Garbage collection path planning method and device, electronic equipment and storage medium

Abstract

The invention discloses a garbage collection path planning method and device, electronic equipment and a storage medium. The method comprises the steps that all nodes of a target area are obtained, a garbage collection and transportation path model is solved based on all the nodes and a preset algorithm, at least two reference garbage transportation paths of the target area are obtained, and each reference garbage transportation path starts from a garbage transportation center, passes through at least one garbage storage point and then returns to the garbage transportation center; updating the reference garbage transportation path by adopting a preset operator to obtain at least one candidate garbage transportation path; and the fitness of the reference garbage transportation path and the candidate garbage transportation path is determined, and the garbage transportation path is screened from the reference garbage transportation path and the candidate garbage transportation path according to the fitness to serve as a target garbage transportation path. According to the invention, reasonable planning of the collection and transportation path is realized under the conditions of large population, large garbage amount, large garbage collection point number and complex path of a large city.

Description

Technical Field

[0001] The present invention relates to the field of urban domestic waste collection and transportation route planning in the environmental protection industry, and particularly to a waste collection route planning method, device, electronic device, and storage medium. Background Art

[0002] With the continuous increase of the urban population, the subsequent continuous increase of urban domestic waste follows. Route planning is an important research hotspot for current urban waste collection and transportation vehicles, and it is also a very challenging problem for vehicle navigation. There are many methods for route planning, such as genetic algorithms, neural network algorithms, ant colony algorithms, etc. Genetic algorithms have good global search capabilities, but they have disadvantages such as slow operation speed, large storage space occupation, and easy premature convergence.

[0003] Existing urban domestic waste collection and transportation route design methods mostly combine artificial neural network prediction models with geographic information system waste collection route optimization to determine the best waste collection route with the minimum driving distance. However, when the number of trash cans is large, the number of collection points is large, the personnel flow is large, and the environment is dynamic, the network structure is huge and the thresholds of neurons need to be continuously changed over time, resulting in slow algorithm convergence speed and easy to fall into local optimum. Summary of the Invention

[0004] The present invention provides a waste collection route planning method, device, electronic device, and storage medium to achieve reasonable planning of collection and transportation routes in the scenario of large urban populations, large amounts of waste, a large number of waste collection points, and complex routes.

[0005] According to one aspect of the present invention, a waste collection route planning method is provided, and the method includes:

[0006] Establish a waste collection and transportation route model, where the waste collection and transportation route model is used to constrain the route length of the vehicle's waste transportation route and the vehicle carbon emissions corresponding to the waste transportation route;

[0007] Obtain all nodes of the target area, and solve the waste collection and transportation route model based on the all nodes and a preset algorithm to obtain at least two reference waste transportation routes of the target area; all nodes of the target area include a waste transfer center and multiple waste storage points, and each reference waste transportation route starts from the waste transfer center, passes through at least one waste storage point, and then returns to the waste transfer center, and the waste storage points included in each waste transportation route are not repeated;

[0008] Updating the reference garbage transportation path using a preset operator to obtain at least one candidate garbage transportation path; the candidate garbage transportation path is a descendant of the reference garbage transportation path, and the candidate garbage transportation path also satisfies the garbage collection and transportation path model;

[0009] Determining the fitness of the reference garbage transportation path and the candidate garbage transportation path, and screening a garbage transportation path from the reference garbage transportation path and the candidate garbage transportation path as the target garbage transportation path according to the fitness.

[0010] According to another aspect of the present invention, there is provided a garbage collection path planning device, which includes:

[0011] A model establishment module for establishing a garbage collection and transportation path model, which is used to constrain the path length of the garbage transportation path of the vehicle and the vehicle carbon emissions corresponding to the garbage transportation path;

[0012] A solution module for obtaining all nodes of the target area, and solving the garbage collection and transportation path model based on the all nodes and a preset algorithm to obtain at least two reference garbage transportation paths of the target area; all nodes of the target area include a garbage transfer center and multiple garbage storage points, and each reference garbage transportation path starts from the garbage transfer center, passes through at least one garbage storage point and then returns to the garbage transfer center, and the garbage storage points included in each garbage transportation path are not repeated;

[0013] An update module for updating the reference garbage transportation path using a preset operator to obtain at least one candidate garbage transportation path; the candidate garbage transportation path is a descendant of the reference garbage transportation path, and the candidate garbage transportation path also satisfies the garbage collection and transportation path model;

[0014] A path determination module for determining the fitness of the reference garbage transportation path and the candidate garbage transportation path, and screening a garbage transportation path from the reference garbage transportation path and the candidate garbage transportation path as the target garbage transportation path according to the fitness.

[0015] According to another aspect of the present invention, there is provided an electronic device, which includes:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor. When executed by the at least one processor, the computer program enables the at least one processor to execute the garbage collection path planning method according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the garbage collection path planning method according to any embodiment of the present invention when executed.

