage transfer station corresponding to garbage collection point j; G represents the set of second-class garbage transfer stations.

[0166] Step 5: Sort the first N first-class garbage collection points from large to small according to their outlier scores, and remove them from the garbage collection point set corresponding to the target first-class garbage treatment station, and add them to the garbage collection point set of the corresponding second-class transfer station; where N satisfies:

[0167]

[0168] Among them, Q i is the average daily garbage volume of the i-th first-class garbage collection point; EV is the excess value of the target first-class garbage treatment station.

[0169] Step six, modify the labeling of the target Class I waste treatment station to Class III, and update the labeling of Class II waste treatment stations and their corresponding waste transfer stations and waste collection points according to the new set division.

[0170] Step 7: If there is a type of garbage disposal station, return to step 2; otherwise, end the reallocation process.

[0171] In one embodiment, the garbage collection truck departs from the transfer station, collects the garbage and returns to the transfer station;

[0172] The real-time scheduling module includes:

[0173] The garbage collection cost calculation module is used to calculate the time cost between every two garbage collection points according to the road network topology map for the garbage collection point set of the target transfer station.

[0174] The third data communication module is used to obtain the node to be processed.

[0175] The task node determination module is used to determine the processable nodes of the garbage collection trucks that have been assigned tasks according to their remaining capacity, delete the processable nodes from the nodes to be processed, and obtain the task nodes.

[0176] The path planning module is used to perform path planning based on the time cost between task nodes and the capacity of the target garbage collection truck as a constraint to obtain the collection route of the target garbage collection truck.

[0177] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A task scheduling method based on GIS, characterized in that: The method comprises: According to the GIS platform, a road network topology map of the target area is obtained; the road network topology map includes sanitation nodes and road nodes; the sanitation nodes include garbage collection points, garbage transfer stations and garbage treatment stations; According to the road network topology diagram, a first cost matrix and a second cost matrix are obtained by using a shortest path algorithm; the first cost matrix is ​​a cost matrix from each garbage transfer station to each garbage treatment station; the second cost matrix is ​​a cost matrix from each garbage collection point to each garbage transfer station; According to the first cost matrix and the second cost matrix, the attribution division is performed to obtain a set of transfer stations corresponding to each garbage processing station and a set of garbage collection points corresponding to each transfer station; For the set of garbage collection points corresponding to each transfer station, the garbage collection trucks are scheduled for collection tasks based on real-time collection needs.

2. A GIS-based task scheduling method according to claim 1, characterized in that: The obtaining of the first cost matrix and the second cost matrix by using the shortest path algorithm according to the road network topology graph comprises: The length of each road section is used as a weight to assign a corresponding edge of the road network topology graph to obtain a first weighted graph; The shortest path from each garbage transfer station to each garbage treatment station is calculated through the first weighted graph, and a first cost matrix is ​​obtained according to the weights of the shortest path edges; Acquire historical traffic data of the target area; the historical traffic data includes the average traffic speed of each road section; According to the average traffic speed and length of each road section, the average passing time of each road section is obtained; The average passing time of each road section is used as a weight and assigned to the corresponding edge of the road network topology graph to obtain a second weighted graph; The shortest path from each garbage collection point to each garbage transfer station is calculated through the second weighted graph, and a second cost matrix is ​​obtained according to the weights of the shortest path edges.

3. A GIS-based task scheduling method according to claim 2, characterized in that: The attribution division is performed according to the first cost matrix and the second cost matrix to obtain a set of transfer stations corresponding to each garbage processing station and a set of garbage collection points corresponding to each transfer station, including: According to the first cost matrix, each garbage transfer station is matched with a garbage treatment station with the minimum cost, so as to obtain a garbage transfer station set of each garbage treatment station; According to the second cost matrix, each garbage collection point is matched with a garbage transfer station with the minimum cost, so as to obtain an initial garbage collection point set of each garbage transfer station; According to the garbage transfer station set of each garbage treatment station and the garbage collection point set of each garbage transfer station, a garbage collection point set corresponding to each garbage treatment station is obtained; Obtain the historical garbage volume data of each garbage collection point and calculate the daily average garbage volume of each garbage collection point; According to the garbage collection points corresponding to each garbage treatment station and the daily average garbage volume of each garbage collection point, the load of each garbage treatment station is obtained; If the load of each garbage processing station does not exceed its maximum processing capacity, the initial garbage collection point set is used as the final garbage collection point set; otherwise, the garbage collection points are redistributed to obtain the final garbage collection point set of each transfer station.

