CN112633603B - Method for adjusting distribution density of dustbin and visualization system thereof - Google Patents
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Abstract
The invention discloses a method for adjusting distribution density of a dustbin and a visualization system thereof, wherein the method comprises the following steps: acquiring and visualizing the use information of the garbage cans of different types of garbage; establishing a functional relation between the distribution density of the garbage can and the scheduling of the garbage truck based on the use information of the garbage can; obtaining an optimization scheme of the distribution density of the garbage bin based on a functional relation between the distribution density of the garbage bin and the scheduling of the garbage truck; adjusting the distribution density of the dustbin based on the optimization scheme; and auditing the optimization scheme. According to the method for adjusting the distribution density of the dustbin and the visualization system thereof, provided by the invention, the functional relation between the distribution density of the dustbin and the scheduling of the garbage truck is established based on the use information of the dustbin, so that an optimized scheme of the distribution density of the dustbin is obtained, the dustbin resources are fully utilized and reasonably planned, and the purposes of saving resources and maximizing the utilization of the resources are achieved.
Description
Technical Field
The invention relates to the field of garbage classification, in particular to a method for adjusting distribution density of a garbage can and a visualization system thereof.
Background
In recent years, china is steadily pushing important cities to implement forced garbage classification, construction of classification throwing, receiving and handling facilities is quickened, related laws and regulations and standard systems of garbage classification are established, and a replicable and generalized household garbage classification mode is formed. At present, in the process of enforcing the forced classification of the garbage in key cities, due to the lack of practical experience of garbage classification, the problems of waste of garbage can resources, untimely cleaning of overflow garbage cans and the like caused by unreasonable distribution of the garbage cans for receiving different types of garbage occur:
1. the garbage cans are generally uniformly distributed in cities, and urban residents usually move to the garbage cans which are relatively close to the urban residents to throw garbage, but the density of the urban residents is dynamically changed, so that the garbage generation amount in different areas and nearby positions is also dynamically changed. In general, the urban residents in different areas are not uniformly distributed in the garbage generation amount, so that the garbage cans near some areas and positions are often in an overflow state, and the garbage cans near some areas and positions are often in an empty state, so that the garbage can resources are wasted.
2. As the policy of sorting garbage advances, sanitation companies typically configure one garbage bin for each type of garbage at the place where garbage is put, but in general, the proportion of different types of garbage is different in different areas, which will result in that the garbage bin receiving one type of garbage is often in an overflow state, while the garbage bin receiving another type of garbage is often in a vacant state, resulting in waste of garbage bin resources, and causing great pressure on the overall arrangement of garbage collection vehicles.
3. Because residents cannot acquire the distribution condition and the overflow condition of the garbage cans for receiving different types of garbage in real time, the extreme condition that residents hold certain garbage everywhere and find the garbage cans for receiving the garbage can without being overflowed sometimes appears, and a plurality of inconveniences are brought to the life of the residents.
Therefore, there is a need for a method for adjusting distribution density of a dustbin and a visualization system thereof, so as to solve the above problems.
Disclosure of Invention
In the summary, a series of concepts in a simplified form are introduced, which will be further described in detail in the detailed description. The summary of the invention is not intended to define the key features and essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
The invention provides a method for adjusting distribution density of a dustbin, which comprises the following steps:
acquiring and visualizing the use information of the garbage cans of different types of garbage;
establishing a functional relation between the distribution density of the garbage can and the scheduling of the garbage truck based on the use information of the garbage can;
obtaining an optimization scheme of the distribution density of the garbage bin based on a functional relation between the distribution density of the garbage bin and the scheduling of the garbage truck;
adjusting the distribution density of the dustbin based on the optimization scheme;
and auditing the optimization scheme.
Further, the distribution density of the dustbin is expressed as:
wherein j represents a garbage type number; i represents a region number; k represents a dustbin model number; ρ r,j,i,k The distribution density of a kth type number dustbin for receiving jth garbage in an ith area is represented; a is that i A region area representing the i-th region; n (N) gb,j,i,k The number of the kth type number dustbin for receiving the jth type garbage in the ith area is represented.