[0020] The technical solution of the embodiment of the present invention establishes a garbage collection and transportation path model. The garbage collection and transportation path model is used to constrain the path length of the garbage transportation path of the vehicle and the vehicle carbon emissions corresponding to the garbage transportation path. By making constraints through the model, the convergence speed of subsequent algorithm calculations can be improved; further, all nodes of the target area are obtained, and based on all nodes and a preset algorithm, the garbage collection and transportation path model is solved to obtain at least two reference garbage transportation paths of the target area; since all nodes of the target area include a garbage transfer center and multiple garbage storage points, each reference garbage transportation path starts from the garbage transfer center, passes through at least one garbage storage point and then returns to the garbage transfer center, and the garbage storage points included in each garbage transportation path are not repeated, ensuring that the same garbage storage points are not repeatedly traversed between each obtained reference garbage transportation path, improving the efficiency of garbage collection; then a preset operator is used to update the reference garbage transportation path to obtain at least one candidate garbage transportation path; the candidate garbage transportation path is the offspring of the reference garbage transportation path, and the candidate garbage transportation path also satisfies the garbage collection and transportation path model; further, the fitness of the reference garbage transportation path and the candidate garbage transportation path is determined, and the garbage transportation path is screened from the reference garbage transportation path and the candidate garbage transportation path according to the fitness as the target garbage transportation path, so as to ensure that the total driving route is the shortest and the carbon emissions generated are the least on the premise that the vehicle loads all the garbage at the collection points, realizing the reasonable planning of the collection and transportation path in the scenario of large cities with a large population, a large amount of garbage, a large number of garbage collection points, and a complex path.

[0021] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0023] Figure 1 is a flowchart of a garbage collection path planning method provided according to an embodiment of the present invention;

[0024] Figure 2 is a flowchart of another garbage collection path planning method provided according to an embodiment of the present invention;

[0025] Figure 3 is an example diagram of an optimal route trajectory map applicable to the embodiments of the present invention;

[0026] Figure 4 is a schematic structural diagram of a garbage collection path planning device provided according to an embodiment of the present invention;

[0027] Figure 5 is a schematic structural diagram of an electronic device for implementing the garbage collection path planning method of the embodiments of the present invention according to an embodiment of the present invention. Detailed Embodiments

[0028] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0029] It should be noted that the terms "first", "second", "third", "reference", "candidate", etc. in the specification and claims of the present invention and the above accompanying drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0030] Embodiment 1

[0031] Figure 1 The following is a flowchart of a garbage collection path planning method provided by an embodiment of the present invention. This embodiment is applicable to the situation of planning the garbage collection path in urban domestic waste. This method can be executed by a garbage collection path planning device, which can be implemented in the form of hardware and / or software, and can be configured in any electronic device with network communication functions. As Figure 1 shown, the garbage collection path planning method of the present invention includes:

[0032] S110. Establish a garbage collection and transportation path model, which is used to constrain the path length of the garbage transportation path of the vehicle and the vehicle carbon emissions corresponding to the garbage transportation path.

[0033] Among them, the garbage collection and transportation path model aims to minimize the path length of the garbage transportation path and the vehicle carbon emissions corresponding to the garbage transportation path. The path length can be the distance from the garbage transfer center, passing through at least one garbage storage point and then returning to the garbage transfer center.

[0034] The optimization problem of the garbage collection and transportation path in the present invention can be described as follows: One or more garbage transportation vehicles of the same model start from the garbage transfer center, pass through several garbage storage points in sequence until all the garbage at all garbage storage points is transported, and then the transportation vehicles return to the garbage transfer center. The optimization goal is to minimize the total driving route and the carbon emissions generated on the premise that all the garbage at the collection points is loaded. The garbage collection and transportation path model is established with the goal of minimizing the path length of the garbage transportation path and the vehicle carbon emissions corresponding to the garbage transportation path.

[0035] There are many influencing factors in the garbage collection and transportation problem in real life. For the convenience of research and without losing scientificity, the following assumptions are made in the present invention: In the area where the vehicle transports garbage, there is only one garbage transfer center and n garbage storage points, and the positions and garbage generation amounts of each garbage storage point fluctuate little. In each garbage transportation path, the garbage storage point cannot be recycled repeatedly. The maximum load of the vehicle is fixed and there is no overloading phenomenon. That is, according to the above situation, further constraints can be imposed on the garbage collection and transportation path model to ensure the accuracy of the garbage collection and transportation path model.

[0036] In this embodiment, optionally, the garbage collection and transportation path model includes an objective function, which aims to minimize the path length and the vehicle carbon emissions, and constrains the garbage collection and transportation path model with the vehicle load corresponding to the garbage transportation path not exceeding the preset carrying capacity.

