Waste clearance vehicle path optimization method based on Internet of Things and related products

Abstract

The invention relates to the technical field of traffic transportation, the Internet of Things and environmental protection, in particular to a waste clearance vehicle path optimization method based on the Internet of Things and a related product, and the method comprises the following steps: generating a reference access block according to a waste clearance period; generating first waste access information according to the reference access chunk; generating second waste access information according to the access degree of freedom; destroying and repairing the first waste access information and the second waste access information to obtain third waste access information; and selecting a waste clearing vehicle path according to the waste clearing vehicle path costs corresponding to the first waste access information, the second waste access information and the third waste access information. According to the invention, the cost of the waste clearing vehicle path is reduced, and the calculation efficiency of the waste clearing vehicle path is improved.

Description

Technical Field

[0001] The present invention relates to the technical fields of transportation, Internet of Things, and environmental protection, and particularly relates to a method for optimizing the route of waste collection vehicles based on the Internet of Things and related products. Background Art

[0002] With the acceleration of the urbanization process, the urban population is expanding day by day, and the accompanying urban waste is increasing day by day. The urban waste collection and transportation capacity is crucial for the development of the city. The commonly used waste collection and transportation strategy is to send vehicles along fixed routes at fixed times to collect waste from fixed waste collection points. This waste collection and transportation strategy does not consider the daily waste disposal situation at the waste collection points, which will not only cause waste overflow at the waste collection points with a large amount of waste disposal, but also result in high costs for the fixed vehicle routes. Summary of the Invention

[0003] In order to solve the above technical problems, embodiments of the present invention disclose a method for optimizing the route of waste collection vehicles based on the Internet of Things and related products.

[0004] Embodiments of the present invention provide a method for optimizing the route of waste collection vehicles based on the Internet of Things, including the following steps:

[0005] Step S101: Generate a reference access block according to the waste collection cycle; repeatedly fill the reference access block into the waste collection planning period until the remaining filling bits in the waste collection planning period are less than the number of bits of the reference access block, and use the reference filling bits to fill the remaining filling bits in the waste collection planning period to obtain a first list; generate first waste access information according to the first list and the number of waste collection points;

[0006] Step S102: Calculate the access freedom according to the remaining filling bits and the waste collection cycle;

[0007] Step S103: Construct a first set according to the access freedom, divide each element in the first set to obtain a corresponding second set for each element, and the size of each element in the second set is equal to the number of reference access blocks in the waste collection planning period; select elements from the first set, and use the reference filling bits to fill the first list according to the selected elements; delete the corresponding number of reference filling bits from the reference access blocks in the first list according to the second set corresponding to the selected elements from the first set to obtain a second list; generate second waste access information according to the second list and the number of waste collection points;

[0008] Step S104: Destroy and repair the first waste access information and the second waste access information to obtain third waste access information;

[0009] Step S105: Select the waste collection vehicle route according to the waste collection vehicle route costs corresponding to the first waste access information, the second waste access information, and the third waste access information.

[0010] Preferably, before the step of damaging and repairing the first waste access information and the second waste access information to obtain the third waste access information, the following is further included:

[0011] Perform capacity repair on the first waste access information and the second waste access information according to the waste accumulation distribution at the waste collection points.

[0012] Preferably, the calculating the access freedom degree according to the remaining filling positions and the waste collection cycle includes:

[0013] Calculate the difference between the waste collection cycle and the remaining filling positions, and reduce the obtained difference by a set value to obtain the access freedom degree.

[0014] Preferably, the constructing the first set includes:

[0015] Obtain positive integers not greater than the access freedom degree and construct the first set.

[0016] Preferably, the reference access block represents an access mode that satisfies the waste collection cycle.

[0017] Preferably, the reference filling position represents not accessing the waste collection point.

[0018] Preferably, the damaging and repairing the first waste access information and the second waste access information includes:

[0019] Calculate the waste accumulation distribution similarity of the waste collection point pair according to the waste accumulation distribution at the waste collection points within the waste collection planning period; determine the first weight according to the dispersion degree and the mean value of all waste accumulation distribution similarities;

[0020] Cluster the waste collection points according to the physical distance between the waste collection points to obtain waste collection point clusters; determine the second weight according to the average aggregation degree of all waste collection point clusters;

[0021] Multiply the waste accumulation distribution similarity corresponding to the waste collection point by the first weight to obtain the first similarity corresponding to the waste collection point; multiply the physical distance between the waste collection points by the second weight to obtain the second similarity corresponding to the waste collection point; add the first similarity and the second similarity to obtain the third similarity corresponding to the waste collection point;

[0022] Select waste collection points according to the third similarity corresponding to the waste collection points, damage the first waste access information and the second waste access information according to the selected waste collection points, and then perform waste access repair to obtain the third waste access information.