Further, the functional relationship between the distribution density of the dustbin and the garbage truck shift is expressed as:
wherein j represents a garbage type number; i represents a region number; k represents a dustbin model number; ρ r,j,i,k The distribution density of a kth type number dustbin for receiving jth garbage in an ith area is represented; a is that i A region area representing the i-th region; p represents the number of the garbage truck type; x is x c Represents the total number of types of garbage collection vehicle types (x c Is just in orderA number); n is n a Represents the total number of regions (n a Is a positive integer); n is n r Representing the total number of garbage classification categories (n r Is a positive integer); x is x j,i Indicating the total number of types of dustbin types (x j,i Is a positive integer); v (V) car,p Representing the capacity of a single type p refuse collection vehicle loaded with refuse; n (N) car,p The number of the garbage truck with the p type number is indicated; v (V) r,k Representing the capacity of a single kth type number dustbin; a. b is a relaxation factor, and is an adjustable parameter, and the value interval of a and b is [0,1 ]]。
Further, the optimizing scheme for obtaining the distribution density of the garbage can based on the functional relation between the distribution density of the garbage can and the shift of the garbage truck comprises the following steps:
defining input variables and/or constraints of the optimization scheme;
defining an objective function of the optimization scheme;
and obtaining an optimization scheme of the distribution density of the dustbin by using a planning algorithm.
Further, the use information of the garbage cans of different types of garbage comprises garbage can overflow information or cover opening frequency information.
Further, visualizing the usage information of the bins of different types of garbage includes forming a hotspot graph.
Further, the method further comprises:
when the optimization scheme passes the auditing, adopting the optimization scheme;
when the optimization scheme fails the audit, re-executing the steps of claim 1 to obtain a second optimization scheme of the distribution density of the garbage can.
Further, acquiring the usage information of the dustbin of different types of garbage further includes: and obtaining the statistical characteristics and rules of the use information of the dustbin by using a big data analysis technology.
The invention also provides a visualization system for adjusting the distribution density of the dustbin, which comprises:
and the display equipment is used for displaying the navigation route map of the garbage truck, which is generated according to the optimization scheme obtained by the method.
The invention also provides a visualization system for adjusting the distribution density of the dustbin, which comprises:
and the display equipment is used for displaying different types of garbage throwing navigation route patterns generated according to the optimization scheme obtained by the method.
According to the method for adjusting the distribution density of the dustbin and the visualization system thereof, provided by the invention, the functional relation between the distribution density of the dustbin and the scheduling of the garbage truck is established based on the use information of the dustbin, so that an optimized scheme of the distribution density of the dustbin is obtained, the dustbin resources are fully utilized and reasonably planned, and the purposes of saving resources and maximizing the utilization of the resources are achieved.
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The following drawings are included to provide an understanding of the invention and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments of the invention and their description to explain the principles of the invention.
In the accompanying drawings:
fig. 1 is a flow chart of a method of adjusting distribution density of a dustbin according to an embodiment of the present invention.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced without one or more of these details. In other instances, well-known features have not been described in detail in order to avoid obscuring the invention.
In order that the invention may be fully understood, a detailed description will be given below to illustrate one method of adjusting the distribution density of a dustbin and a visualization system thereof. It will be apparent that the invention is not limited to the specific details of those skilled in the art of garbage classification. Preferred embodiments of the present invention are described in detail below, however, the present invention may have other embodiments in addition to these detailed descriptions.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is intended to include the plural unless the context clearly indicates otherwise. Furthermore, it will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Exemplary embodiments according to the present invention will now be described in more detail with reference to the accompanying drawings. These exemplary embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. It should be appreciated that these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of these exemplary embodiments to those skilled in the art. In the drawings, thicknesses of layers and regions are exaggerated for clarity, and the same reference numerals are used to denote the same elements, so that descriptions thereof will be omitted.