[0037] Among them, the objective function included in the garbage collection and transportation path model can be expressed by the following formula:

[0038]

[0039] where d ij is the interval distance of the vehicle from node i to node j, and e ij is the interval fuel (oil) consumption of the vehicle from node i to node j; z ij is the interval garbage collection and transportation volume of the vehicle from node i to node j. The garbage transfer center and the garbage storage point are both nodes.

[0040] Furthermore, the carbon emissions during the garbage transportation process of the vehicle can be represented by the relationship between the carbon emissions ε and the average driving speed ν of the vehicle, as shown by the following formula:

[0041]

[0042] where the parameters k, a, b, c, d, e, f are correction factors related to the vehicle and fuel type; for example, when the vehicle self-weight is less than 3.5t and the fuel is diesel, the parameters k, a, b, c, d, e, f are 429.51, -7.8227, 0.0617, 0, 0, 0, 0 in sequence. According to the above formula, the carbon emissions between any two nodes can be calculated. i = 1, 2,..., n; j = 1, 2,..., n.

[0043] In order to better adapt to the garbage collection and transportation path model, the carbon emissions ε of the vehicle from node i to node j in the present invention ij can be represented by the following formula, thus:

[0044]

[0045] where e 0 is the fuel emission factor.

[0046] Furthermore, in order to ensure the accuracy of the garbage collection and transportation path model, it can be constrained, and the following formulas (1) to (6) can be used for constraint:

[0047]

[0048] q ij ≤Qz ij (4);

[0049]

[0050] q ij ≥0 (6);

[0051] Wherein, q is the garbage transportation volume; Q is the maximum carrying capacity. The constraints of formula (1) ensure that each garbage storage point is recycled only once. Formula (2) means that the vehicle arrives at this garbage storage point and must leave from this garbage storage point. Formula (3) means that after the vehicle loads a certain garbage storage point, the increase in the vehicle's load capacity is equal to the garbage generation volume of this garbage storage point. This constraint can avoid abnormal situations such as circular transportation. Formula (4) means that the load of the vehicle between node i and node j cannot exceed the maximum carrying capacity Q, and when the vehicle does not pass through (i, j), the load of this section is 0. Formula (5) means that after the vehicle traverses each garbage storage point, it returns to the garbage transfer center. Formula (6) is the value constraint of the variable.

[0052] In this embodiment, by introducing the objective function in the garbage collection and transportation path model and different constraints on the garbage collection and transportation path model, the accuracy of the model is ensured.

[0053] S120. Obtain all nodes in the target area, and solve the garbage collection and transportation path model based on all nodes and a preset algorithm to obtain at least two reference garbage transportation paths in the target area; all nodes in the target area include a garbage transfer center and multiple garbage storage points. Each reference garbage transportation path starts from the garbage transfer center, passes through at least one garbage storage point, and then returns to the garbage transfer center, and the garbage storage points included in each garbage transportation path are not repeated.

[0054] Wherein, the target area is an area or district that needs garbage transportation; for example, a certain district in a certain city. The beginning and end of the garbage transportation path are both the garbage transfer center.

[0055] Specifically, the preset algorithm can be understood as a model that can perform iterative calculations on the garbage collection and transportation path model. The preset algorithm is used to traverse all nodes in the target area and solve the garbage collection and transportation path model in combination with all nodes, so that all nodes in the target area can be divided into multiple groups, and the node combinations in each group form a reference garbage transportation path. Each reference garbage transportation path includes the garbage transfer center. The garbage storage points included in each garbage transportation path are not repeated to avoid repeated recycling of garbage storage points and affect the transportation and collection efficiency.

[0056] Wherein, the preset algorithm can be the Brain Storm Optimization Algorithm (BSO algorithm), that is, the garbage collection and transportation path model can be solved based on all nodes and the Brain Storm Optimization Algorithm to obtain at least two reference garbage transportation paths in the target area.

[0057] In this embodiment, optionally, the preset algorithm has the functions of clustering and iterative updating. Solving the garbage collection and transportation path model based on all nodes and the preset algorithm to obtain at least two reference garbage transportation paths in the target area includes steps A1 - A4:

[0058] Step A1: Use a preset algorithm to perform regional clustering on all nodes to obtain at least two first garbage transportation paths.

[0059] Specifically, regional clustering can be understood as determining the similarity of each node through the attribute characteristics of the nodes in the target area, grouping the nodes with similarity greater than the preset similarity value into one group, and thus obtaining at least two first garbage transportation paths. Exemplarily, the attribute characteristic can be the distance between nodes, and the similarity can be represented by calculating the Euclidean distance between nodes. That is, if the Euclidean distance between two nodes is less than the preset distance, it means their similarity is greater than the preset similarity value; otherwise, the similarity is less than the preset similarity value.

[0060] Step A2: Input the nodes included in the first garbage transportation path into the garbage collection and transportation path model, and solve the objective function to obtain the first solution parameter.