4. A GIS-based task scheduling method according to claim 3, characterized in that: The reallocation of the garbage collection points comprises: Step 1: Label each garbage treatment station according to its load and maximum processing capacity, and assign the label of each garbage treatment station to its corresponding garbage transfer station and garbage collection point; the labeling includes Class I, Class II and Class III; Class I labeling indicates that the load of the garbage treatment station exceeds its maximum processing capacity; Class II labeling indicates that the load of the garbage treatment station is lower than its maximum processing capacity; Class III labeling indicates that the load of the garbage treatment station is equal to its maximum processing capacity; Step 2: Calculate the difference between the load of each type of waste treatment station and its maximum treatment capacity as the excess value; Step 3, taking the first-class waste treatment station with the largest excess value as the target first-class waste treatment station; Step 4: According to the second cost matrix, the outlier scores of the first-class garbage collection points corresponding to the target first-class garbage disposal stations and their corresponding second-class transfer stations are calculated: Among them, S j is the outlier score of a type of garbage collection point j; D jK represents the time cost between garbage collection point j and garbage transfer station K; D jF represents the time cost between garbage collection point j and garbage transfer station F, where F is the first-class garbage transfer station corresponding to garbage collection point j; G represents the set of second-class garbage transfer stations; Step 5: Sort the first N first-class garbage collection points from large to small according to their outlier scores, and remove them from the garbage collection point set corresponding to the target first-class garbage treatment station, and add them to the garbage collection point set of the corresponding second-class transfer station; where N satisfies: Among them, Q i is the daily average waste volume of the i-th first-class waste collection point; EV is the excess value of the target first-class waste treatment station; Step 6: Modify the label of the target Class I waste treatment station to Class III, and update the label of Class II waste treatment stations and their corresponding waste transfer stations and waste collection points according to the new set division; Step 7: If there is a type of garbage disposal station, return to step 2; otherwise, end the reallocation process.

5. A GIS-based task scheduling method according to claim 3, characterized in that: The garbage truck departs from the transfer station, collects the garbage and returns to the transfer station; For each set of garbage collection points corresponding to the transfer station, the garbage collection truck is dispatched according to the real-time collection demand, including: For the set of garbage collection points at the target transfer station, the time cost between each two garbage collection points is calculated according to the road network topology map; Get the nodes to be processed; According to the remaining capacity of the garbage collection truck that has been assigned the task, determine its processable nodes, delete the processable nodes from the nodes to be processed, and obtain the task nodes; According to the time cost between task nodes and taking the capacity of the target garbage collection truck as a constraint, path planning is performed to obtain the collection route of the target garbage collection truck.

6. A task scheduling device based on GIS, characterized in that: The device comprises: A graph structure module is used to obtain a road network topology map of a target area according to a GIS platform; the road network topology map includes sanitation nodes and road nodes; the sanitation nodes include garbage collection points, garbage transfer stations and garbage treatment stations; A cost weight calculation module is used to obtain a first cost matrix and a second cost matrix according to the road network topology map by using a shortest path algorithm; the first cost matrix is ​​a cost matrix from each garbage transfer station to each garbage treatment station; the second cost matrix is ​​a cost matrix from each garbage collection point to each garbage transfer station; A resource allocation module, configured to perform attribution division according to the first cost matrix and the second cost matrix to obtain a set of transfer stations corresponding to each garbage processing station and a set of garbage collection points corresponding to each transfer station; The real-time scheduling module is used to schedule the garbage collection tasks of garbage collection trucks according to the real-time collection needs for each transfer station corresponding to the garbage collection point set.