[0023] Preferably, the step of selecting waste collection points according to the third similarity corresponding to the waste collection points includes: randomly selecting waste collection points; and selecting other waste collection points according to the third similarity between the selected waste collection points and other waste collection points to obtain the selected waste collection points.

[0024] In another embodiment of the present invention, a computer device is further provided. The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a method for optimizing the path of waste collection vehicles based on the Internet of Things is implemented.

[0025] In another embodiment of the present invention, a computer-readable storage medium is further provided. The storage medium stores a computer program, and when the computer program is executed, a method for optimizing the path of waste collection vehicles based on the Internet of Things is implemented.

[0026] The technical solution provided by the embodiments of the present invention has at least the following advantages compared with the prior art:

[0027] The present invention provides a method for optimizing the path of waste collection vehicles based on the Internet of Things. The waste access information within the waste collection planning period is generated based on the benchmark access chunks and the benchmark filling bits, which not only has high generation efficiency but also improves the quality of the waste access information, can obtain a high-quality waste collection vehicle path in a short time, and reduces the cost of the waste collection vehicle path. Traditional waste collection uses a fixed-time and fixed-point method. The method for optimizing the path of waste collection vehicles based on the Internet of Things considers the cumulative distribution of waste and adjusts the waste access information according to the cumulative distribution of waste to prevent garbage overflow at the collection points, improves the residents' experience, and reasonable access scheduling reduces the waste collection cost. The present invention determines the weighted similarity between waste collection points according to the similarity of waste cumulative distribution and distance similarity between waste collection points, and performs dynamic weight adjustment, which improves the accuracy of the similarity measurement of collection points, further improves the adjustment efficiency of waste access information, thereby improving the quality of waste access information and the optimization quality of vehicle paths, and reducing the cost of waste collection vehicle paths. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is an exemplary flowchart of a method for optimizing the path of waste collection vehicles based on the Internet of Things according to the first embodiment of the present invention. Detailed Implementation Modes

[0029] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the drawings denote elements having the same or similar functions. Although various aspects of the embodiments are shown in the drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0030] The term "exemplary" used herein means "serving as an example, embodiment, or illustration". Any embodiment described as "exemplary" herein is not necessarily to be construed as superior or better than other embodiments.

[0031] In addition, for a better illustration of the present disclosure, numerous specific details are given in the following detailed implementation modes. Those skilled in the art should understand that the present disclosure can be implemented without some specific details. In some instances, methods, means, elements, and circuits well-known to those skilled in the art are not described in detail so as to highlight the gist of the present disclosure. A method for optimizing the path of waste collection vehicles based on the Internet of Things provided by an embodiment of the present invention.

[0032] The traditional waste collection and transportation strategy is to send vehicles along fixed routes at fixed times to collect waste. For example, waste is collected along a fixed route every two days. This strategy does not consider the waste disposal pattern. During the peak waste disposal period, waste overflows, and when the waste disposal is less, the vehicle load is small, resulting in a waste of vehicle operation costs.

[0033] The accumulation of waste at waste collection points is periodic. The periodicity of the waste accumulation distribution at waste collection points with a large population aggregation is more obvious, such as communities. Usually, the amount of waste disposed is more from Friday to Sunday and relatively less from Monday to Thursday. This has been supported by statistical data from scholars at home and abroad. Therefore, bins with built-in sensors can be used to intelligently obtain the amount of waste disposed, and the waste disposal information of each waste collection point can be obtained through the Internet of Things. Further, a low-cost and high-efficiency waste collection vehicle path can be determined based on the waste disposal information of the waste collection points.

[0034] Figure 1 A flowchart showing a method for optimizing the path of waste collection vehicles based on the Internet of Things according to a first embodiment of the present invention is shown. As Figure 1 shown, the method includes steps S101, S102, S103, S104, and S105, which are specifically as follows:

[0035] Step S101: Generate a reference access block according to the waste collection cycle; repeatedly fill the reference access block into the waste collection planning period until the remaining filling bits in the waste collection planning period are less than the number of bits of the reference access block, and use the reference filling bits to fill the remaining filling bits in the waste collection planning period to obtain a first list; generate first waste access information according to the first list and the number of waste collection points.