[0061] Specifically, the first solution parameter can be understood as the value of the objective function. Taking the formula of the objective function mentioned in S110 as an example, the first solution parameter is the value of minf, that is, when the nodes included in the first garbage transportation path are input into the garbage collection and transportation path model, the value of minf calculated by the objective function.

[0062] Step A3: If the first solution parameter is less than or equal to the preset threshold, the first garbage transportation path corresponding to the first solution parameter is used as the reference garbage transportation path.

[0063] Step A4: If the first solution parameter is greater than the preset threshold, use the Gaussian mutation formula to update the first garbage transportation path until the first solution parameter is less than or equal to the preset threshold.

[0064] The technical solution of this embodiment uses a preset algorithm with clustering and iterative update functions to perform regional clustering on all nodes, ensuring the accuracy of obtaining at least two first garbage transportation paths. Further, input the nodes included in the first garbage transportation path into the garbage collection and transportation path model, solve the objective function to obtain the first solution parameter, and compare the first solution parameter with the preset threshold to obtain an accurate reference garbage transportation path, which is convenient for subsequent update of the reference garbage transportation path.

[0065] S130: Use a preset operator to update the reference garbage transportation path to obtain at least one candidate garbage transportation path; the candidate garbage transportation path is the offspring of the reference garbage transportation path and also satisfies the garbage collection and transportation path model.

[0066] Specifically, the preset operator can be understood as an operator that can reorder different nodes in each reference garbage transportation path. The candidate garbage transportation path can be understood as the offspring of the reference garbage transportation path obtained by updating the reference garbage transportation path with the preset operator, and among the offspring that satisfy the garbage collection and transportation path model, that is, ensuring that the value obtained by inputting the candidate garbage transportation path into the objective function is less than the preset threshold, that is, satisfying the objectives of the shortest path length and the minimum vehicle carbon emissions.

[0067] In this embodiment, optionally, the preset operator is a heuristic crossover operator. Using the preset operator to update the reference garbage transportation path to obtain at least one candidate garbage transportation path includes steps B1 - B2:

[0068] Step B1: Process the reference garbage transportation path with the heuristic crossover operator to obtain a third garbage transportation path.

[0069] Among them, the heuristic crossover operator (Heuristic Crossover Operator) is an operation method used to generate new individuals in evolutionary algorithms such as genetic algorithms, aiming to guide the search towards a direction that may produce better solutions by combining the excellent characteristics of parent individuals. In the present invention, the parent individuals are the reference garbage transportation paths.

[0070] Step B2: If the third garbage transportation path satisfies the garbage collection and transportation path model, determine the third garbage transportation path as the candidate garbage transportation path; if the third garbage transportation path does not satisfy the garbage collection and transportation path model, use the heuristic crossover operator to update the reference garbage transportation path until the number of updates is greater than the second preset number of times.

[0071] Furthermore, if the third garbage transportation path satisfies the garbage collection and transportation path model, determine the third garbage transportation path as the candidate garbage transportation path; if the third garbage transportation path does not satisfy the garbage collection and transportation path model, use the heuristic crossover operator to update the reference garbage transportation path until the number of updates is greater than the second preset number of times, including: inputting the nodes included in the third garbage transportation path into the garbage collection and transportation path model, solving the objective function to obtain the third solution parameter; if the third solution parameter is less than or equal to the preset threshold, the third garbage transportation path corresponding to the third solution parameter is used as the reference garbage transportation path; if the third solution parameter is greater than the preset threshold, use the heuristic crossover operator to update the reference garbage transportation path until the number of updates is greater than the second preset number of times.

[0072] The technical solution of this embodiment further updates and processes the reference garbage transportation path using the heuristic crossover operator, further optimizing the reference garbage transportation path, and ensuring the accuracy of the finally obtained candidate garbage transportation path.

[0073] S140. Determine the fitness of the reference waste transportation route and the candidate waste transportation route, and screen the waste transportation route from the reference waste transportation route and the candidate waste transportation route according to the fitness as the target waste transportation route.

[0074] Each reference waste transportation route of the present invention and the candidate waste transportation route corresponding to each reference waste transportation route can actually be directly used as the formal route in the vehicle transportation and collection process. However, in order to make the route more optimal, the waste transportation route is further screened from each reference waste transportation route and the candidate waste transportation route corresponding to each reference waste transportation route according to the fitness as the target waste transportation route. Thus, the target waste transportation route corresponding to each reference waste transportation route can be determined.

[0075] Among them, the fitness is used to measure the degree of adaptation of each individual in the population to the optimization goal of the problem. In the present invention, the population is a waste transportation route group composed of the reference waste transportation route and the candidate waste transportation route, and the individual is each waste transportation route in the waste transportation route group.