At present, there is no unified and perfect garbage can layout scheme for garbage classification in China, garbage cans are uniformly arranged in cities, the positions of the garbage cans are arranged at fixed intervals no matter how much garbage is generated in areas and how much different types of garbage occupy, and the number of the garbage cans is determined according to the types of garbage classification. Along with the acceleration of the industrialization process, the garbage yield of people in industry, agricultural production and daily life is increased; with the acceleration of the urban process, the population flowing speed is greatly accelerated, and the garbage generation amount is increasingly unevenly distributed; with the perfection of urban functional partitions, the proportion difference of different types of garbage in different areas is more and more obvious. In order to realize the whole coverage of the classified collection garbage, a large number of garbage cans for receiving different types of garbage are required to be arranged, if a reasonable layout scheme is not available, the problems that the garbage cans are wasted in resources, the garbage cans are overflowed and are not cleared in time and the like are caused, huge pressure is caused for classifying and throwing garbage to residents and arranging garbage clearance vehicles in an overall mode, and negative effects are caused on implementation of garbage classification.
In view of the above problems, the present invention provides a method for adjusting distribution density of a dustbin, as shown in fig. 1, comprising the steps of:
step S101: acquiring and visualizing the use information of the garbage cans of different types of garbage;
step S102: establishing a functional relation between the distribution density of the garbage can and the scheduling of the garbage truck based on the use information of the garbage can;
step S103: obtaining an optimization scheme of the distribution density of the garbage bin based on a functional relation between the distribution density of the garbage bin and the scheduling of the garbage truck;
step S104: adjusting the distribution density of the dustbin based on the optimization scheme;
step S105: and auditing the optimization scheme.
First, the distribution density of the dustbin is expressed as:
wherein j represents a garbage type number; i represents a region number; k represents a dustbin model number; ρ r,j,i,k The distribution density of a kth type number dustbin for receiving jth garbage in an ith area is represented; a is that i A region area representing the i-th region; n (N) gb,j,i,k The number of the kth type number dustbin for receiving the jth type garbage in the ith area is represented.
In an embodiment, an sanitation company is responsible for dividing a patch area into a plurality of areas, and distribution densities of garbage cans of different types received by different areas are calculated. Among them, the tile dividing method includes, but is not limited to, dividing in units of cells.
The total capacity of the dustbin for receiving certain garbage in a certain area is obtained by the following steps:
wherein x is j,i Indicating the total number of types of dustbin types (x j,i Is a positive integer); v (V) r,k Representing the capacity of a single kth type number dustbin; v (V) total,j,i Indicating the total capacity of the bin for receiving class j waste in the i-th zone.
First, step S101 is performed: and acquiring and visualizing the use information of the garbage cans of different types of garbage.
Illustratively, obtaining usage information for a dustbin of different types of refuse includes: and acquiring the use information of the garbage cans of different types of garbage by using a sensor technology, wherein the use information comprises, but is not limited to, garbage can overflow information and cover opening frequency information.
The present use information of the dustbin is displayed and stored by adopting a visualization technology, so that a worker can intuitively monitor the use condition of the dustbin, and meanwhile, the worker can intuitively evaluate the advantages and disadvantages of the dustbin layout scheme through comparison of the present record and the historical record. Wherein the visualization technique includes, but is not limited to, forming a hotspot graph.
Further, acquiring the usage information of the dustbin of different types of garbage further includes: and obtaining the statistical characteristics and rules of the use information of the dustbin by using a big data analysis technology.
In an embodiment, a history record of garbage information cleared by sanitation companies is called, statistical characteristics and rules of different types of garbage generation amounts in different areas in unit time are obtained by utilizing a big data analysis technology, and garbage generation rates of corresponding areas and garbage types are calculated. Where a unit time includes, but is not limited to, in hours, in days, and in quarters. The garbage generation rate is defined as follows:
wherein Δt represents a time interval; v r,j,i Representing the average generation rate of the jth garbage in the ith area in the delta t time interval; t (T) r,j,i The generation amount of the jth garbage in the ith area is expressed in terms of volume in the delta t time interval.
Next, step S102 is performed: and establishing a functional relation between the distribution density of the garbage can and the scheduling of the garbage truck based on the use information of the garbage can.