[0036] The waste collection cycle represents the minimum time interval for waste collection. For example, if the waste collection cycle is 3, each waste collection point is visited at least once within any consecutive 3 days, and the number of consecutive non-visited days cannot exceed 2 days. The reference access block represents the access method that meets the waste collection cycle. Optionally, the reference access block represents that the first few days of the cycle are not visited and the last day of the cycle must be visited. For example, when the waste collection cycle is 3, the reference access block is 001, where 0 represents not visited and 1 represents visited.

[0037] The waste collection planning period is set according to the implementation scenario. Optionally, the waste collection planning period is set to 7 days. The reference filling bit represents not visiting the waste collection point. For example, the reference filling bit is set to 0. When the waste collection planning period is set to 7 days and the waste collection cycle is 3, the waste collection planning period is filled with 0010010, that is, the first list. The first list represents the access method of a waste collection point within the waste collection planning period, 1 represents visited, and 0 represents not visited. Sequentially splice multiple first lists, and the number of first lists is equal to the number of waste collection points, then the first waste access information can be obtained. If the number of waste collection points is 3, the first waste access information is 001001000100100010010. The first waste access information represents the access method of all waste collection points within the waste collection planning period.

[0038] Step S102: Calculate the access freedom according to the remaining filling bits and the waste collection cycle.

[0039] Calculate the difference between the waste collection cycle and the remaining filling bits, and reduce the obtained difference by a set value to obtain the access freedom. Preferably, the set value is 1. When the waste collection planning period is set to 7 days and the waste collection cycle is 3, the waste collection planning period is filled with 0010010, and the freedom is 3 - 1 - 1 = 1.

[0040] Step S103: Construct a first set according to the access freedom degree, partition each element in the first set to obtain a corresponding second set for each element, where the size of each element in the second set is equal to the number of benchmark access chunks in the waste removal planning period; select an element from the first set, and use the benchmark padding bits to pad the first list according to the selected element; according to the second set corresponding to the element selected from the first set, delete the corresponding number of benchmark padding bits from the benchmark access chunks of the first list to obtain a second list; generate second waste access information according to the second list and the number of waste removal points.

[0041] Obtain a positive integer not greater than the access freedom degree and construct a first set. The waste removal planning period is set to 7 days. When the waste removal cycle is 3, the waste removal planning period is filled as 0010010, the freedom degree is 1, and the first set is {1}. Integer partition the elements in the first set. The partition values can be repeated. The number of partitions is the number of benchmark access chunks, which is 2. And each element in the second set includes values corresponding one-to-one to the benchmark access chunks. Thus, the second set is {[0,1],[1,0]}. If the obtained freedom degree is 2 and the number of benchmark access chunks is 3, then the first set is {1, 2}. The second set corresponding to element 1 in the first set is {[0,0,1],[0,1,0],[1,0,0]}, and the second set corresponding to element 2 in the first set is [1,1,0],[0,1,1],[1,0,1],[2,0,0],[0,2,0],[0,0,2]}. The size of the elements in the second set is equal to 3, that is, the number of benchmark access chunks. Each digit corresponds to a benchmark access chunk and is used to delete the corresponding number of benchmark padding bits from the benchmark access chunks later. The sum of all digits within each element in the second set is equal to the element in the first set that is correspondingly partitioned.

[0042] Next, select elements from the first set. For example, if the waste collection and transportation planning period is set to 7 days and the waste collection and transportation cycle is 3, the waste collection and transportation planning period is filled with 0010010 (the first list), the degree of freedom is 1, the first set is {1}, and the second set is {[0,1],[1,0]}. Select the element 1 in the first set, fill 1 reference filling bit to the end of the filled waste collection and transportation planning period to get 00100100, and then delete elements according to the second set corresponding to the element. Delete from the filled first list according to the second set to get 0010100 (obtained by deleting according to [0,1], deleting 0 0s from the first reference access block and 1 0 from the second reference access block), 0100100 (obtained by deleting according to [1,0]). Thus, obtain the second list 0010100, 0100100. The second list has the same representational meaning as the first list. The generation method of the second waste access information is the same as that of the first waste access information. If the number of waste collection and transportation points is 3, the second waste access information is 001010000101000010100, 010010001001000100100.

[0043] Step S104, damage and repair the first waste access information and the second waste access information to obtain the third waste access information.

[0044] Step S105, select the waste collection and transportation vehicle path according to the waste collection and transportation vehicle path costs corresponding to the first waste access information, the second waste access information, and the third waste access information.