[0076] The fitness in the present invention can be used to reflect the length of the waste transportation route. The higher the fitness, the longer the waste transportation route. That is, the fitness can be represented by calculating the length of the waste transportation route of the waste transportation route. Further, screening the waste transportation route from the reference waste transportation route and the candidate waste transportation route according to the fitness as the target waste transportation route includes: taking the waste transportation route corresponding to the fitness greater than the first preset value as the target waste transportation route.

[0077] In addition, the fitness in the present invention can also be represented by the solution value minf obtained by inputting the waste transportation route into the objective function. The smaller the solution value minf, the better the fitness. Further, screening the waste transportation route from the reference waste transportation route and the candidate waste transportation route according to the fitness as the target waste transportation route includes: taking the waste transportation route corresponding to the fitness less than the second preset value as the target waste transportation route.

[0078] Among them, the first preset value and the second preset value can be calculated according to the method of retaining the first preset percentage of the reference waste transportation route and the candidate waste transportation route to obtain the corresponding values. The exemplary preset percentage can be 30%.

[0079] The technical solution of the embodiment of the present invention is to establish a garbage collection and transportation path model, which is used to constrain the path length of the garbage transportation path of the vehicle and the vehicle carbon emissions corresponding to the garbage transportation path. By using the model for constraint, the convergence speed of the subsequent algorithm calculation can be improved; further, all nodes of the target area are obtained, and based on all nodes and a preset algorithm, the garbage collection and transportation path model is solved to obtain at least two reference garbage transportation paths in the target area; since all nodes of the target area include a garbage transfer center and multiple garbage storage points, each reference garbage transportation path starts from the garbage transfer center, passes through at least one garbage storage point and then returns to the garbage transfer center, and the garbage storage points included in each garbage transportation path are not repeated, ensuring that the same garbage storage points are not repeatedly traversed between each obtained reference garbage transportation path, thus improving the efficiency of garbage recycling; then, a preset operator is used to update the reference garbage transportation path to obtain at least one candidate garbage transportation path; the candidate garbage transportation path is the offspring of the reference garbage transportation path, and the candidate garbage transportation path also satisfies the garbage collection and transportation path model; further, the fitness of the reference garbage transportation path and the candidate garbage transportation path is determined, and according to the fitness, the garbage transportation path is screened from the reference garbage transportation path and the candidate garbage transportation path as the target garbage transportation path, so as to ensure that under the premise that the vehicle loads all the garbage at the collection points, the total driving route is the shortest and the carbon emissions generated are the least, realizing the reasonable planning of the collection and transportation path in the scenario of large cities with a large population, a large amount of garbage, a large number of garbage recycling points, and a complex path.

[0080] Embodiment 2

[0081] Figure 2 It is a flowchart of another garbage recycling path planning method provided by the embodiment of the present invention. The technical solution of this embodiment further optimizes the process of using a preset operator to update the reference garbage transportation path to obtain at least one candidate garbage transportation path on the basis of the foregoing embodiment. Among them, the preset operator can be a twist operator. This embodiment can be combined with each optional solution in one or more of the foregoing embodiments. As Figure 2 shown, the garbage recycling path planning method of the present invention includes:

[0082] S210. Establish a garbage collection and transportation path model, which is used to constrain the path length of the garbage transportation path of the vehicle and the vehicle carbon emissions corresponding to the garbage transportation path.

[0083] S220. Obtain all nodes in the target area, solve the garbage collection and transportation path model based on all nodes and a preset algorithm, and obtain at least two reference garbage transportation paths for the target area; all nodes in the target area include a garbage transfer center and multiple garbage storage points. Each reference garbage transportation path starts from the garbage transfer center, passes through at least one garbage storage point, and then returns to the garbage transfer center, and the garbage storage points included in each garbage transportation path are not repeated.

[0084] S230. Use the twist operator to perform the first preset number of updates on the reference garbage transportation paths to obtain at least one candidate garbage transportation path; the candidate garbage transportation path is the offspring of the reference garbage transportation path, and the candidate garbage transportation path also satisfies the garbage collection and transportation path model.

[0085] Among them, the twist operator usually appears in the fields related to genetic algorithms or other evolutionary algorithms, and is used to perform specific transformation operations on individuals to introduce new genetic diversity or guide the search in a specific direction. For the individuals in the present invention, they are reference garbage transportation paths.

[0086] Specifically, determine at least two reference break positions in the reference garbage transportation path corresponding to the current update, and the first reference nodes included in each reference break position; the first reference nodes include at least one node; use the twist operator to reverse the nodes in the first reference nodes to obtain the second reference nodes corresponding to the reference break positions, and exchange the second reference nodes corresponding to the reference break positions according to the preset position exchange method to obtain the second garbage transportation path; if the second garbage transportation path satisfies the garbage collection and transportation path model, determine the second garbage transportation path as the candidate garbage transportation path; if the second garbage transportation path does not satisfy the garbage collection and transportation path model, use the twist operator to update the reference garbage transportation path until the number of updates is greater than the first preset number.