In order to avoid the situation that the garbage truck cannot be filled with garbage to be transported, the total capacity of the garbage truck is not less than the garbage generation amount in the time interval of the garbage truck scheduling, and in order to avoid the situation that the garbage can overflows, the total capacity of the garbage truck is not less than the garbage generation amount in the time interval of the garbage truck scheduling, so that the garbage truck is obtained:
wherein p represents the model number of the garbage truck; x is x c Represents the total number of types of garbage collection vehicle types (x c Is a positive integer); n is n a Represents the total number of regions (n a Is a positive integer); n is n r Representing the total number of garbage classification categories (n r Is a positive integer); v (V) car,p Representing the capacity of a single type p refuse collection vehicle loaded with refuse; n (N) car,p The number of the garbage truck with the p type number is indicated; v (V) r,k Representing the capacity of a single kth type number dustbin; Δt represents a time interval of the garbage truck scheduling; a. b is a relaxation factor, and is an adjustable parameter, and the value interval of a and b is [0,1 ]]. Wherein, the closer a is to 1, the higher the volume utilization rate of the carriage of the garbage truck for loading garbage is indicated; the closer b is to 1, the higher the volume utilization of the dustbin.
Substituting the formula (1) into the formulas (4) and (5), and obtaining the functional relation between the distribution density of the garbage can and the class of the garbage truck after finishing as follows:
wherein j represents a garbage type number; i represents a region number; k represents a dustbin model number; ρ r,j,i,k The distribution density of a kth type number dustbin for receiving jth garbage in an ith area is represented; a is that i A region area representing the i-th region; p represents the number of the garbage truck type; x is x c Represents the total number of types of garbage collection vehicle types (x c Is a positive integer); n is n a Represents the total number of regions (n a Is a positive integer); n is n r Representing the total number of garbage classification categories (n r Is a positive integer); x is x j,i Indicating the total number of types of dustbin types (x j,i Is a positive integer); v (V) car,p Representing the capacity of a single type p refuse collection vehicle loaded with refuse; n (N) car,p The number of the garbage truck with the p type number is indicated; v (V) r,k Representing the capacity of a single kth type number dustbin; a. b is a relaxation factor, and is an adjustable parameter, and the value interval of a and b is [0,1 ]]。
Next, step S103 is performed: and obtaining an optimization scheme of the distribution density of the garbage bin based on a functional relation between the distribution density of the garbage bin and the scheduling of the garbage truck.
Illustratively, the optimizing scheme for obtaining the distribution density of the garbage can based on the functional relation between the distribution density of the garbage can and the shift of the garbage truck comprises the following steps:
defining input variables and/or constraints of the optimization scheme;
defining an objective function of the optimization scheme;
and obtaining an optimization scheme of the distribution density of the dustbin by using a planning algorithm.
In an embodiment, the steerable input variables of the bin layout optimization problem are defined according to local garbage classification policies and sanitation operation modes, including, but not limited to, bin distribution density for receiving different types of garbage, number of garbage truck simultaneous trips for receiving different types of garbage, daily trip frequency. Constraint conditions of the dustbin layout optimization problem are defined according to actual personnel and equipment conditions of sanitation companies and assessment standards, for example: the daily frequency of the garbage truck for receiving garbage of a certain type is not higher than m times (m is a positive integer).
In an embodiment, the optimization objective includes, but is not limited to, rationally utilizing local garbage classification-related financial funds, reducing sanitation company operating costs as a garbage can layout optimization objective, and thereby defining objective functions such as:
J＝w 1 (1-a) 2 +w 2 (1-b) 2 (7)
wherein J represents an objective function; w (w) 1 、w 2 And the weighting factors are represented and used for adjusting the priority among different optimization targets.
Minimizing the objective function J in equation (7) means that bringing a, b closest to 1, and satisfying the solution of the objective function J in equation (7) is a solution that maximizes the capacity utilization of the garbage truck and the garbage can. Wherein the definition of the objective function depends on the choice of the optimization objective, and thus the objective function according to the present invention includes, but is not limited to, equation (7).