[0045] Optionally, based on the above embodiments, before the step of damaging and repairing the first waste access information and the second waste access information to obtain the third waste access information, further include:

[0046] Perform capacity repair on the first waste access information and the second waste access information according to the waste accumulation distribution at the waste collection and transportation points.

[0047] Method of capacity repair: For each waste collection and transportation point, check all days that need to be visited (the positions corresponding to 1 in the access information of this point). If the accumulated garbage volume on the day that needs to be visited exceeds the volume that the waste collection and transportation point can accommodate, set the access information of the previous day to 1, and repeat the check until the accumulated garbage volumes corresponding to all days that need to be visited do not exceed the capacity. It should be noted that when the vehicle visits the waste collection and transportation point, all the accumulated garbage at this point will be cleared away.

[0048] Optionally, based on the above embodiments, the reference filling bit represents not visiting the waste collection and transportation point. For example, the reference filling bit is set to 0.

[0049] Based on the first waste access information and the second waste access information, the present invention introduces a variety of destruction methods to obtain a variety of third waste access information. The first is random destruction. On the basis of the above-mentioned embodiments, the destruction and repair of the first waste access information and the second waste access information to obtain the third waste access information include: randomly selecting non-reference filling bits from the first waste access information and the second waste access information, changing the non-reference filling bits into reference filling bits, and then performing capacity repair and cycle repair to obtain the third waste access information. Preferably, the first destruction uses the random destruction method. The second is similarity-based destruction, which is performed according to the similarity of the waste cumulative distribution and the distance between waste collection points. Specifically, it is as follows in steps S201 to S204.

[0050] Optionally, on the basis of the above-mentioned embodiments, the destruction and repair of the first waste access information and the second waste access information to obtain the third waste access information further include:

[0051] Step S201, calculate the similarity of the waste cumulative distribution of waste collection point pairs according to the waste cumulative distribution of waste collection points during the waste collection planning period; determine the first weight according to the dispersion degree and the mean value of all waste cumulative distribution similarities.

[0052] Introduce local neighborhood search to perform neighborhood search on the initially obtained first waste access information and second waste access information to obtain the third waste access information. The present invention determines the positions that need to be destroyed based on the similarity of data distribution and the distance between waste collection points, and then performs repair to achieve local neighborhood search.

[0053] The waste accumulation at waste collection points is periodic. The periodicity of the waste cumulative distribution at waste collection points with large-scale population aggregation is more obvious, such as communities. Usually, the waste discharge volume is more from Friday to Sunday, and relatively less from Monday to Thursday. This has been supported by statistical data from scholars at home and abroad. The waste cumulative distribution in the present invention refers to the daily waste discharge volume during the waste collection planning period. The daily waste discharge volume can be counted by intelligent trash cans with built-in sensors. In this way, the waste cumulative distribution of waste collection points can be obtained. Optionally, it is also possible to continuously count multiple waste collection planning periods, align the waste cumulative distributions of multiple waste collection planning periods, and vertically calculate the mean value of the waste discharge volume on the corresponding same days to obtain the daily waste discharge volume during the waste collection planning period, so as to obtain the waste cumulative distribution.

[0054] Every two waste collection points form a waste collection point pair. Calculate the similarity of the waste cumulative distribution for the waste collection point pairs. Preferably, the Euclidean distance can be used to measure the similarity of the waste cumulative distribution. When using the Euclidean distance, normalization is required to obtain the similarity. The larger the similarity value, the higher the similarity. Obtain the similarity of the waste cumulative distribution for all point pairs, calculate the dispersion degree and the mean value, and determine the first weight. Optionally, the dispersion degree is characterized by the mean square error.

[0055] Optionally, the method for determining the first weight w1: w1 = α + β * (1 - E) + γ * tanh(θ * b * σ). Where α, β, γ, and θ are constant parameters, E is the average waste cumulative distribution similarity, σ is the dispersion degree, and b is the number of waste collection points. The higher the average value of the waste cumulative distribution similarity, the lower the dispersion degree, and the lower the first weight, so as to improve the measurement accuracy of the overall similarity. Preferably, α is taken as 0.7, β is taken as 0.15, γ is taken as 0.15, and θ is taken as 0.9.

[0056] Step S202: Cluster the waste collection points according to the physical distance between the waste collection points to obtain waste collection point clusters; determine the second weight according to the average aggregation degree of all waste collection point clusters.

[0057] Optionally, the k-nearest neighbor clustering method is used for clustering to obtain waste collection point clusters. Optionally, the physical distance is the shortest path distance between the collection points on the map.