[0087] Among them, the preset position exchange method can be the order of exchange of each reference break position. For example, if there are two reference break positions, namely the first reference break position and the second reference break position, then it can be selected to directly exchange the first reference break position and the second reference break position.

[0088] For example, the reference garbage transportation path is (1, 7, 4, 12, 8, 9, 6, 2, 3, 5, 10, 11, 1). The first reference node corresponding to the first reference break position is (4, 12), and the first reference node corresponding to the second reference break position is (8, 9). The nodes in the first reference node are reversed using the torsion operator to obtain the second reference node corresponding to the reference break position. That is, the second reference node corresponding to the first reference break position is (12, 4), and the second reference node corresponding to the second reference break position is (9, 8). The second reference nodes corresponding to the reference break positions are exchanged according to the preset position exchange method, that is, (12, 4) and (9, 8) are exchanged to obtain the second garbage transportation path as (1, 7, 9, 8, 12, 4, 6, 2, 3, 5, 10, 11, 1).

[0089] Further, if the second garbage transportation path meets the garbage collection and transportation path model, the second garbage transportation path is determined as the candidate garbage transportation path; if the second garbage transportation path does not meet the garbage collection and transportation path model, the reference garbage transportation path is updated using the torsion operator until the number of updates is greater than the first preset number of times, which may include: inputting the nodes included in the second garbage transportation path into the garbage collection and transportation path model, solving the objective function to obtain the second solution parameter; if the second solution parameter is less than or equal to the preset threshold, the second garbage transportation path corresponding to the second solution parameter is used as the reference garbage transportation path; if the second solution parameter is greater than the preset threshold, the second garbage transportation path is updated using the torsion operator until the number of updates is greater than the first preset number of times.

[0090] S240. Determine the fitness of the reference garbage transportation path and the candidate garbage transportation path, and screen the garbage transportation path from the reference garbage transportation path and the candidate garbage transportation path as the target garbage transportation path.

[0091] Exemplarily, 1 garbage transfer station and 30 garbage storage points are selected and simulated using the method of the present invention. The garbage transfer station is numbered 1, and the other garbage storage points are numbered in sequence. The coordinates of the transfer station and the storage points and the garbage generation amount are shown in Table 1 below. The initial parameters of the algorithm are set as the average vehicle driving speed V = 50 km / h, and the carbon emission standard per liter of gasoline. After simulating using the method of the present invention, five target garbage transportation paths with the shortest route and the least carbon emissions generated are obtained, as Figure 3 shown.

[0092] Table 1 Coordinates of the garbage transfer station and the storage points and the garbage generation amount

[0093]

[0094] The technical solution of the embodiment of the present invention is to establish a garbage collection and transportation path model, which is used to constrain the path length of the garbage transportation path of the vehicle and the vehicle carbon emissions corresponding to the garbage transportation path. By making constraints through the model, the convergence speed of subsequent algorithm calculations can be improved; further obtain all nodes of the target area, and solve the garbage collection and transportation path model based on all nodes and a preset algorithm to obtain at least two reference garbage transportation paths in the target area; because all nodes of the target area include a garbage transfer center and multiple garbage storage points, each reference garbage transportation path starts from the garbage transfer center, passes through at least one garbage storage point and then returns to the garbage transfer center, and the garbage storage points included in each garbage transportation path are not repeated, ensuring that the same garbage storage points will not be repeatedly walked between each obtained reference garbage transportation path, improving the efficiency of garbage recycling; then use the torsion operator to update the reference garbage transportation path for the first preset number of times to obtain at least one candidate garbage transportation path; the candidate garbage transportation path is the offspring of the reference garbage transportation path, and the candidate garbage transportation path also satisfies the garbage collection and transportation path model; the torsion operator introduces new gene combinations by changing the specific structure of the reference garbage transportation path, increasing the genetic diversity of the population, enabling the algorithm to have the opportunity to jump out of the local optimum and continue to explore a broader solution space. Further determine the fitness of the reference garbage transportation path and the candidate garbage transportation path, and screen the garbage transportation path from the reference garbage transportation path and the candidate garbage transportation path as the target garbage transportation path according to the fitness, so as to ensure that under the premise that the vehicle loads all the garbage at the collection points, the total driving route is the shortest and the carbon emissions generated are the least, realizing the reasonable planning of the collection and transportation path in the scenario of large cities with a large population, a large amount of garbage, a large number of garbage collection points, and a complex path.