In an embodiment, a planning algorithm is utilized to obtain a result that satisfies the functional relationship between the distribution density of the bins and the garbage truck shift in S3 without violating the constraints in S4 and that is capable of minimizing the objective function in S5. Wherein the solution results include, but are not limited to, distribution densities of bins receiving different types of garbage at different areas, and the planning algorithm includes, but is not limited to, a linear planning algorithm. Meanwhile, since the variable of garbage generation amount involved in the modeling and solving process of the garbage layout optimization problem is a random variable, the confidence level of the solving result needs to be improved as much as possible by combining a random process analysis and processing technology.
The method utilizes a planning algorithm technology and defines parameters, constraint conditions and objective functions for quantitatively describing the distribution of the dustbin, so that the problem of optimization of decision processes related to the dustbin layout for receiving different types of garbage is solved, the obtained optimal scheme has strict mathematical derivation basis, and the dynamic processes of industrialization, urban and urban partition functionalization are fully considered, so that the optimal scheme of the dustbin layout for receiving different types of garbage, which is matched with the current process, can be calculated in real time.
Next, step S104 is performed: and adjusting the distribution density of the dustbin based on the optimization scheme.
In an embodiment, the garbage bin layout optimization scheme is used for comparing the recommended distribution density of the garbage bins which are used for receiving different types of garbage in different areas, the recommended number of the garbage bins which are used for receiving different types of garbage in different areas can be calculated according to the formula (1), the garbage bin layout optimization scheme is compared with the existing situation, and the position distribution and the number increase and decrease of the garbage bins are adjusted, for example: and (3) moving the garbage bin which is in excess of the certain position and receives the certain garbage to the position which is lack of the garbage bin which receives the garbage, and increasing or decreasing the number of the garbage bins which receive the garbage if the recommended number requirement cannot be met, so as to realize the optimization scheme of the garbage bin layout.
Next, step S105 is performed: and auditing the optimization scheme.
Comparing and evaluating the visualization results of the use information of the dustbin before and after optimizing the dustbin layout scheme, checking whether the dustbin with high use frequency is overflowed frequently and is not cleared, and whether the dustbin with low use frequency is not used for a long time, if the dustbin with low use frequency is not used for a long time, the optimized scheme passes the checking, if the dustbin layout scheme is not used for a long time, a worker needs to finely adjust the optimized scheme of the dustbin layout according to actual conditions, if the dustbin layout scheme is occasionally used for a short time, the worker needs to return to the step S102, recheck and update statistical characteristics, rules and constraint conditions related to the garbage generation amount, and repeat the steps S102 to S103 to update the optimized scheme of the dustbin layout.
Compared with the traditional method that the positions of the garbage cans are arranged at fixed intervals and the number of the garbage cans is determined according to the types of garbage classification, the method can build connection between the data features of different types of garbage production and the arrangement of the garbage cans, the decision process of the garbage can layout scheme is obtained through strict mathematical derivation, when the data features of different types of garbage production in the region change, the garbage production distribution model parameters are changed, the planning algorithm is executed again, and the optimal scheme of the garbage can layout combined with the actual conditions of the region can be obtained, and the process has repeatability and strong operability.
The invention also provides a visualization system for adjusting the distribution density of the dustbin, which comprises:
and the display equipment is used for displaying the navigation route map of the garbage truck, which is generated according to the optimization scheme obtained by the method.
In the embodiment, under the condition of given dustbin layout, according to the current dustbin loaded garbage amount and the position of the dustbin loaded garbage amount, the capacity of the garbage carriage loaded in the garbage truck and the departure place of the garbage truck, the sanitation company assessment standard is taken as a constraint condition, the sanitation company operation cost is reduced as an optimization target, the optimal scheduling scheme of the garbage truck at the current moment is obtained by using a planning algorithm, a visual navigation route map of the garbage truck at the current moment is generated according to the optimal scheduling scheme of the garbage truck at the current moment, and a driver of the garbage truck is guided to go to finish garbage transfer.
The system guides sanitation companies to comprehensively arrange the garbage disposal vehicles in a visual mode, dynamically adjusts the routes, the discharging frequency and the like of the garbage disposal vehicles, and can avoid the problems that the overflow garbage bin is not timely disposed and the carriage loaded with garbage on the garbage disposal vehicle is not fully utilized.