[0058] Optionally, the calculation method of the second weight w2: w2 = δ - ξ * c. Where δ and ξ are constant parameters, and c is the average aggregation degree. Preferably, the values of δ and ξ are 0.7 and 0.3 respectively. The aggregation degree of the point clusters is measured by the silhouette coefficient, and the silhouette coefficient is normalized.

[0059] Step S203: Multiply the waste cumulative distribution similarity corresponding to the waste collection point by the first weight to obtain the first similarity corresponding to the waste collection point; multiply the physical distance between the waste collection points by the second weight to obtain the second similarity corresponding to the waste collection point; add the first similarity and the second similarity to obtain the third similarity corresponding to the waste collection point.

[0060] Step S204: Select waste collection points according to the third similarity corresponding to the waste collection points, damage the first waste access information and the second waste access information according to the selected waste collection points, and then perform capacity repair and cycle repair to obtain the third waste access information.

[0061] Optionally, the selection of waste disposal points according to the third similarity corresponding to the waste disposal points includes: randomly selecting waste disposal points to form a third set; selecting other waste disposal points according to the third similarity between the elements in the third set and other waste disposal points, and merging them with the third set to obtain the selected waste disposal points. When selecting other waste disposal points, select the other waste disposal points with the highest third similarity to the elements in the first set. Thus, the elements in the third set are divided into two categories, one is the randomly selected waste disposal points, and the other is the waste disposal points with the highest corresponding third similarity. Thus, the elements in the third set are grouped in pairs to obtain a number of point pairs. If there are multiple randomly selected waste disposal points, the point pairs in the third set may be repeated, and the repeated point pairs need to be removed.

[0062] Optionally, the destruction includes: for each point pair, replacing the waste access information of each point pair with the same other access information. Specifically, the point pair includes two points a and b, the access information of point a is 0010011, and the access information of point b is 0100101, then the access information of the two points can be replaced with 0101010. Then perform capacity repair and cycle repair to obtain the third waste access information. After the destruction and repair of the first waste access information according to each point pair, a kind of third waste access information is obtained. After the destruction and repair of the second waste access information according to each point pair, a kind of third waste access information is obtained.

[0063] Optionally, for each pair of points, replace the access information of one of the points with that of the other point respectively, calculate the path cost after replacement, and select the replacement method with the lower path cost. Specifically, the elements in the third set can form several pairs of points, and each pair of points includes a randomly selected waste collection point and a waste collection point with the highest third similarity to it. For each pair of points, replace the access information of one of the points with that of the other point respectively, calculate the path cost after replacement, and select the replacement method with the lower path cost. For example, the pair of points includes two points a and b, the access information of point a is 0010011, and the access information of point b is 0100101. First, replace the access information of point a in the first waste access information with 0100101, that is, the access information of b, repair the damaged first waste access information to meet the capacity constraint and access cycle constraint, and then calculate the path cost corresponding to the repaired first waste access information. Then, keep the access information of point a in the first waste access information as the original 0010011, replace the access information of point b with 0010011, repair the damaged first waste access information to meet the capacity constraint and cycle constraint, and then calculate the path cost corresponding to the repaired first waste access information. Select the replacement method with the lower path cost, and thus obtain a new waste access information, that is, one of the third waste access information.

[0064] After damaging the first waste access information and the second waste access information, the repairs that need to be carried out include: capacity repair and cycle repair. The capacity repair has been described above. The method of cycle repair: for each waste collection point, check whether the access cycle is met. If not, increase the access opportunity until the access time interval is met.

[0065] Optionally, in step S105, selecting the waste collection vehicle path according to the waste collection vehicle path costs corresponding to the first waste access information, the second waste access information, and the third waste access information includes:

[0066] Step S301, according to the waste collection vehicle path costs corresponding to the first waste access information, the second waste access information, and the third waste access information, select several waste access information to form the first optimization information group;

[0067] Step S302, damage and repair the first optimization information group to obtain the second optimization information group;

[0068] Step S303, according to the waste collection vehicle path costs corresponding to the first optimization information group and the second optimization information group, select several waste access information to form the first optimization information group;

[0069] Step S304. Repeat steps S302 and S303 for a set number of times, and select the waste collection vehicle route based on the waste collection vehicle route cost corresponding to the first optimization information group. Preferably, when selecting the first optimization information group, select the waste visit information with a low cost. Preferably, select the waste collection point visit information with the lowest waste collection vehicle route cost as the final visit plan, and solve the shortest waste collection vehicle route based on the waste visit points every day, so as to obtain the waste collection vehicle route for the entire waste collection planning period. There are many methods to solve the vehicle route, and the classic vehicle route solving algorithm can be used to obtain it. Optionally, a mathematical solver can be used, or a genetic algorithm can also be used.