[0095] Embodiment III

[0096] Figure 4 FIG. is a schematic structural diagram of a garbage collection path planning device provided by an embodiment of the present invention. This embodiment is applicable to the situation of planning the urban domestic garbage collection path. The garbage collection path planning device can be implemented in the form of hardware and / or software, and the garbage collection path planning device can be configured in any electronic device with network communication functions. As Figure 3 shown, the garbage collection path planning device of the present invention includes:

[0097] A model establishment module 310, configured to establish a garbage collection and transportation path model, where the garbage collection and transportation path model is used to constrain the path length of the garbage transportation path of the vehicle and the vehicle carbon emissions corresponding to the garbage transportation path;

[0098] A solution module 320, configured to obtain all nodes in a target area, solve the waste collection and transportation path model based on the all nodes and a preset algorithm, and obtain at least two reference waste transportation paths for the target area; all nodes in the target area include a waste transfer center and multiple waste storage points, and each of the reference waste transportation paths starts from the waste transfer center, passes through at least one waste storage point and then returns to the waste transfer center, and the waste storage points included in each waste transportation path are not repeated;

[0099] An update module 330, configured to update the reference waste transportation paths by using a preset operator to obtain at least one candidate waste transportation path; the candidate waste transportation path is a child generation of the reference waste transportation path, and the candidate waste transportation path also satisfies the waste collection and transportation path model;

[0100] A path determination module 340, configured to determine the fitness of the reference waste transportation paths and the candidate waste transportation paths, and screen a waste transportation path from the reference waste transportation paths and the candidate waste transportation paths as a target waste transportation path according to the fitness; the fitness is used to reflect the length of the waste transportation path, and the higher the fitness, the longer the waste transportation path.

[0101] Based on the above embodiments, optionally, the waste collection and transportation path model includes an objective function, the objective function aims at the shortest path length and the minimum vehicle carbon emissions, and restricts the waste collection and transportation path model with the vehicle load corresponding to the waste transportation path not exceeding a preset carrying capacity.

[0102] Based on the above embodiments, optionally, the preset algorithm has functions of clustering and iterative update, and the solution module is configured to: perform regional clustering on the all nodes by using the preset algorithm to obtain at least two first waste transportation paths; input the nodes included in the first waste transportation paths into the waste collection and transportation path model, and solve the objective function to obtain a first solution parameter; if the first solution parameter is less than or equal to a preset threshold, the first waste transportation path corresponding to the first solution parameter is used as a reference waste transportation path; if the first solution parameter is greater than the preset threshold, update the first waste transportation path by using a Gaussian mutation formula until the first solution parameter is less than or equal to the preset threshold.

[0103] Based on the above embodiments, optionally, the preset algorithm is a brainstorm optimization algorithm.

[0104] Based on the above embodiments, optionally, the preset operator is a twist operator, and the update module includes a first update unit, configured to: perform a first preset number of updates on the reference waste transportation paths by using the twist operator to obtain at least one candidate waste transportation path.

[0105] Based on the above embodiments, optionally, the first update unit is configured to: determine at least two reference break positions in the reference garbage transportation path corresponding to the current update, and the first reference nodes included in each of the reference break positions; the first reference nodes include at least one node; use a torsion operator to reverse the nodes in the first reference nodes to obtain second reference nodes corresponding to the reference break positions, and exchange the second reference nodes corresponding to the reference break positions according to a preset position exchange method to obtain a second garbage transportation path; if the second garbage transportation path meets the garbage collection and transportation path model, determine the second garbage transportation path as the candidate garbage transportation path; if the second garbage transportation path does not meet the garbage collection and transportation path model, use the torsion operator to update the reference garbage transportation path until the number of updates is greater than a first preset number of times.

[0106] Based on the above embodiments, optionally, the preset operator is a heuristic crossover operator, and the second update unit is configured to: use the heuristic crossover operator to process the reference garbage transportation path to obtain a third garbage transportation path; if the third garbage transportation path meets the garbage collection and transportation path model, determine the third garbage transportation path as the candidate garbage transportation path; if the third garbage transportation path does not meet the garbage collection and transportation path model, use the heuristic crossover operator to update the reference garbage transportation path until the number of updates is greater than a second preset number of times.

[0107] The garbage collection path planning device provided by the embodiments of the present invention can execute the garbage collection path planning method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0108] Embodiment 4

[0109] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0110] Figure 5 The structural schematic diagram of an electronic device that can be used to implement the garbage collection path planning method of the embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0111] As shown Figure 5 in FIG. 1, the electronic device 10 includes at least one processor 11 and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0112] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0113] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the garbage collection path planning method.

[0114] In some embodiments, the garbage collection path planning method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the garbage collection path planning method described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the garbage collection path planning method by any other suitable means (e.g., by means of firmware).

[0115] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0116] A computer program for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0117] In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium may be a machine-readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0118] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0119] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0120] The computing system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0121] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is imposed herein.