The invention also provides a visualization system for adjusting the distribution density of the dustbin, which comprises:
and the display equipment is used for displaying different types of garbage throwing navigation route patterns generated according to the optimization scheme obtained by the method.
In the embodiment, residents can enter the system and select the type of garbage to be put on the terminal, the system automatically searches the nearest non-overflowed garbage bin for receiving the type of garbage according to the current information stored in the server, and an optimal route is planned to form a navigation route map.
The system displays the distribution condition and the overflow condition of the garbage cans for receiving different types of garbage to residents in a visual mode through various channels such as APP, applet and public number, optimizes the route of garbage throwing of the residents, and improves the user experience of the residents in the garbage classification throwing process.
The invention not only defines the parameters for quantitatively describing the distribution of the garbage cans, but also provides an optimization algorithm for adjusting the position distribution and the number increase and decrease of the garbage cans for receiving different types of garbage. According to the optimization principle, the invention relies on planning algorithm technology to dynamically solve the problem of decision process optimization related to the garbage bin layout for receiving different types of garbage, and guides the position distribution and number increase and decrease of the garbage bins for receiving different types of garbage according to the solving result so as to adapt to different industrialized, urban and urban partition functionalization processes, fully utilize and reasonably plan garbage bin resources, and achieve the purposes of saving resources and maximizing resource utilization. The method for adjusting the distribution density of the dustbin has clear physical significance and a strict mathematical derivation process, and can theoretically obtain an optimization scheme of the dustbin layout for receiving different types of garbage.
Furthermore, the invention establishes a visualization system for adjusting the distribution density of the dustbin, and the system can intuitively display the distribution condition and the overflow condition of the dustbin for receiving different types of garbage by means of a visualization technology, thereby not only helping staff evaluate the rationality and check the layout scheme of the dustbin layout, but also guiding the scheduling of a garbage truck and providing a resident for throwing the garbage route.
The present invention has been illustrated by the above-described embodiments, but it should be understood that the above-described embodiments are for purposes of illustration and description only and are not intended to limit the invention to the embodiments described. In addition, it will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that many variations and modifications are possible in light of the teachings of the invention, which variations and modifications are within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. A method of adjusting distribution density of a dustbin, comprising the steps of:
step S101: acquiring and visualizing the use information of the garbage cans of different types of garbage;
step S102: establishing a functional relationship between the distribution density of the garbage cans for receiving different types of garbage and the garbage truck scheduling for receiving different types of garbage based on the use information of the garbage cans;
step S103: obtaining an optimization scheme of the distribution density of the garbage bin based on the functional relationship between the distribution density of the garbage bin for receiving different types of garbage and the garbage truck shift for receiving different types of garbage, wherein the functional relationship between the distribution density of the garbage bin and the garbage truck shift is expressed as:
wherein j represents a garbage type number; i represents a region number; k represents a dustbin model number; ρ r,j,i,k The distribution density of a kth type number dustbin for receiving jth garbage in an ith area is represented; a is that i A region area representing the i-th region; p represents the number of the garbage truck type; x is x c Indicating the total number of types of garbage collection vehicle types of sanitation companies, x c Is a positive integer; n is n a Represents the total number of regions, n a Is a positive integer; n is n r Represents the total number of garbage classification categories, n r Is a positive integer; x is x j,i Indicating the total number of types of garbage cans for receiving the jth garbage in the ith area and x j,i Is a positive integer; v (V) car,p Representing the capacity of a single type p refuse collection vehicle loaded with refuse; n (N) car,p The number of the garbage truck with the p type number is indicated; v (V) r,k Representing a single type k modelThe capacity of the garbage bin; a. b is a relaxation factor, and is an adjustable parameter, and the value interval of a and b is [0,1 ]]；
Step S104: adjusting the distribution density of the dustbin based on the optimization scheme;
step S105: and auditing the optimization scheme.
2. A method of adjusting the distribution density of a dustbin as claimed in claim 1, wherein the distribution density of the dustbin is expressed as:
wherein j represents a garbage type number; i represents a region number; k represents a dustbin model number; ρ r,j,i,k The distribution density of a kth type number dustbin for receiving jth garbage in an ith area is represented; a is that i A region area representing the i-th region; n (N) gb,j,i,k The number of the kth type number dustbin for receiving the jth type garbage in the ith area is represented.