[0070] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An optimization method for the path of waste collection vehicles based on the Internet of Things, characterized in that, Including the following steps: Step S101: Generate a reference access chunk according to the waste collection cycle; repeatedly fill the reference access chunk into the waste collection planning period until the remaining filling bits of the waste collection planning period are less than the number of bits of the reference access chunk, and use the reference filling bits to fill the remaining filling bits of the waste collection planning period to obtain a first list; generate first waste access information according to the first list and the number of waste collection points; Step S102: Calculate the access freedom according to the remaining filling bits and the waste collection cycle; Step S103: Construct a first set according to the access freedom, divide each element in the first set to obtain a corresponding second set for each element, and the size of each element in the second set is equal to the number of reference access chunks in the waste collection planning period; Select an element from the first set, and use the reference filling bits to fill the first list according to the selected element; Delete the corresponding number of reference filling bits from the reference access chunks of the first list according to the second set corresponding to the element selected from the first set to obtain a second list; generate second waste access information according to the second list and the number of waste collection points; Step S104: Damage and repair the first waste access information and the second waste access information to obtain third waste access information; Step S105: Select a waste collection vehicle route according to the waste collection vehicle route costs corresponding to the first waste access information, the second waste access information, and the third waste access information.

2. The method for optimizing the path of waste collection vehicles based on the Internet of Things according to claim 1, wherein, Before damaging and repairing the first waste access information and the second waste access information to obtain third waste access information, it further includes: Perform capacity repair on the first waste access information and the second waste access information according to the waste accumulation distribution of the waste collection points.

3. The method for optimizing the path of waste collection vehicles based on the Internet of Things according to claim 1, wherein The calculating the access freedom according to the remaining filling bits and the waste collection cycle includes: Calculate the difference between the waste collection cycle and the remaining filling bits, and reduce the obtained difference by a set value to obtain the access freedom.

4. The method for optimizing the path of waste collection vehicles based on the Internet of Things according to claim 1, wherein, The constructing the first set includes: Obtain a positive integer not greater than the access freedom and construct a first set.

5. The method for optimizing the path of waste collection vehicles based on the Internet of Things according to claim 1, characterized in that, The reference access chunk represents an access method that satisfies the waste collection cycle.

6. The method for optimizing the path of waste collection vehicles based on the Internet of Things according to claim 1, wherein The reference filling bit represents not accessing the waste collection point.

7. The method for optimizing the path of waste collection vehicles based on the Internet of Things according to claim 1, characterized in that The damaging and repairing the first waste access information and the second waste access information includes: Calculate the waste accumulation distribution similarity of the waste collection point pairs according to the waste accumulation distribution of the waste collection points within the waste collection planning period; determine the first weight according to the dispersion degree and the mean value of all waste accumulation distribution similarities; Cluster the waste collection points according to the physical distance between the waste collection points to obtain waste collection point clusters; determine the second weight according to the average aggregation degree of all waste collection point clusters; Multiply the waste accumulation distribution similarity of the waste transfer point pair by the first weight to obtain the first similarity corresponding to the waste transfer point; multiply the physical distance between the waste transfer points by the second weight to obtain the second similarity corresponding to the waste transfer point; add the first similarity and the second similarity to obtain the third similarity corresponding to the waste transfer point. Select waste transfer points according to the third similarity corresponding to the waste transfer points, damage the first waste access information and the second waste access information according to the selected waste transfer points, and then perform waste access repair to obtain the third waste access information.

8. The method for optimizing the path of waste collection vehicles based on the Internet of Things according to claim 1, wherein, Selecting waste transfer points according to the third similarity corresponding to the waste transfer points includes: randomly selecting waste transfer points, and then selecting other waste transfer points according to the third similarity between the selected waste transfer points and other waste transfer points to obtain the selected waste transfer points.

9. A computer device, characterized in that, The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for optimizing the path of waste transfer vehicles based on the Internet of Things according to any one of claims 1 to 8.

10. A computer-readable storage medium, in which a computer program is stored, characterized in that, When the computer program is executed, it implements the method for optimizing the path of waste transfer vehicles based on the Internet of Things according to any one of claims 1 to 8.

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