[0122] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A garbage collection path planning method, characterized in that: The method comprises: Establishing a garbage collection and transportation path model, wherein the garbage collection and transportation path model is used to constrain the path length of the garbage transportation path of the vehicle and the carbon emissions of the vehicle corresponding to the garbage transportation path; Obtain all nodes in the target area, solve the garbage collection and transportation path model based on all nodes and a preset algorithm, and obtain at least two reference garbage transportation paths in the target area; all nodes in the target area include a garbage transfer center and multiple garbage storage points, each of the reference garbage transportation paths starts from the garbage transfer center, passes through at least one garbage storage point and then returns to the garbage transfer center, and the garbage storage points included in each garbage transportation path are not repeated; The reference garbage transportation path is updated by using a preset operator to obtain at least one candidate garbage transportation path; the candidate garbage transportation path is a descendant of the reference garbage transportation path, and the candidate garbage transportation path also satisfies the garbage collection and transportation path model; The fitness of the reference garbage transportation path and the candidate garbage transportation path is determined, and a garbage transportation path is selected from the reference garbage transportation path and the candidate garbage transportation path as a target garbage transportation path according to the fitness.

2. The method according to claim 1, characterized in that The garbage collection and transportation path model includes an objective function, which aims to minimize the path length and the vehicle carbon emissions, and constrains the garbage collection and transportation path model by requiring that the vehicle load corresponding to the garbage transportation path shall not exceed a preset load.

3. The method according to claim 2, characterized in that The preset algorithm has the functions of clustering and iterative updating. The garbage collection and transportation path model is solved based on all the nodes and the preset algorithm to obtain at least two reference garbage transportation paths in the target area, including: Using the preset algorithm to perform regional clustering on all the nodes to obtain at least two first garbage transportation paths; Inputting the nodes included in the first garbage transportation path into the garbage collection and transportation path model, solving the objective function to obtain a first solution parameter; If the first solution parameter is less than or equal to a preset threshold, the first garbage transportation path corresponding to the first solution parameter is used as a reference garbage transportation path; If the first solution parameter is greater than a preset threshold, the Gaussian variation formula is used to update the first garbage transportation path until the first solution parameter is less than or equal to the preset threshold.

4. The method according to claim 1 or 3, characterized in that: The preset algorithm is a brainstorming optimization algorithm.

5. The method according to claim 1, characterized in that The preset operator is a twist operator, and the reference garbage transportation path is updated by using the preset operator to obtain at least one candidate garbage transportation path, including: The reference garbage transportation path is updated a first preset time by using a twist operator to obtain at least one candidate garbage transportation path.

6. The method according to claim 5, characterized in that The reference garbage transportation path is updated a preset number of times using a preset operator to obtain at least one candidate garbage transportation path, including: Determine at least two reference break positions in the reference garbage transportation path corresponding to the current update, and a first reference node included in each of the reference break positions; the first reference node includes at least one node; Reversing the nodes in the first reference node by using a twist operator to obtain a second reference node corresponding to the reference fracture position, exchanging the second reference node corresponding to the reference fracture position according to a preset position exchange method to obtain a second garbage transportation path; If the second garbage transportation path satisfies the garbage collection and transportation path model, determining the second garbage transportation path as the candidate garbage transportation path; If the second garbage transportation path does not satisfy the garbage collection and transportation path model, a twist operator is used to update the reference garbage transportation path until the number of updates is greater than a first preset number.

7. The method according to claim 1, characterized in that The preset operator is a heuristic crossover operator, and the reference garbage transportation path is updated by using the preset operator to obtain at least one candidate garbage transportation path, including: Processing the reference garbage transportation path using a heuristic crossover operator to obtain a third garbage transportation path; If the third garbage transportation path satisfies the garbage collection and transportation path model, determining the third garbage transportation path as the candidate garbage transportation path; If the third garbage transportation path does not satisfy the garbage collection and transportation path model, a heuristic crossover operator is used to update the reference garbage transportation path until the number of updates is greater than a second preset number of times.

8. A garbage collection path planning device, characterized in that: The device comprises: A model building module, used to build a garbage collection and transportation path model, wherein the garbage collection and transportation path model is used to constrain the path length of the garbage transportation path of the vehicle and the carbon emissions of the vehicle corresponding to the garbage transportation path; A solution module is used to obtain all nodes in the target area, solve the garbage collection and transportation path model based on all nodes and a preset algorithm, and obtain at least two reference garbage transportation paths in the target area; all nodes in the target area include a garbage transfer center and multiple garbage storage points, each of the reference garbage transportation paths starts from the garbage transfer center, passes through at least one garbage storage point and then returns to the garbage transfer center, and the garbage storage points included in each garbage transportation path are not repeated; An updating module, used to update the reference garbage transportation path by using a preset operator to obtain at least one candidate garbage transportation path; the candidate garbage transportation path is a descendant of the reference garbage transportation path, and the candidate garbage transportation path also satisfies the garbage collection and transportation path model; The path determination module is used to determine the fitness of the reference garbage transportation path and the candidate garbage transportation path, and select a garbage transportation path from the reference garbage transportation path and the candidate garbage transportation path as a target garbage transportation path according to the fitness.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the garbage collection path planning method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the garbage collection path planning method according to any one of claims 1 to 7 when executed.

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