3. The method for adjusting the distribution density of the dustbin according to claim 1, wherein the optimizing scheme for obtaining the distribution density of the dustbin based on the functional relationship between the distribution density of the dustbin and the refuse collection vehicle shift comprises:
defining input variables and/or constraint conditions of the optimization scheme, wherein the input variables comprise distribution density of garbage cans for receiving different types of garbage, the number of garbage disposal trucks for receiving different types of garbage simultaneously, and daily frequency of truck departure, and the constraint conditions comprise that the daily frequency of truck departure of garbage disposal trucks for receiving certain types of garbage is not higher than m times, and m is a positive integer;
defining an objective function of the optimization scheme;
and obtaining an optimization scheme of the distribution density of the dustbin by using a planning algorithm.
4. The method of claim 1, wherein the usage information of the different types of garbage includes garbage bin overflow information or uncovering frequency information.
5. The method of adjusting a distribution density of a dustbin according to claim 1, wherein visualizing usage information of different types of refuse comprises forming a heatmap.
6. The method of adjusting the distribution density of a dustbin according to claim 1, further comprising:
when the optimization scheme passes the auditing, adopting the optimization scheme;
when the optimization scheme fails the audit, re-executing the steps 102 and 103 of claim 1 to obtain a second optimization scheme of the distribution density of the garbage can.
7. The method of adjusting a distribution density of a dustbin as in claim 1, wherein obtaining usage information for different types of refuse further comprises: and obtaining the statistical characteristics and rules of the use information of the dustbin by using a big data analysis technology.
8. A visualization system for adjusting distribution density of a dustbin, comprising:
a display device for displaying a garbage truck navigation roadmap generated according to an optimization scheme obtained by the method of any one of claims 1-7.
9. A visualization system for adjusting distribution density of a dustbin, comprising:
display device for displaying different types of garbage placement navigation roadmaps generated according to an optimization scheme obtained by the method according to any one of claims 1-7.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015135308A1 (en) * | 2014-03-14 | 2015-09-17 | 湖南大学 | Intelligent and informatized multi-vehicle collaboratively operating municipal refuse collection and transfer system and method |
| CN105197466A (en) * | 2015-10-28 | 2015-12-30 | 杨丽君 | Intelligent garbage can |
| CN105700501A (en) * | 2016-01-30 | 2016-06-22 | 广西升禾环保科技股份有限公司 | An operation working system with a garbage spot monitor function and used for environmental sanitation |
| CN111223029A (en) * | 2020-01-10 | 2020-06-02 | 重庆高洁环境绿化工程集团有限公司 | Intelligent environmental sanitation management system and method |
| CN111931986A (en) * | 2020-07-08 | 2020-11-13 | 淮阴工学院 | Garbage clearing and transporting vehicle route optimization method and urban garbage clearing and transporting ecological system |
-
2020
- 2020-12-30 CN CN202011643023.6A patent/CN112633603B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015135308A1 (en) * | 2014-03-14 | 2015-09-17 | 湖南大学 | Intelligent and informatized multi-vehicle collaboratively operating municipal refuse collection and transfer system and method |
| CN105197466A (en) * | 2015-10-28 | 2015-12-30 | 杨丽君 | Intelligent garbage can |
| CN105700501A (en) * | 2016-01-30 | 2016-06-22 | 广西升禾环保科技股份有限公司 | An operation working system with a garbage spot monitor function and used for environmental sanitation |
| CN111223029A (en) * | 2020-01-10 | 2020-06-02 | 重庆高洁环境绿化工程集团有限公司 | Intelligent environmental sanitation management system and method |
| CN111931986A (en) * | 2020-07-08 | 2020-11-13 | 淮阴工学院 | Garbage clearing and transporting vehicle route optimization method and urban garbage clearing and transporting ecological system |
Non-Patent Citations (1)
| Title |
|---|
| "校园垃圾箱优化配置研究";石宝玉 等;《牡丹江师范学院学报（自然科学版）》(第1期);原文第15-18页 * |
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