7. A GIS-based task scheduling device according to claim 6, characterized in that: The cost weight calculation module includes: A distance cost weighting module is used to assign the length of each road section as a weight to the corresponding edge of the road network topology graph to obtain a first weighted graph; A first cost determination module, configured to calculate the shortest path from each garbage transfer station to each garbage treatment station through the first weighted graph, and obtain a first cost matrix according to the weight of the shortest path edge; A first data communication module is used to obtain historical traffic data of a target area; the historical traffic data includes an average traffic speed of each road section; A time cost weighting module is used to obtain an average passing time of each road section according to the average traffic speed and length of each road section; the average passing time of each road section is used as a weight to assign the corresponding edge of the road network topology graph to obtain a second weighted graph; The second cost determination module is used to calculate the shortest path from each garbage collection point to each garbage transfer station through the second weighted graph, and obtain a second cost matrix according to the weight of the shortest path edge.

8. The GIS-based task scheduling device according to claim 7, characterized in that: The resource allocation module comprises: A transfer station division module, used for matching each garbage transfer station with a garbage treatment station with the minimum cost according to the first cost matrix, to obtain a garbage transfer station set for each garbage treatment station; A collection point division module, used for matching each garbage collection point with a garbage transfer station with the minimum cost according to the second cost matrix, to obtain an initial garbage collection point set of each garbage transfer station; The waste source determination module of the waste treatment station is used to obtain the waste collection point set corresponding to each waste treatment station according to the waste transfer station set of each waste treatment station and the waste collection point set of each waste transfer station; The second data communication module is used to obtain the historical garbage volume data of each garbage collection point and calculate the daily average garbage volume of each garbage collection point; The garbage volume prediction module is used to obtain the load of each garbage processing station according to the garbage collection points corresponding to each garbage processing station and the daily average garbage volume of each garbage collection point; The reallocation module is used to use the initial set of garbage collection points as the final set of garbage collection points if the load of each garbage processing station does not exceed its maximum processing capacity; otherwise, the garbage collection points are reallocated to obtain the final set of garbage collection points for each transfer station.

9. A GIS-based task scheduling device according to claim 8, characterized in that: The process of reallocating the garbage collection points by the reallocation module includes: Step 1: Label each garbage treatment station according to its load and maximum processing capacity, and assign the label of each garbage treatment station to its corresponding garbage transfer station and garbage collection point; the labeling includes Class I, Class II and Class III; Class I labeling indicates that the load of the garbage treatment station exceeds its maximum processing capacity; Class II labeling indicates that the load of the garbage treatment station is lower than its maximum processing capacity; Class III labeling indicates that the load of the garbage treatment station is equal to its maximum processing capacity; Step 2: Calculate the difference between the load of each type of waste treatment station and its maximum treatment capacity as the excess value; Step 3, taking the first-class waste treatment station with the largest excess value as the target first-class waste treatment station; Step 4: According to the second cost matrix, the outlier scores of the first-class garbage collection points corresponding to the target first-class garbage disposal stations and their corresponding second-class transfer stations are calculated: Among them, S j is the outlier score of a type of garbage collection point j; D jK represents the time cost between garbage collection point j and garbage transfer station K; D jF represents the time cost between garbage collection point j and garbage transfer station F, where F is the first-class garbage transfer station corresponding to garbage collection point j; G represents the set of second-class garbage transfer stations; Step 5: Sort the first N first-class garbage collection points from large to small according to their outlier scores, and remove them from the garbage collection point set corresponding to the target first-class garbage treatment station, and add them to the garbage collection point set of the corresponding second-class transfer station; where N satisfies: Among them, Q i is the daily average waste volume of the i-th first-class waste collection point; EV is the excess value of the target first-class waste treatment station; Step 6: Modify the label of the target Class I waste treatment station to Class III, and update the label of Class II waste treatment stations and their corresponding waste transfer stations and waste collection points according to the new set division; Step 7: If there is a type of garbage disposal station, return to step 2; otherwise, end the reallocation process.

10. The GIS-based task scheduling device according to claim 8, characterized in that: The garbage truck departs from the transfer station, collects the garbage and returns to the transfer station; The real-time scheduling module includes: The garbage collection cost calculation module is used to calculate the time cost between each two garbage collection points according to the road network topology map for the garbage collection point set of the target transfer station; A third data communication module, used to obtain a node to be processed; The task node determination module is used to determine the processable nodes of the garbage collection trucks assigned with the task according to the remaining capacity, delete the processable nodes from the nodes to be processed, and obtain the task nodes; The path planning module is used to perform path planning based on the time cost between task nodes and the capacity of the target garbage collection truck as a constraint to obtain the collection route of the target garbage collection truck.

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